commit 401c661dcbb665dbaa4c8ff8766bd74d9b6515ec Author: TinyAtoms Date: Fri Mar 27 08:07:26 2020 -0300 partway through 3.2 diff --git a/All Figures.zip b/All Figures.zip new file mode 100644 index 0000000..59b03eb Binary files /dev/null and b/All Figures.zip differ diff --git a/ISLR Seventh Printing.pdf b/ISLR Seventh Printing.pdf new file mode 100644 index 0000000..4796dcc Binary files /dev/null and b/ISLR Seventh Printing.pdf differ diff --git a/ISLR/islr-ch2.md b/ISLR/islr-ch2.md new file mode 100644 index 0000000..1723946 --- /dev/null +++ b/ISLR/islr-ch2.md @@ -0,0 +1,241 @@ + +# Notation +A dataset contains *p* features and has *n* datapoints +so s dataset that has weight, length, age of 1000 people has +p=3 features and n=1000 points. + +# Chapter 2 : Statistical learning + +## 2.1 What is statistical learning? +Statistical learning is the method were we take in a set of **features, predictors, or independent variables** +to predict the **response or dependent variable** +The first are generally called X and the latter called y. + +The function looks like this: + +y = f(X) + $\epsilon$ +where f(X) is the systematic info about y and $\epsilon$ is the random, non-reducable error. y(X) also contains an error, +but that can be reduced by selecting another, more appropriate model to train. $\epsilon$ is nonzero, because it may contain variables we haven't measured, for example if we were predicting how a patient might respond to drugs but didn't measure the weight of patients, or may contain unmeasurable variances, such as manufacturer variance in pillmaking so each pill doesn't contain exactly the same ammount of active ingredient. + +The irreducable error will always place an upper bound on the accuracy of our model, and in practice, we will not know what the value of this error is. + +### Inference + +We don't always want to predict y, we sometimes just want to know the relationship betwen X and y. When doing this, we don't want $\hat{y}$ to be treated like a black box. +In this setting, we may be seeking one or more of the following answers: + +1. Which predictors are associated with the response? It's often the case that only some of the features are ehavily associated with y, and identifying the few important factors out of a large set of variables may be worthwile. + +2. What is the relationship between the response and each predictor? Features may have a possitive or negative or no correlation with theresponse. Depending on the complexity of f, the relationship between the response and a given predictor may also depend on the values of the other predictors. + +3. Can the relationship between Y and each predictor be adequately summarized using a linear equation, or is the relationship more complicated? Historically, we've used linear methods to estimate f(X), which sometimes is reasonable and desirable, but often the relationship is more complicated. + + + +Modeling can also be done for both inference and prediction purposes. Depending on what our goal is, different methods of estimating f will be appropriate. For example, *linear models* allow for relatively simple and interpretable inference, but may not yield as accurate predictions, while some highly nonlinear approaches may provide very accurate predictions, but will be less interpretable. + +### 2.1.2 How do we estimate f? +We'll explore various approaches throughout this book, and these book generally share some characteristics. We will always assume that we observed a set of *n* datapiubts, and these are called training data because we'll use this data to train, teach, fit the model. $x_{ij}$ is the value of the j'th predictor for observation i. +Correspondingly, $y_i$ is the response variable for the i'th observation. +Then our training data consists of +$\{(x_1, y_1), (x_2, y_2), \dotso (x_n, y_n)\}$ where $x_i = (x_{i1}, x_{i2}, \dotso , x_{ip} )^T$ + +Our goal is to apply a method to the training data in order to estimate the unknown function f. In other words, we want to find the function $\hat{y}$ such that $Y \approx \hat{f}(X)$ for any observation (X,Y). Broadly speaking, most methods can be divided into either *parametric* or *non-parametric.* + +### Parametric methods +These methods invove a 2 step model-based approach +1. First, we make an assumption about the form or shape of f. For example, a simple assumption is that f is linear: +f(X) = a0 + b1 X1 + b2 X2 + ... + bp Xp +This is a linear model, extensively discussed in chapter 3. Once this assumption is made, the problem of estimating is greatly simplified. Instead of having to estimate an entirely arbitrary p-dimensional function f(X), we only need to estimate p+1 coefficients. + +2. After a model has been selected, we use a procedure that fits or trains the model. In case of the linear model, we need to estimate the parameters. The most common approach to fitting the model is the *(ordinary) least squares.* However, this is only one of the possible ways. + +The model based approach is refered to as parametric; it reduces the problem of estimating f down to estimating a set of parameters. The downside is that the chosen model will usually not match the true unknown form of f. If our model is too far from true f, our estimate is poor. We can try to adress this problem by choosing a *flexible* model that can fit many different possile functional forms of f. But in general, fitting a more flexible model requires estimating a greater number of parameters, and these more complex models can lead to *overfitting* the data, meaning they follow the errors/noise too closely. + +### Nonparametric methods +These methods don't make explicit assumptions about the functional form of f. Instead, they seek an estimate of f that gets as close as possible to the datapoints without being too rough or wiggly. +These approaches have the potential to acurately fit a wider range of possible shapes of f. The major disadvantage is that since they don't reduce the problem to a small number of parameters, they need far more observations to train on. +This method tries to produce an estimate for f that is as close as possible to the data that's as smooth as possible. (Look into thin plane spline) In order to fit a thin-plate spline, we must select a level of smoothness. In general, the lower the level of smoothness (the rougher the tps), the higher the chance of overfitting. We'll discuss choosing the correct ammount of smoothness in later chapters. + + +## 2.1.3 Tradeoff between prediction accuracy and model interpretability + +Of the multitude of methods we'll examine, some are less flexible or more restrictive, in the sense that they can produce a relatively small range of shapes to estimate f. For example, linear regression is a rel. inflexible approach, because it only generates linear functions. +![](./pics/ch2-1.png) + +Why would we ever choose a more restrictive method, then? +If we're interested in inference, we want a more interpretable model. very flexible approaches, can lead to such complicated estimates of f that it is difficult to understand how any individual predictor is associated with the response. + +This doesn't mean that when we only want to predict,that we should choose the most flexible model. This will not always yield the most accurate prediction, because the potential of overfitting is larger. + +### 2.1.4 Supervised vs unsupervised learning +We can also divide the statistical learning problems like so. Thus far, we've only looked at examples in the supervised learning domain. Many classical statisitcal learning methods such as linear regression, logistic regression, GAMs, boosting and support vector machines fall into the supervised category, and the majority of this book falls into this category. +Supervised mean that for every $x_i$, we have a response $y_i$. In unsupervised, we have xi but no associated yi. We lack a response variable that can supervise our analysis. +What statistical analysis is possible, then? We can seek to undersand the relationship between variables or between observations. One statistical learning tool we can use is cluster analysis or clustering, where the goal is to say wether observations fall into relatively distinct groups. For example, a marketing segmentation study where we observe multiple variables for potential customers, such as income, location and shopping habbits. We might believe we have groups such as big spenders and low spenders. We could try to cluser the customers based on the available vars into these groups. + +This might be easy with a visual inspection if we have 2 vars, but is practically impossible when he have more than 3 vars, which we often do. + +Sometimes, the question of wether we're using a supervised or unsupervised method is less clearcut. We may have n observations and m < n observations. This arises when the response is more difficult/expensive to collect compared to the inputs. We refer to these kind of problems as semi-supervised learning problems, and these are beyond the scope of this book. + +### 2.1.5 Regression vs classification problems + +Vars can be divided in quantitative or qualitative(categorical) +We tend to refer to problems with a quantitative response as regression problems, while those involving qualitative responses as classification problems. The distinction isn't always distinct. logistic regression is often used with qualitative binary response. But since it estimates class probabilitites, it can be thought of as a regression method as well. + +We tend to select the method on the basis of wether the problem is quantitative or qualitative, we might use linear regression when quantitative and logistic regression when qualitative. However, wether the features are qualitative or quantitative is less important. Most methods discussed in this book can be used regardless of predictor type, provided that we properly *code* the qualitative predictors before the analysis. + +## 2.2 Assessing model accuracy +Different approaches produce different results, and some approaches will be more appropriate and accurate for a given problem. +We will discuss some of the most important concepts that arise in selecting a method for a specific data set. We'll explain how these can be applied later on. + + +### 2.2.1 Measuring the quality of fit +In order to measure the performance of a learnign method on a data set, we need a way to measure how well the predictions match the observed data. When using regression, the most used measure is *mean squared error* MSE. It's the summation of the squared difference between predicted response and actual response, divided by the number of rpedictions. +We typically split all the available data in a training set, and a set to get the accuracy from. + +A fundamental property of stat. learning methods is that as model flexibility increses, training MSE decreases, but test MSE may not. When a given method yields a small training MSE but large test MSE, we are overfitting the data. This happens when the method is working too hard to find patterns in the training data and may pick up patterns caused by random chance. when we overfit, the test MSE will be very large because the supposed pattern that the method found simply doesn't exist in the test data. We should note that test MSE will always be larger than training MSE. **Overfitting specifically refers to cases where a less flexible bodel would have yielded a smaller test MSE** + +In practice, its usually easy to compute training MSE, but test MSE may be harder because there's no test data available. +As we can see in the examples, the flexibility level corresponding with minimal test MSE can vary considerbly among data sets. We;ll discuss a number of appoaches that can be used to estimate the minimum point. An important method is cross validation. + +## 2.2.2 The bias variance tradeoff + +It can be shown that the expected test MSE can be decomposed in the sum of the variance and squared bias of expected f and the variance of error term e +$$ +E(y_0- \hat{f}(x_0))^2 = Var(\hat{f}) + (bias(\hat{{f}}))^2 + Var(\epsilon) +$$ + +This equation tells us that in order to minimize the expected error, we need a method that both archieves a low variance as a low bias. +**Variance** refers to the amount by which f would change if we +estimated it using a different training data set. In general, more flexible statistical methods have higher variance. +On the other hand, **bias** refers to the error that is introduced by approximating a reallife problem, which may be extremely complicated, by a much simpler model. Generally, more flexible methods result in less bias. As a general rule, as we use more flexible methods, the variance will increase and the bias will decrease. + +`The relative rate of change of these two quantities determines whether the test MSE increases or decreases. As we increase the flexibility of a class of methods, the bias tends to initially decrease faster than the variance increases Consequently, the expected test MSE declines. However, at some point increasing flexibility has little impact on the bias but starts to significantly increase the variance. When this happens the test MSE increases. +The challenge lies in finding a method for which both the variance and the squared bias are low. This trade-off is one of the most important recurring themes in this book. + +## 2.2.3 The classification setting +So far, our discussion of model accuracy has been focused on regression, but many of the concepts also transfer over to the classification setting wih only some minimal modification due to the fact that y is no longer numerical. + +We now use error rate, the average of times where expected y is not y. + +### the Bayes classifier +It is possible to show that the test error rate given in (2.9) is minimized, on average, by a very simple classifier that assigns each observation to the most likely class, given its predictor values. In other words, we should simply assign a test observation with predictor vector x0 to the class j for which the probability conditional that Y = j given the observed predictor vector x0 is the largest. +$$ + P(Y=j| X=x_0) +$$ + This very simple classifier is called the Bayes classifier. +In a 2class/binary problem, the Bayes classifier corresponds to class1 if the probability P(Y=1| X=x0) > 0.5, and to the other if otherwise. + +The Bayes classifier produces the lowest possible test error rate, called the *Bayes error rate*. Since the Bayes classifier will always choose the class for which the probability is the largest, the error rate at X = x0 will be 1−maxj P(Y=j| X=x0). +In general, the Bayes error rate is given by +$$ +1 - E( max j P(Y=j| X=x0) ) +$$ +where the expectation averages the probability over all possible values of X. + +## K nearest neighbours +In theory we would always like to predict qualitative responses using the Bayes classifier. But for real data, we do not know the conditional distribution of Y given X, and so computing the Bayes classifier is impossible. Many approaches attempt to estimate the conditional distribution of Y given X, and then classify a given observation to the class with highest estimated probability. One such method is the K-nearest neighbors (KNN) classifier. + +Given a number K and x0, it first identifies the K training points closest to x0 (repr. by $\mathcal{N}_0$.) It then estimates the conditional probability for class j as the fraction of points in N0 whose response values equal j. Finally, KNN applies Bayes rule and classifies the test observation x0 to the class with the largest probability. +So, for example, if i have xi and k=9, and 7 out of the 9 neighbours are B and 2 are A, we'll get a 7/9th probability that xi is B. + + +The choice of K has a drastic effect on the KNN classifier obtained. When K is low, the decision boundary is overly flexible and finds patterns in the data that don’t correspond to the Bayes decision boundary. This corresponds to a classifier that has low bias but +very high variance. As K grows, the method becomes less flexible and +produces a decision boundary that is close to linear. This corresponds to a low-variance but high-bias classifier. Just as in regression, there is a similar disparity between training error rate and test error rate. + + +Excercises: +For each of parts (a) through (d), indicate whether we would generally +expect the performance of a flexible statistical learning method to be +better or worse than an inflexible method. Justify your answer. +## I. The sample size n is extremely large, and the number of predictors p is small. + +**I expect the variance(the variance i learned at school) between datasets to be low since it's a huge dataset, since there are many data points, so what we could try to do is select a method that decreases the bias. Since bias tends to decrease faster than variance increases as flexibility increases, I'd try to go with a more flexible method** + +2. The number of predictors p is extremely large, and the number +of observations n is small. +**Small number of observations already points towards using a less flexible method, since these generally need less datapoints. So I'd go towards that direction. And since the previous question is essentially the opposite, and i selected the more flexible method, i guess this would take the less flexible method** + +3. The relationship between the predictors and response is highly +non-linear. + +**Now, we can say that if we chose an inflexible one, we'd get more bias, because we're trying to greatly simplify the model. I would go towards a more flexible method. At least, not a method that can only handle y being linear** + + +4. The variance of the error terms, i.e. σ 2 = Var(), is extremely +high. + +**I would try a method that tried to reduce the variance, so this would point me towards a method that's less flexible** + +## Explain whether each scenario is a classification or regression problem, and indicate whether we are most interested in inference or prediction. Finally, provide n and p. + +We collect a set of data on the top 500 firms in the US. For each firm we record profit, number of employees, industry and the CEO salary. We are interested in understanding which factors affect CEO salary. +**n=500 and p = 4. This looks more like an inference problem than a prediction problem, since you're interested in the relationship between predictors and response. I'd also say that it looks more like a classification problem, in the sense that we'd be interested if the salary goes up/down as x1, x2, etc increases** + +We are considering launching a new product and wish to know +whether it will be a success or a failure. We collect data on 20 +similar products that were previously launched. For each prod- +uct we have recorded whether it was a success or failure, price +charged for the product, marketing budget, competition price, +and ten other variables. + +**This is definitely a classification problem, and we're more interested in prediciton than inference. We have n=20 and p = 14** + +We are interested in predicting the % change in the USD/Euro +exchange rate in relation to the weekly changes in the world +stock markets. Hence we collect weekly data for all of 2012. For +each week we record the % change in the USD/Euro, the % +change in the US market, the % change in the British market, +and the % change in the German market. + +**Prediction over inference, and regression. p=4 and n=52 * 8** + +![](./pics/ch2-2.png) + + Explain why each of the five curves has the shape displayed in +part (a). + +1. Bias. This is the error that occurs by the discripancy between the model and the real world problem. As flexibility increases, this allows us to create a model that's more similar to the real world problem, and thus bias decreases. +2. Variance. as flexibility increases, we're fitting the data more closely, and may get patterns caused by random chance. This means that when we use the model on another data set, which probably won't have those patterns, we will get a higher variance. +3. this is the addition of the above 2. +4. this is loosely linked to 3. +5. This is the irreducable error, neither increasing or decreasing the error should have an effect. + + +Describe three real-life applications in which classification might +be useful. Describe the response, as well as the predictors. Is the +goal of each application inference or prediction? Explain your +answer. + +**We could try predict wether the stock of a company goes up or down. It's primarily prediction, and the responses would be up/down. The predictors would be competitors and past stock history. +We could try to see wether some disseases increase the likelyhood of havind diabetes. This would be an inference problem, with predictors being having various other disseases, and response being yes/no. We could try to look at age, sickness, activity level, stuff like that and mortality rate of corona virus patients. This would be an inference problem, and the response whould be yes/no death.** + +Do the same, but with regression. +**Stock price, with predictors being competitors, downstream suppliers, past stock prices. Test score, with predictors like past test scores, socioeconomic standing, hours spent studying, classes missed. Value of some art thing, predictors being artist, genre, date, twitter followers of artist** + +Describe three real-life applications in which cluster analysis +might be useful. + + +**party alliance, with predictors being location, income, age, gender. Loan riskiness, with income, occupation, age. The last problem mentioned in classifiing problems** + +What are the advantages and disadvantages of a very flexible (versus +a less flexible) approach for regression or classification? Under what +circumstances might a more flexible approach be preferred to a less +flexible approach? When might a less flexible approach be preferred + +**A more flexible approach decreases the bias and allows us to model the problem closer to the real world. We prefer a more flexible approach if we know the problem isn't linear, if we have a lot of datapoints, if we're looking for prediction rather than inference. We might want the less flexible methods if we dont have a lot of data, if we want inference, if we know the problem is linear, if we have less computing power.** + +Describe the differences between a parametric and a non-parametric +statistical learning approach. What are the advantages of a para- +metric approach to regression or classification (as opposed to a non- +parametric approach)? What are its disadvantages? + +**Parametric needs less datapoints to be trained, needs less computing power, is less flexible, is linear. Advantages include needing less datapoints and being more interpretable. Disadvantages include having more bias because of the linearity.** + +![](./pics/ch2-3.png) +k=1: green. +K=3 : 2/3 red +I have no idea + diff --git a/ISLR/notebooks/ch2-8.ipynb b/ISLR/notebooks/ch2-8.ipynb new file mode 100644 index 0000000..43c8cdf --- /dev/null +++ b/ISLR/notebooks/ch2-8.ipynb @@ -0,0 +1,594 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "from matplotlib import pyplot as plt\n", + "import seaborn as sns\n", + "sns.set(style=\"whitegrid\")\n", + "tips = sns.load_dataset(\"tips\")" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": "Index(['Private', 'Apps', 'Accept', 'Enroll', 'Top10perc', 'Top25perc',\n 'F.Undergrad', 'P.Undergrad', 'Outstate', 'Room.Board', 'Books',\n 'Personal', 'PhD', 'Terminal', 'S.F.Ratio', 'perc.alumni', 'Expend',\n 'Grad.Rate'],\n dtype='object')" + }, + "metadata": {}, + "execution_count": 2 + } + ], + "source": [ + "college = pd.read_csv(\"./../../datasets/College.csv\")\n", + "college.set_index(\"Unnamed: 0\", inplace=True)\n", + "college.columns" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": " Apps Accept Enroll Top10perc Top25perc \\\ncount 777.000000 777.000000 777.000000 777.000000 777.000000 \nmean 3001.638353 2018.804376 779.972973 27.558559 55.796654 \nstd 3870.201484 2451.113971 929.176190 17.640364 19.804778 \nmin 81.000000 72.000000 35.000000 1.000000 9.000000 \n25% 776.000000 604.000000 242.000000 15.000000 41.000000 \n50% 1558.000000 1110.000000 434.000000 23.000000 54.000000 \n75% 3624.000000 2424.000000 902.000000 35.000000 69.000000 \nmax 48094.000000 26330.000000 6392.000000 96.000000 100.000000 \n\n F.Undergrad P.Undergrad Outstate Room.Board Books \\\ncount 777.000000 777.000000 777.000000 777.000000 777.000000 \nmean 3699.907336 855.298584 10440.669241 4357.526384 549.380952 \nstd 4850.420531 1522.431887 4023.016484 1096.696416 165.105360 \nmin 139.000000 1.000000 2340.000000 1780.000000 96.000000 \n25% 992.000000 95.000000 7320.000000 3597.000000 470.000000 \n50% 1707.000000 353.000000 9990.000000 4200.000000 500.000000 \n75% 4005.000000 967.000000 12925.000000 5050.000000 600.000000 \nmax 31643.000000 21836.000000 21700.000000 8124.000000 2340.000000 \n\n Personal PhD Terminal S.F.Ratio perc.alumni \\\ncount 777.000000 777.000000 777.000000 777.000000 777.000000 \nmean 1340.642214 72.660232 79.702703 14.089704 22.743887 \nstd 677.071454 16.328155 14.722359 3.958349 12.391801 \nmin 250.000000 8.000000 24.000000 2.500000 0.000000 \n25% 850.000000 62.000000 71.000000 11.500000 13.000000 \n50% 1200.000000 75.000000 82.000000 13.600000 21.000000 \n75% 1700.000000 85.000000 92.000000 16.500000 31.000000 \nmax 6800.000000 103.000000 100.000000 39.800000 64.000000 \n\n Expend Grad.Rate \ncount 777.000000 777.00000 \nmean 9660.171171 65.46332 \nstd 5221.768440 17.17771 \nmin 3186.000000 10.00000 \n25% 6751.000000 53.00000 \n50% 8377.000000 65.00000 \n75% 10830.000000 78.00000 \nmax 56233.000000 118.00000 ", + "text/html": "
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PrivateAppsAcceptEnrollTop10percTop25percF.UndergradP.UndergradOutstateRoom.BoardBooksPersonalPhDTerminalS.F.Ratioperc.alumniExpendGrad.Rate
Unnamed: 0
Abilene Christian UniversityYes1660123272123522885537744033004502200707818.112704160
Adelphi UniversityYes218619245121629268312271228064507501500293012.2161052756
Adrian CollegeYes1428109733622501036991125037504001165536612.930873554
Agnes Scott CollegeYes41734913760895106312960545045087592977.7371901659
Alaska Pacific UniversityYes193146551644249869756041208001500767211.921092215
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" + ], + "text/plain": [ + " Private Apps Accept Enroll Top10perc \\\n", + "Unnamed: 0 \n", + "Abilene Christian University Yes 1660 1232 721 23 \n", + "Adelphi University Yes 2186 1924 512 16 \n", + "Adrian College Yes 1428 1097 336 22 \n", + "Agnes Scott College Yes 417 349 137 60 \n", + "Alaska Pacific University Yes 193 146 55 16 \n", + "\n", + " Top25perc F.Undergrad P.Undergrad Outstate \\\n", + "Unnamed: 0 \n", + "Abilene Christian University 52 2885 537 7440 \n", + "Adelphi University 29 2683 1227 12280 \n", + "Adrian College 50 1036 99 11250 \n", + "Agnes Scott College 89 510 63 12960 \n", + "Alaska Pacific University 44 249 869 7560 \n", + "\n", + " Room.Board Books Personal PhD Terminal \\\n", + "Unnamed: 0 \n", + "Abilene Christian University 3300 450 2200 70 78 \n", + "Adelphi University 6450 750 1500 29 30 \n", + "Adrian College 3750 400 1165 53 66 \n", + "Agnes Scott College 5450 450 875 92 97 \n", + "Alaska Pacific University 4120 800 1500 76 72 \n", + "\n", + " S.F.Ratio perc.alumni Expend Grad.Rate \n", + "Unnamed: 0 \n", + "Abilene Christian University 18.1 12 7041 60 \n", + "Adelphi University 12.2 16 10527 56 \n", + "Adrian College 12.9 30 8735 54 \n", + "Agnes Scott College 7.7 37 19016 59 \n", + "Alaska Pacific University 11.9 2 10922 15 " + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "college.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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JKaQxb775VnWvRCEuR2RkJOUecFTKHU1dqHHQTJkyhdOnT9O9e3dKS0vp2rUrOTk5PProo1rWJ+qY2+3m73//OwaTDWuTqy75OKqq4nNX4HOdobLo0GXNxKwoCpbYFBwOB3PmzLnk4whxVkREBA63t7rpTO5otFXjprOwsDBmz55NQUEB2dnZxMfH06RJ3UxJIurOp59+yo8//oi9WRqK0XLJx3EXH0J1V01e6Dq5A1CxRLW95OMZbZGYY5JYu3Yt/fr1o3fv3pd8LCEaNWqEy+PjzE93NNIZQFs1vqO5/vrrAYiJiaFz587VIXPDDTdoU5moc/v372f+/PmYIlphCk+4+Bt+g6c05zdfXwpL444YbVG89o9/yABccVnCw8MBKKzwAlUfpIV2ahw0x44d+9U2VVU5ceKEXwsS+nA6ncyc+TcUkx1bbLfLP6Dq+e3Xl0BRjFjje1FWWsasWbNkYTRxyc52YipxebHbbDLXmcYu2nT2+OOPA1Vt92e/Pis7O5s2bdpoU5moU//+9785eTIXe4sBl9VkpjWjLRJLk85s3bqVL7/8ksGDB+tdkmiAbD/NbVbu9mGxyDxnWrto0Px86o9fTgPSrVs3GQwZALZt28aKFSswR3fAFBqrdzkXZY5uj9eRy7/mzCE5Ofmcue2EqImzdzAeHxjNcjejtYsGzQMPPABAly5dqqfwF4GjuLiYv7/6KkZb1GX1MqtLiqJgje9FxdEVzJz5N156aYY0fYha8XiqmnLNRnB5L79ZV/y2Gvc6S01NpbKykiNHjlBUVHRO+3ifPn00KU5oS1VVXnvtNcrKHNhbDUYxNJyLtcEcgiU2hYMHNzFv3jxuueUWvUsSDYjD4QAgwmokr7gcVVVl1gkN1ThoduzYwR//+EcqKyspKysjLCwMh8NBXFwcq1at0rJGoZGVK1eyfft2rLFdMVob3jgCc6MWeEqzmTt3Lt27d6ddu3Z6lyQaiPz8fADiw8zszXdRUlIigzY1VONeZ88//zx3330327ZtIzQ0lG3btnHfffcxYcIELesTGsnNzWXOm29iCo3FHNVwL9C2uO4oJhszZ/6tei14IS7mxx9/JMpuJj6s6rP2+XrVCv+pcdAcPXqU22+//Zxtf/jDH3j33Xf9XZPQmNfr5eWXX8HjUbHG92zQTQaK0YIlrhe5uTm89957epcjGgBVVfkuK4vEMAOJYWYUYO/evXqXFdBqHDTh4eGUlVWN9G7SpAmHDh3izJkzlJeXa1ac0MaiRYvYt+97LLHdMJhD9S7nsp29K1u2bBm7du3SuxxRzx05coTCoiKuiLRgNxuIDzezffs2vcsKaDUOmkGDBrF27VoAxo4dy+23384NN9zAkCFDNCtO+N/Ro0f54IMPMYU3w9Sopd7l+I21aWeM1ka88ve/Vz/oFeJ81q1bh0GBDtFV42c6xlg5ePDQOQsmCv+qcWeA//u//6v+etKkSXTp0gWHw0FaWpomhQn/c7vdvPzyy2AwYY1LadBNZr+kGExY43tReOwr5syZw0MPPaR3SaIeqqys5MuVK2kXbSXUUvU5u3NTG5nHHGRkZHDnnXfqXGFgqvEdzTPPPHPO65SUFPr3789zzz3n96KENubNm8eRI0cwx6ZgMAXeaGijPQZLdBKZmZls3bpV73JEPbR69WrOlJbSM95eva2R1UiHGAsrli+XRwEaqXHQ/Oc//znv9iVLlvitGKGdQ4cOMW/ePEwRrTCHN9O7HM1YmnSqnnhT1q4RP+f1evlswXziw81cEXnuNEt9m4VSXlHBF198oVN1ge2iTWcLFiwAqv6Rzn591vHjx6XveQPgdrt55ZVXUIw2/0yYWY9VTbzZk9KjXzJnzhxZL0lUW7t2Lbkn8xiXFPGrZuPEcDNtoqz857PPGDZsWI1XDhY1c9GgWbx4MVB1sTr7NVRNA9K4cWNefPFF7aoTfjFv3jy/rDHTUBhtUZhjOrJ27VrS0tLo2bOn3iUJnXk8Hj7+6CPiw8x0iLGe93uubRnKW7sKWbZsGTfffHMdVxjYLho0H3zwAQCvvPKKPGBtgI4dO1a1xkyjlpe9xkxDYmmchLfsBLNmzeaNN5LlE2qQW7VqFXmnTjGhU+QFO8E0CzfTLtrKf/7zGcOHDyc0tOF3/a8vavyMZuLEidXdRr1eL5999hmLFi3C5/NpVpy4PD6fr2rdFsWENbar3uXUKUUxYo3rQVFRYfWHJRGc3G43n86dS2K4mbZRv31HP6BlKA5HuTx79rMaB83kyZOrp2l4+eWXefvtt3nnnXd44YUXNCtOXJ61a9eyb98+LE26BGQvs4sx2mMwR7Xh888/5+jRo3qXI3SSmZnJ6fx8rm0RetEu/fFhZtrHWFm8aJH0QPOjWk1Bk5SUBMDSpUt58803ee+996SXRj3ldDp5+513MNqjMUVcoXc5urE2vgrFaOHNN9/UuxShg7M9zRLCzbS5yN3MWf2bh+IoL+fzzz/XuLrgUeOgMRgMuN1u9u/fT3h4OAkJCTRq1EhGYddTy5cvp7ioCEvTrgE1MLO2FJMVc0xH9uzZw7fffqt3OaKObd68mdyTefRrFlLjv4OEcDOtoywsWbyYyspKjSsMDjUOmtTUVP73f/+X6dOnM2zYMKBqbEZsbP1fkTHYuFwuFnz2GabQWEwhTfQuR3fmyNYYzXY++eQTvUsRdUhVVf7zn8+Itpsu2NPsQq5JDKG4pKR62i1xeWocNM899xzXXnstN954I/feey8ARUVFPPjgg5oVJy7N5s2bOVNSgjkmSbcaVK8bm83GqFGjsNlsqF63brUoBhPGyHZ8++23HD9+XLc6RN3av38/Bw8eoneCHUMt7+qvjLQQG2Zm0aKF5yzyKC5NjYPmgw8+YNy4cYwdO7Z62dxevXpx6tQpzYoTl2blypUYrWEYQ/S721R9bgYPHsw999zDoEGDUH36BQ2AOfIKUBRZpC+ILF26FJvJQJfY83eE2ZVXwa68ivPuUxSFXvF2fvzxOFlZWVqWGRRqHDSzZ88+7/bXX3/db8WIy+dwOMjKysIY1kLXZzOKwczKlSuZM2cOX375JYrBrFstAAaTDWNILFu2yBxowaC4uJiNGzfSpakNq/H8l7mdeRXsvEDQAFzVxIbdbGT58uValRk0Ljpgc/PmzUDVmIwtW7accxt54sQJGdRUz3z33XeoqooxVN9nZ4rRjLO8mKVLlwJgDAnXtR6oWrcmO3s3hYWFREdH612O0FBmZiZer5eUn02eWVtmo0KXJlY2bdpESUkJERENb7nz+uKiQXN2eQCXy8Wf//zn6u2KotCkSROefPJJ7aoTtXZ2rJPRHqNzJfWPwVb1Ozl27JgETQBTVZWVGRm0aGShSUiNV0I5r25xdrbklLN69Wquv/56P1UYfC76r5CZmQnA448/zowZMzQvSFye06dPYzTbUAyX9wcWiAzmqmlo5LliYDtw4ADZOTmMatvoso/VNNREYriFVau+kqC5DDV+RiMh0zA4HA7dn4fUV2cnFJUR34FtzZo1mIwKHRvXrkvzhXRuYuXo0WPVrQWi9mr8sbd///4XfLi8Zs0af9UjLlNVj0DpjnlePz1fPNtrUgQej8fDurVraRdlwWaq8efo35TcxEbGkVJWr17NHXfc4ZdjBpsaB81LL710zuvTp0/z/vvvVw/e/C0vvvgiGRkZZGdns3TpUtq1awfAkSNHeOKJJyguLiYyMpIXX3yRVq1aabYvGISGhuLzVKKqalDPCHA+qtcFQFhYmM6VCK18/fXXnCktpUtz/62TFWox0CbKyurMTG677Tb5oHIJahz5PXv2POe/4cOHM2vWrAuuvPlz1113HR999BGJiYnnbJ82bRoTJkwgIyODCRMmMHXqVE33BYO4uDh83srqi6r4L5+7DKj6HYnAtGL5csKtphrPa1ZTV8faKCwqYseOHX49brC4rHtLi8XCiRMnLvp9KSkpxMfHn7OtoKCAvXv3MmLECABGjBjB3r17KSws1GRfsGjZsiUAPmeRzpXUP96ffifNmzfXuRKhhaNHj7Lj66/pFmvFaPDv3Xz7GCsRNhOfLVggMwVcgho3nb366qvnvHY6ndUrGF6K3NxcYmNjq29DjUYjTZs2JTc3F1VV/b4vWLqzdujQAYPBiLf8FKaw+Iu/IYh4y0/RokULwsP1H9Mj/EtVVd57912sJgO9Evy/yJ1RUeiXaOfzffvYunUrvXv39vs5AlmNg+bkyZPnvLbb7dx5552MHj3a70XVBw152olmzRLJzsuBpl30LqXeUL2V+MpPk3BVT77++mu9yxF+tmvXLnZ8/TVDrgwjxOyfTgC/1DXOzvaTTl577VUqKytlsHot1ChoPB4PKSkpbNq0qfohe/fu3Rk9ejRm86V1pY2PjycvLw+v14vRaMTr9XLq1Cni4+NRVdXv+2orOTkZq9U/3SPrWm5uLv/617/wOosx2vz3ULQh85Rmo6o+xo4dS4cOHfQuR/jR/v37+XzZMlpGWDS5mznLZFC4vm04b+8p4ovPP+fpZ5655OtfIHK5XBf8gH7R6C8tLWX8+PH87W9/w2w207FjR8xmMy+//DLjx4+ntLT0koqKiYkhKSmJZcuWAbBs2TKSkpKIjo7WZF8w6du3L0ajEXfxD3qXUm94Sg4TGxdH+/bt9S5F+NHevXuZ+pe/EGaGmztE1HqW5tpKCDczqm043+3dy9NPPYXT6dT0fIFCUS/yZGv69Onk5OTw97//nZCQ/35acDgcPPTQQyQkJDB9+vTfPMkzzzzDypUryc/PJyoqisjISD7//HMOHz7ME088wZkzZ2jUqBEvvvgiV155JYAm+2ribCo35DsagJkzZ7J+wyZCWo9CMdb9p67yY6vwlp+ufm0MaUJIy+vqvA4Ab0Uh5UdXcvfddwdsU28wyszMZPasWYSb4bZOEUTaatft+J09VZ2E7uxc+w+i35ysYOmhM7S+sjVPTJki63Lx29fOiwZNv379mDdvHgkJCb/ad+LECcaPH8+GDRv8W7GOAiVoDh48yMMPP4ylyVVYG3eq8/PXp6CpOLEes6eIt9/+t4yhCQAOh4O33nqLr776ipYRFm7q0IgwS+3HtlxO0ADsK3Cy6EAZRouV+x94gH79+gX12LXfunZetOmsrKzsgmkdFxdHWVmZf6oUftW2bVt69OiBp2g/qjd4l6P1VhTgKc1mzJjrJWQaOFVV2bhxI/fdey+rVn1Fv+Yh3H5V5CWFjD90iLHxh6sjiTC6mTFjBk8//ZTMo3cBFw2a5s2bs2XLlvPu27x5s4xJqMduu+02VK8b1+k9epeiC1VVceV9Q3ijRtJk1sAdPHiQP0+ZwgsvvIDV4+DuLtEMbBWOUec7iGi7iUldohh8RRi7vvmGeydP5r333sPhcOhaV31z0aC58847+dOf/kRGRgY+nw+oWptmxYoVTJkyReb+qceuuOIKhg8fjrvoEN6KOh60qph++3UdcBf/gLeigLsnTTrn+aJoOI4cOcLzzz/Pww8/zJGD+xjWOpx7ukSRGF5/ensZFYVrmoVyf7dokqJNLFiwgHvuvpv58+fLBK4/uehf/w033EBxcTFPPPEEjzzyCJGRkRQXF2M2m7n//vsZO3ZsXdQpLtGtt97Kho0bKT25FXvLQXW2fIApPAGvI/ec13XJV1mG+/QuOnXqxIABA+r03OLy7du3jwULFrB161asJgNpzUO5plmI3ybK1EKkzcgN7SPonRhC5tEy3n//fT77bAGjR1/PsGHDgnrhtIt2BjirrKyMnTt3UlRURFRUFF27dg3INu9A6Qzwczt37mTq1KmYo9pii+teJ+dUVRXH4c/B58bS5CrMka3r7EGpqvqo+HE1Zl8Zs2fPomnTpnVyXnF5vF4vmzdvZtHChew/cAC72UiveBu9EkOwaxAwl9sZ4GKyS92sO+5gf4ELs9lMeno6o0ePDtjHDb917azxx9uwsDBSU1P9XpzQXteuXRk9ejSLFy/GaI/BHNFK83MqioLBbAfsWKLaaH6+n3Pl7cJbfpqHHn1UQqYBKCwsJCMjgxUrllNYWES03cSw1uFcHWvHYmy4vbgSw83c0jGS0+UetmSXs+qrlWRkZND5qqR5omAAAB5tSURBVKsYNnw4vXr1wmQKjgUKg+OnFNxxxx0cPHiI7/ftwGBphNEemINY3SVHcBcdYOTIkfTv31/vcsQFeL1edu7cycqVK9m2dSten4/WUVYGd4ygXbRV84GXdalJiImRbRuR3jKMb/Iq+Prg97zwwrdERUYycNAgBg0adEmzlzQkEjRBwmQy8cQTf+Khhx6mOHs9thbXYbAEVtOnx5GHK3c7ycnJ3HXXXXqXI84jJyeHzMxMvvrySwoKCwmxGOkZbyMl3k6MPbAvR6EWA6nNQ+nbLISDhZXsOFnBggXzmT9/PsnJyQwaNIhrrrkGm82md6l+F9j/suIcUVFR/PWv03nsscdxZq/H3jwdxRQYz6G8zmJc2RtJSEzg//7v/4KmSaIhKC0tZcOGDaxatYr9+/ejAK2jLKR3iKB9jBWTn6f0r+8MikL7GCvtY6yUuLzszqtg5+F9vJKVxT//OZu+ffuRnp7OVVddhcFQfzs/1Ib8NQaZli1b8pe/PMnUqVOpOLEOe/NrdZmixp98laW4TqylUaNQnvrrXwOyk0pD43Q62b59O2vWrOHrr7/G6/XSNNTMoCvCuKqJjUZWWaUSIMJqJK1FGP2ah/LjGTd7TjnZuG4NmZmZREdFkda/P/3796d167rrTKMFCZogdNVVV/HEE0/w3HPP4cxej61ZWp11e/Y3n9uB8/ha7FYTzz37rDz815Hb7Wbnzp2sW7eOLVs243JV0shqomeclc5NbcSFmhr0xVJLBkWhVYSFVhEWfnelyv5CF9+eLmfpksUsWrSIhPh40vr3JzU1lRYtWuhdbq3VuHtzsAjE7s0XsnbtWmb+7W+YQmKxNUtFMfj3U2b5sVUAms1x5nOX4zy+GovBy3PPPUubNnXbu01ULSGye/du1q9fz+ZNmyivqMBuNpIUY6FzExstIsz18sG+qqr8Y0c+Lq/KtS3DSImz18sQrHD7+L7AxbennRwtqURVoUXz5qT170+/fv1ITEzUu8RqfuneLAJP//79cbvdvPrqqzizN2BL7Of3sNGKz1OB8/gazIqbp59+RkKmDnk8Hvbs2cOGDRvYvGkTZQ4HNpORDjFmOl0ZyZWRFr8vpexvO3IrKHRWzXTy+aFSUKGHhmvZXCq72UC3ODvd4uyUVnr5Pt/Fd/l5fPjhh3z44Ydc0aoVqWlp9O3b97wTH9cXEjRBbuDAgXg8HmbPno0zexO2ZtegKPU7bHweJ87jazDiYvr0v8oaM3XA6/Xy3XffsX79ejZu2EBpWRlWk4H20RY6tYykdZSlQT3U31/o+tXr+hg0PxduMdIzIYSeCSGUuLzszXeyNz+H999/n/fff58rr7yC/v2vpV+/fvWuCVmCRjB06FC8Xi9vvPEGzuzN2BKvQVHqZ28X1ePCeXwNBm8F0/86nU6d6n4JhGChqiqHDx9m9erVrFu7luKSEsxGA+2jzXRqHkGbaCvmBhQuP+f2qb/5ur6LsBrpkxhKn8RQip1VofPd6Wzeeecd3nnnHTq0b8+1AwbQr1+/ejH1jQSNAGD48OF4PB7eeustnDlbsSX0rndt1qrXjfPEWhRPGdOmT+eqq67Su6SAVFBQQGZmJpmrVnEiOxujQaFtlIWBHaoGUzbk0fqBKNJm5JpmoVzTLJTCCg/f5bvIyv6BN97Yz5tz5pDSowfp6en06NFDt6WnJWhEtdGjR+Nyufjggw9wGcxY47rXm7BRfR6cJ9bhcxXz5JNP0qVLF71LCig+n4/du3fzxRdfsG3bNnw+Hy0iLIxoE06nxjbs5vp5hyvOFW03kdrcRGrzUE6Wudl9ysm3u3awdetWIiMaMXjIUIYMGVLnTWsSNOIcN998M+Xl5Xz22WcoJhvWJsl6l4Sq+nDmbMZTkc/jjz1Gjx499C4pYHi9XtavX8/cuZ+QnZ1DiMVInwQb3ePsRAf4SP1AFxdmJi6sauzSoaJKduRWMH/ePObPn0+/fn255ZYJdTbBp/yfJH5l4sSJFBUVkZmZiWKyY4lqrVstqqriOvkNntJsJk+eLBO7+tGOHTv491tvcSI7m9hQMze0b0THxrYG9VBfXJxBUWgXbaVdtJVip5ftueVs3bSJDRs2kpaWxqRJk4iKitK0Bgka8SuKovDggw9SXFzMzp1fY7CEYQo9/3LeWnMXHcBdfIixY8cyYsQIXWoING63m3fffZclS5bQOMTMTR0iSGocWBNZivOLtBkZdEU41zQLZdMJBxs3rGfXzp08/MgjdOvWTbPzSsOrOC+TycTjjz9OQkICrpxN+CrL6rwGT9lJXHm76NWrF7fffnudnz9QzZ49myVLltArwc7krlF0amKTkAkyoWYDg66oWq3U6q1g+vTp7N27V7PzSdCICwoNDWXatKlYzUZcOZtQfd46O7fPXY4rdwvNmjfjkUceCZjJBfW2d+9eVq1aRb/mIfyudaMG2z1Z+EdsqIlJnSOJsBqZNesfaDVRjPz1it8UHx/PQw/9EU9FIa5Tu+vknKrqw5WzBZNR5c9TpmC32+vkvMEgLy8PgC5Ng/t36vL4sNlsjBo1CpvNhsvj07sk3VhNBjrEWDiVd0qzc0jQiIvq06cPI0aMwF10AI8jT/PzuQsP4Ck/xf3/7/8F7LK3ejk7IePGEw7NPr02BE6PyuDBg7nnnnsYNGgQTk/w/i5KXF6y8l20aNFCs+EMEjSiRiZOnEhcXDyVJ7eh+tyancfrOkNl/rf06tWLAQMGaHaeYNW6dWvGjRvHrjwnCw+cwRmkn+RtJoWVK1cyZ84cvvzyS2ym4GxC/PFMJe9+W4xXMfPQww9rdh4JGlEjNpuNhx9+CG+lA9fp7zQ5h6qqVObtwG6zcf/999ebwaKBZsKECYwfP55vT7t4Y2cRe/OdQXd3YzUZcDqdLF26FKfTidUUXJfCcrePjB9KeWdPEeawKJ56+mlNWw+C67crLktSUhKDBg3CU3QAr6vE78f3nPkRj+MUd9wxUfN+/cHMYDBw6623MmPGDMJiYpn3fQlv7S7icJEr6AIn2Li8PtYfd/DajgK25FQwaNBg/jFrFh06dND0vDKORtTKxIkT2bBhI5WndmNvnua346o+L+78PVxxxRUMHjzYb8cVF9ahQwdmzZ7N6tWr+ejDD/ggq5BmjSz0a2anXbSMqwkk5W4f23LK2ZrrpMLtpUePFG6/fSKtWrWqk/NL0IhaiYiIYNy4m3n33XfxOPL8NpDTXXQAb6WDSZMmYTTW72UKAonRaGTgwIGkpaWxatUqPlswn7l7T9M01EzfZnaSG9vq/doy4sLOuLxszi7n6zwnlR4fvXr14qabbqrzpTUkaEStjRw5ksWLl3Am/1uMIU0v+1mK6nXjLtxH165dZbJMnVgsFn73u98xePBg1q1bx4L581i4/wSrfyynb4KdrnF2mZqmASlyell/3MHuU05UFFJTU7npppto2bKlLvVI0Ihas1gsjB8/jtdffx2v4ySmsPjLOl5l0QF8Hhe///3v/VShuFRGo5EBAwbQv39/duzYwbxPP+XzAwfYkF1BWjM7V8fa5Q6nHit2ell33MGuPCdGo5EhQ3/HmDFjiIuL07UuCRpxSQYNGsSnn86jpOD7ywoa1efBU3SQbt26065dOz9WKC6HwWCgZ8+e9OjRg507d/LRhx+y9OBBtuY6GXpFKFdGWS9+EFFnKr0qG0842HiiHAwGfjdsGDfddBMxMTF6lwZI0IhLZDabGTv2Bt5880285fkYQxpf0nHcxYfxeZyMG3eznysU/qAoCt26daNr165s2bKFf7/1Ju9nnSa5iY3hrcNlnZp64GhxJYsOlVJc4aFfv77ceeddspTz+aSnp2OxWLBaqz4lPfroo6SmprJr1y6mTp2Ky+UiMTGRl156qTqhL3Wf8J/Bgwfz8Sef4Cr8HntI7afvV1UfnqIDJCUl0bFjRw0qFP6iKAp9+vShe/fufPbZZ3w6dy7HS4u4oV04LSMsepdXa7+c460hzvnmU1Uyj5Wx8Xg5cXGxPP6X/623q87Wm48jr732GosXL2bx4sWkpqbi8/l47LHHmDp1KhkZGaSkpDBz5kyAS94n/MtmszFyxAg8pdl4XWdq/X7PmR/xVjq48cYbNahOaMFisXDLLbfw0syZhEQ15v2sYnbnVehdVq21j7b+5uv6zuX1MXdvCRuOlzNw0CBefe0f9TZkoB4FzS9lZWVhtVpJSUkBYPz48axYseKy9gn/GzFiBCaTCXfh/lq9T1VV3EUHSEhIrP63Eg1H27ZtefnlV+jUKZmFB86wOduhd0m1khJvJ9pmINSsMLxNOCnxDWeSUafHxwdZJRwsquTee+/lf/7nf+r9xLP1JmgeffRRRo4cyfTp0zlz5gy5ubkkJCRU74+Ojsbn81FcXHzJ+4T/RUREkJ6ejufMUXweV43f5y0/jbeikDFjrpclABqosLAwpv/1r1zTpw8ZP5Sx8UTDCRtFUQi3GmkcYqJHfEiDme6owl0VMrkOL1OmTGH48OF6l1Qj9eIZzUcffUR8fDyVlZU8++yzPPXUUwwaNEjXmrKysnQ9f0PSpk0bVq5cibv4ENbGnWr0Hnfhfmw2OxEREXz99dcaVyi0dN3AgZScOcOX332HT4XU5qF6lxSQyt0+Psgq5lSFl5tvHofFYmkwfzv1Imji46u6x1osFiZMmMB9993H7bffTk5OTvX3FBYWYjAYiIyMJD4+/pL21UZycnJ15wRxcZs3b2ZP1j7UmA4oym+P7PdVluEpy+aGm2+mT58+dVSh0FL37t155ZWXWbV2HWWVXoZcGS5T2PhRYYWHj/ae4UylypNP/qVeNje7XK4LfkDXvc2ivLyc0tJSoKrd/osvviApKYnk5GScTic7duwAYO7cuQwdOhTgkvcJ7YwaNQqvuwLPmRMX/d7KooMYDAaGDRtWB5WJumA0Gnn44Ue4/vrr2ZpTwQdZxZS46m5F1kC2N9/Jm7uLcSkWnn7mmXoZMhej+x1NQUEBDz74IF6vF5/PR+vWrZk2bRoGg4EZM2Ywbdq0c7opA5e8T2inW7duxMXFk198EHPEhae5UH0evGeO0LdvX+lyHmAMBgOTJk2iRYsW/OuNN3hjZxGDWoVydaxN7m4uQWmll6+OlLH7lJPWra/k8cf/dM7z54ZEUWVe8HOcvf2TprPaW7x4MW+99RYhVwzBaIui/NgqAEJaXlf9PZXFh3HlbueFF16gU6eaPc8RDU9OTg6vvPwy+/bvJy7MzKBWoVwZaalXD93f2VMIwJ2do3Wu5Fwur4+t2eVsOFGBF4WxY8dyyy23YDLpfl/wm37r2lm/KxcNSnp6Ou++9x7uosMY489/e+8tPkzz5i1kgGaAS0hIYMZLL7F+/XreeedtPsgqIDHcTL9mIbSPkSUIzsfx01T+236ayr93797ceeedDfYu5uckaITfhIeHk9qvH2vXbUSNvfpX+73OYjwVhQwdOrZefbIV2lAUhbS0NHr37v3TEgQL+PT7U8SEmOkea+XqWDshQT6Fjaqq5JR52JFbTlZ+JW6vj969ejH2xhs1X4ysLknQCL8aOHAgq1evxlP6604B7pIjGI1G+vfvr0NlQi8/X4Jg06ZNLFu6lJXff0/mMQdJMVa6xtlpFWEOqrucCrePrNNOvjnlJLfUjdVqIX3gIEaPHq3pksp6kaARfpWcnEx0dAwlZ348Z7uqqvhKj9O9e3ciIiJ0qk7oyWg0kpqaSmpqKseOHWPFihWsWvUV335bRITNROcmVro0tdE4JDAvS16fyuHiSnblVbC/sBKvT6Vlixbce+swBgwYQEhIiN4laiYw/0WFbgwGA6mp/ViyZCmKLbq6icxbkY/XXU5qau0n3xSBp2XLlkyePJk77riDrVu38tVXX7Fh1y7WH3eQGG6mcxMbnZrYCLM07KY1VVXJLvOw51QF3+VX4qj0Eh4WxrDhg0lPT6d169ZB0YwsQSP8rk+fPixevBi8lSimqt4n3rJsDAYjPXv21Lk6UZ9YrVbS0tJIS0ujoKCAdevWsTozk+U/HCXjSCmtI610bmqjQ4wVs7HhXJCLnF72nKpgz+lKCsrdmE0mevbqzbXXXkv37t0xm816l1inJGiE33Xo0AF7SAgVrko4GzSOk3Ts1DGgmwfE5YmJiWHMmDGMGTOGY8eOsWbNGlZnZvLZ/kKsJgMdYyxcHWunRSNzvbwLcHl8ZOU72X3KxY8llUBVU/Kt6elcc801hIYG79Q8EjTC74xGI1d36cLmLVsB8HlceJ3FdOs6SufKREPRsmVLJk6cyG233UZWVhaZmZls3LCBnXlFxISY6drUSpdYG+GW357uSGuqqvLjGTc786qaxtxeH80SE7l99HX079+/3i1AphcJGqGJTp06sXnzZlSfD2/FaQAZOyNqzWAw0LlzZzp37sy9997Lhg0b+HLlSr76qddax8ZWeiXYaRZet3c5lV6Vb09XsC3XSV6ZG5vVyoDrBjJo0CDat29fL++49CRBIzTRvn17AFSfG19FIYqi0KZNG52rEg2ZzWZj4MCBDBw4kBMnTrB8+XK+/HIlWbuLSAy3kNrcTvtoq6YX+XK3jy3Z5Ww/WTWoslWrljxwx0jS0tLq/ZowepKgEZpo2fKn+c58HryuYhISE2VKH+E3zZo145577uH3v/89mZmZLFq4kLl784gLM9O/eQgdYvwbOBUeHxtPONiW66TS46N3716MHn09nTp1kruXGpCgEZqw2+2YzWbcPi+Kp4xWLevvMrOi4bLb7QwfPpyhQ4eybt06Pp07l0+/z6FVpIXfXRlGbOjl9e7yqSrfnKwg88dyKtxe+vXrx7hx4//7QUrUiASN0IzFYsFd7sLrKguI+ZpE/WU0GhkwYABpaWlkZGTwwfvv86+dRaQ2DyGtRSjGS7jrKKzwsPBAKcfPVNIxKYk/TJ5M69atNag+8EnQCM1YLBYcDgcq0KRJE73LEUHAaDQybNgw+vXrx5tvvsmaNWv4odjNzUmNatVD7bvTTpYcKsVgtvDQQw8xYMAAaSK7DA172K2o134+rbmsPSPqUqNGjXjkkUd47LHHOOWCt3YXc8rhqdF7N51wMH9fCa1at2XWrNmkp6dLyFwmCRqhmZ8HjcxvJvSQlpbGCy+8iGIN5f3viims+G/YdI210zX23J5im044WHmkjL59+/Lcc8/JOBg/kaARmvl50ISHh+tYiQhmbdq04bnnn0cx2/nwuxKcHh8AV8faufpnQbM331kdMo899hgWi0WvkgOOBI3QTPfu3au/DubpN4T+mjdvzl+mTqXY5WPZodJf7S92ellysJS2bdvwyCOPYDTqO+NAoJGgEZrp06dP9dcyx5nQW1JSEuPHjyfrtJPDRa5z9q08UopqMPH4438Kugkv64IEjdCMzWar/lr+eEV9MHbsWGKbNuGrow5UVQUgu9TN3nwXY2+8kbi4OJ0rDEwSNEIzMhOAqG8sFgs33TyO3DI3R0vcAGzOdmC32xg9erTO1QUuCRqhGXmYKuqjAQMGYLfb2H2qAqfHx76CSq67bqA072pIgkZoRoJG1EcWi4U+fa5hf6GbA4UuPD6VtLQ0vcsKaBI0QjPyXEbUV127dqXC7WVzdjmhIXbatWund0kBTYJGaObn42iEqE+SkpIAyC3z0K5de+nOrDEJGqEZ+eMV9VXTpk2xWquadlu2aqVvMUFAgkZoRoJG1FeKomCzVnW/j4+P17mawCdBI4QISk1+msdMZhbXnjSiCyGC0h//+EeysrK4+uqr9S4l4EnQCCGCUsuWLWWlzDoiTWdCCCE0JUEjhBBCUxI0QgghNBWwQXPkyBHGjRvHkCFDGDduHEePHtW7JCGECEoBGzTTpk1jwoQJZGRkMGHCBKZOnap3SUIIEZQCMmgKCgrYu3cvI0aMAGDEiBHs3buXwsJCnSsLPn/4wx8k5IUIcgHZvTk3N5fY2NjqkelGo5GmTZuSm5tLdHS0ztUFl5EjR+pdghBCZwEZNP6QlZWldwlCCBEQAjJo4uPjycvLw+v1YjQa8Xq9nDp1qlZzGiUnJ8sKkUIIUUMul+uCH9AD8hlNTEwMSUlJLFu2DIBly5aRlJQkzWZCCKGDgLyjAZg+fTpPPPEE//znP2nUqBEvvvii3iUJIURQCtigad26NfPnz9e7DCGECHoB2XQmhBCi/gjYO5pLpaoqAJWVlTpXIoQQDcfZa+bZa+jPSdD8gtvtBuDAgQM6VyKEEA2P2+3GZrOds01Rzxc/Qczn8+FwODCbzSiKonc5QgjRIKiqitvtJjQ0FIPh3KcyEjRCCCE0JZ0BhBBCaEqCRgghhKYkaIQQQmhKgkYIIYSmJGiEEEJoSoJGCCGEpiRohBBCaEqCRlyyKVOm8NJLL52z7Y477uDjjz/WqSIhfi09PZ0RI0bg8/nO2Sazf9QdCRpxyf785z+zfPlydu/eDcDcuXNRFIVbbrlF58qEOFd5eTmLFy/Wu4ygJUEjLll4eDhPP/00U6ZM4ciRI7z++us8++yzKIrCggULuPHGGxkzZgwTJ07k6NGjAOzYsYPrr7+e0aNHM2LECL744gt9fwgRFB544AFmzZr1q8lyjx07xsSJExk5ciRjxoxh3bp1OlUY2GRSTXFZ+vbtS48ePbjxxhuZMmUKCQkJbN26la+++oqPP/4Yi8VCZmYmTz75JB9++CFz5sxh8uTJ/O53v0NVVUpLS/X+EUQQSE5OplOnTnzyySdMnDixevujjz7KzTffzE033cShQ4e49dZbWb58uazG62cSNOKyTZo0ieXLl3PjjTcCkJmZyd69e7npppuAqsn2HA4HAL169eKf//wnR48epW/fvnTu3Fm3ukVw+eMf/8jtt99e/f+pqqp8//33jB07FoA2bdqQlJTErl27SE9P17PUgCNBIy6bwWA4Z6ZrVVW5+eabeeCBB371vZMmTWLgwIFs2rSJ6dOnM2DAAB588MG6LFcEqSuvvJL+/fvzzjvv6F1K0JFnNMLvBgwYwKJFi8jLywPA6/WSlZUFwA8//EDLli255ZZbuO2229izZ4+epYog8+CDD/Lxxx/jcDhQFIWkpCQWLlwIwOHDh9m3bx9XX321zlUGHrmjEX7Xp08fHnjgASZPnozP58Pj8TBs2DCSk5N577332LFjB2azGYvFwtSpU/UuVwSRuLg4Ro8ezdtvvw3AzJkzmTp1Ku+++y4mk4kZM2bI8xkNyHo0QgghNCVNZ0IIITQlQSOEEEJTEjRCCCE0JUEjhBBCUxI0QgghNCVBI0Q9cffdd1eP6RAikEj3ZiE0lJ6eTn5+PkajEbvdTlpaGn/5y18IDQ3V7Jy33XYbo0aNqp4CSAi9yR2NEBp744032LlzJwsXLiQrK4vXX3/9nP2qqp6zVooQgUaCRog6EhsbS2pqKgcPHuS2227jlVdeYfz48XTp0oXjx49z2223MX/+fCorK0lJSTlnYa7CwkI6d+5MQUEBJSUlTJ48md69e9OjRw8mT57MyZMnAXjllVfYsWMHTz31FF27duWpp54CqqZXufPOO+nZsydDhgyR5RlEnZKgEaKO5Obmsm7dOpKSkgBYvHgxTz/9NN988w0JCQnV32exWBg0aBCff/559bbly5fTo0cPYmJi8Pl83HDDDaxevZrVq1djtVqrA+Whhx4iJSWFqVOnsnPnTqZOnUp5eTl33XUXI0aMYNOmTbzyyiv89a9/5dChQ3X7CxBBS4JGCI3df//9pKSkMGHCBHr06MG9994LwJgxY2jbti0mkwmz2XzOe0aOHHlO0CxdupSRI0cCEBUVxZAhQ7Db7YSFhXHfffexffv2C55/zZo1JCYmMnbsWEwmEx07dmTIkCGsWLFCg59WiF+TSTWF0Njs2bO55pprfrU9Pj7+gu/p1asXTqeT3bt3ExMTw759+xg4cCAAFRUVPP/886xfv56SkhIAHA4HXq8Xo9H4q2NlZ2ezZ88eUlJSqrd5vV5GjRp1uT+aEDUiQSOETn6+hs8vGY1Ghg4dyrJly2jcuDHXXnstYWFhALz99tscOXKEefPm0aRJE77//nuuv/56LtSBND4+nh49esg6LEI30nQmRD01cuRIli9fztKlSxkxYkT1dofDgdVqpVGjRhQXFzNr1qxz3te4cWOOHz9e/fraa6/l6NGjLFq0CLfbjdvtZs+ePRw+fLjOfhYR3CRohKinunTpgt1u59SpU6SlpVVvnzhxIi6Xi969ezNu3DhSU1PPed/tt99ORkYGPXr04JlnniEsLIx///vffPHFF6SmptKvXz9mzpxJZWVlXf9IIkjJgE0hhBCakjsaIYQQmpKgEUIIoSkJGiGEEJqSoBFCCKEpCRohhBCakqARQgihKQkaIYQQmpKgEUIIoSkJGiGEEJr6/1eSbT+I8kROAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = sns.violinplot(x=\"Private\", y=\"Outstate\", data=college)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = sns.boxplot(x=\"Private\", y=\"Outstate\", data=college)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "sep =pd.cut(college.Top10perc, pd.interval_range(start=0, end=100, periods=2), labels=[\"Not elite\", \"Elite\"])\n", + "college[\"Elite\"] = sep " + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = sns.violinplot(x=\"Elite\", y=\"Outstate\", data=college)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Index(['Private', 'Apps', 'Accept', 'Enroll', 'Top10perc', 'Top25perc',\n", + "# 'F.Undergrad', 'P.Undergrad', 'Outstate', 'Room.Board', 'Books',\n", + "# 'Personal', 'PhD', 'Terminal', 'S.F.Ratio', 'perc.alumni', 'Expend',\n", + "# 'Grad.Rate'],\n", + "# dtype='object')\n", + "ax = sns.distplot(college.Apps)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Index(['Private', 'Apps', 'Accept', 'Enroll', 'Top10perc', 'Top25perc',\n", + "# 'F.Undergrad', 'P.Undergrad', 'Outstate', 'Room.Board', 'Books',\n", + "# 'Personal', 'PhD', 'Terminal', 'S.F.Ratio', 'perc.alumni', 'Expend',\n", + "# 'Grad.Rate'],\n", + "sns.distplot(college.Accept)\n", + "sns.distplot(college.Enroll)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = sns.distplot(college.Top10perc)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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C5ORkiouLASguLiY5ORmj0ejQLysri+3bt2Oz2bBYLJSXl5OZmTmutiNHjrBmzRpeeOEFbrnlFof3a2xstH+/d+9e9Hq9Q8gIIYSYXE4d8lq/fj0FBQVs2bKFkJAQNm7cCMCKFStYvXo1c+bMIScnh8OHD7NkyRIAVq1aRXx8PIDLbUVFRfT09FBYWGiv5bnnniMpKYm1a9fS0tKCTqcjKCiI3//+93h5TYkjeEIIcU1y6jdwYmIi27dvH7J869at9u8NBgNFRUXDru9q244dO0as6dVXX71KxUIIISab3CkvhBBCExIoQgghNCGBIoQQQhMSKEIIITQhl0Vdg/oVG02WLodl/n5eBAf4uKkiIcT1QALlGtRrVThyutlh2bykKAkUIcSEkkNeQgghNCGBIoQQQhMSKEIIITQhgSKEEEITEihCCCE0IYEihBBCExIoQgghNCGBIoQQQhMSKEIIITQhgSKEEEITTgVKdXU1+fn5ZGZmkp+fT01NzZA+iqJQVFREeno6GRkZDg/kcrVt8+bN3HfffSxdupQHHniAvXv32tu6u7t54oknyMjIICsri/fff9+Vn18IIYRGnJrLa926dSxbtoycnBx27txJYWEh27Ztc+iza9cu6urqKCsro62tjdzcXBYuXEhcXJzLbampqSxfvhx/f39OnDjBQw89xL59+/Dz8+MPf/gDQUFBvPvuu9TU1PD973+fsrIyAgMDJ2SghBBCXN2oeygtLS1UVlaSnZ0NQHZ2NpWVlVgsFod+JSUl5OXlodfrMRqNpKenU1paOq62RYsW4e/vD0BSUhKqqtLW1gbAO++8Q35+PgAzZswgJSWFDz/8UIsxEUII4YJR91DMZjPR0dEYDAZg4BnwUVFRmM1mjEajQ7/Y2Fj7a5PJRENDw7jaLvf2229zww03EBMTA0B9fT3Tp08fdb2rOXbs2JBlFRUVY9rGZDI3mKmtO+uwbHqEN7V1taMuM4UqfFXdNmG1efK4SW1j56l1gdTmqsmobUpMX3/gwAF+97vf8cc//lHT7aakpODr62t/XVFRQVpamqbvoZWKigpMMSYS2g0Oy4OCgki4IWHUZaaYKKKMiRNWmyePm9Q2Np5aF0htrtKqtt7e3mH/EB806iEvk8lEY2MjiqIAAyfRm5qaMJlMQ/rV19fbX5vNZvvehKttAIcOHeLnP/85mzdvZubMmfblsbGxnDt3bsT1rlf1zR3sO3wOVVXdXYoQ4jozaqBERESQnJxMcXExAMXFxSQnJzsc7gLIyspi+/bt2Gw2LBYL5eXlZGZmjqvtyJEjrFmzhhdeeIFbbrllyPu98cYbANTU1HD06FEWLVo0zuGYui509lL6cQ1vfVDF/yn/ki9qLKOvJIQQGnLqkNf69espKChgy5YthISEsHHjRgBWrFjB6tWrmTNnDjk5ORw+fJglS5YAsGrVKuLj4wFcbisqKqKnp4fCwkJ7Lc899xxJSUn8+Mc/pqCggIyMDPR6Pb/61a8ICgrSYkymnNNn2yg/UIdOp+PrX4umvaOXvZ/XEzstiLBg39E3IIQQGnAqUBITEx3uDxm0detW+/cGg4GioqJh13e1bceOHSPWFBAQwAsvvHC1sq8Lqqpy4HgDYcG+ZN95I0EBPkQbA3jm1QOUHajlHxffhEEv968KISae/KaZ4mrMF2i92EvqTdMIuvTM+LBgX+5Ji+d8azcHjje6uUIhxPVCAmWK+/hYA14GPTfFhTksnzk9lOQZRj472cSFzj43VSeEuJ5IoExh1n6Fz040cVNcKD7ehiHtabOjgIFzLEIIMdEkUKaw02fb6bUqJN9oHLY9NMiXqPAATn8lgSKEmHgSKFPYFzUWosL9MUWMPH/ZzfFhnG/rptHSOYmVCSGuRxIoU1TbxV7MzZ3cnmJCp9ON2C8xLhSAA5Vycl4IMbEkUKaoL2os6HSw4GvRV+0XHOCDKSKQTyVQhBATTAJlijrbdBFTRCChQaPfuHhTfBjnzndQ23BhEioTQlyvJFCmoL5+hfNt3cROc+7ZL4lxoeh0sPfzc6N3FkIIF0mgTEGNLV2oKpimOTfVTKCfN0kJRvYekkkjhRATRwJlCqpv7kQHxEQEOL3OguRo6ps7qW24OHGFCSGuaxIoU5C5uZNpYf7D3sw4kpTECAA+P3V+osoSQlznJFCmGMVmo9HSicnJ8yeDIkL9mR4ZyOEvJVCEEBNDAmWKOd/aTb+ijjlQAObeHMmxqmas/bYJqEwIcb2TQJlizM0Dd7w7e4XX5W6dFUlPn8KpulatyxJCCOcCpbq6mvz8fDIzM8nPz6empmZIH0VRKCoqIj09nYyMDIfnp7jatm/fPh544AFSUlLsD/Ua9OKLL7Jw4UJycnLIyckZ8Zkq1xpzSyehQT4E+HmPed05idPQ65DDXkKICeHUA7bWrVvHsmXLyMnJYefOnRQWFrJt2zaHPrt27aKuro6ysjLa2trIzc1l4cKFxMXFudwWHx/PM888Q2lpKX19Q6dgz83NZe3atdqMxBRgU1XMzZ3MiA1xaf2gAB8S48L4/NR5lmXO1rg6IcT1btQ9lJaWFiorK8nOzgYgOzubyspKLBbHZ5aXlJSQl5eHXq/HaDSSnp5OaWnpuNoSEhJITk7Gy8up3LvmNTR30tOnEOvk/SfDuXVWJKfqWunqsWpYmRBCOBEoZrOZ6OhoDIaBS1QNBgNRUVGYzeYh/WJjY+2vTSYTDQ0N42obze7du1m6dCnLly/n0KFDTq0zlX15aRp6V07ID5p7cySKTeX4mRatyhJCCMDJQ16e6MEHH+Sxxx7D29ub/fv3s3LlSkpKSggPD3d6G8eOHRuyrKKiQssyNXXkSzO+3jraWsy0WwZmGJ4e4U1tXa1Dv+GWmUIVvqpuw6qoeBmgbN9x9N3aTcXiyeMmtY2dp9YFUpurJqO2UQPFZDLR2NiIoigYDAYURaGpqQmTyTSkX319PampqYDjnoerbVcTGRlp//7OO+/EZDLx5ZdfsmDBAmd+bgBSUlLw9f375IoVFRWkpaU5vf5kqqiooKG1j9jIYGYkzLAvDwoKIuGGBIe+wy0zxUQRZUwEIOWzPsztPZr9rJ4+blLb2HhqXSC1uUqr2np7e4f9Q3zQqIe8IiIiSE5Opri4GIDi4mKSk5MxGh2fEpiVlcX27dux2WxYLBbKy8vJzMwcV9vVNDb+fTr2L774gnPnznHjjTeOut5U1Wu10djSRWSY89OtjGTurEhqGy7SeqFHg8qEEGKAU4e81q9fT0FBAVu2bCEkJMR+Ce+KFStYvXo1c+bMIScnh8OHD7NkyRIAVq1aRXx8PIDLbQcPHuTJJ5+ko6MDVVXZvXs3zzzzDIsWLWLTpk0cP34cvV6Pt7c3zz33nMNey7WmodWKCkSG+497W3NvngbAkdPNfHNe3Li3J4QQ4GSgJCYmOtwfMmjr1q327w0Gw4j3grjaNn/+fD788MNh2668L+VaZ24duGw6Mmz8gTJzehgBfl4crZJAEUJoR+6UnyLMFiuhgT4E+o/9hsYrGfQ6bpkZwdHTzRpUJoQQAyRQpghzq5UbYly7oXE4qTdNo765k5b2bs22KYS4vkmgTAG9VoXz7VYSYoI12+acxIHzKLKXIoTQigTKFFBT346qQoJJuz2UGbGhBPp7c0QCRQihEQmUKaDqXDuApnsoBr2OlJkRHK2SQBFCaEMCZQqoOtuOv68eY4ifpttNvWkaDS1dNLV2abpdIcT1SQJlCqg614Yp3BudTqfpdufcNHAe5ZjspQghNCCB4uGs/TZqzRcwGX0033ZCTAjBAT5yHkUIoQkJFA9X23Bh4JG/4eO//+RKer2OlMQIjlbJzMNCiPGTQPFwVWcHTshPxB4KDFw+3GTpotEi51GEEOMjgeLhqs61EejnhTHIMCHbT700r5c8FlgIMV4SKB7uzNl2bpweqvkJ+UE3RAdjDPHj0MmmCdm+EOL6IYHiwRTFRnV9O4nTwybsPXQ6HbclRfL5qfMoNnXC3kcIce2TQPFgZ5s66Ou3kRgXOqHvMy8pio5uK1Vn2yb0fYQQ1zYJFA82eId84vSJDZS5N0ei08FncthLCDEOEigerOpcGz7eBqZHaTflynBCg3xJjAuT8yhCiHFxKlCqq6vJz88nMzOT/Px8ampqhvRRFIWioiLS09PJyMhweCCXq2379u3jgQceICUlZcgDta623rWi6mw7N8aGYNCP/4R8v2KjydLl8HWxq8/eftusSE7UttLZbR33ewkhrk9OPbFx3bp1LFu2jJycHHbu3ElhYSHbtm1z6LNr1y7q6uooKyujra2N3NxcFi5cSFxcnMtt8fHxPPPMM5SWltLX1+f0+10LbDaVM+faWZymzc/Ta1WG3BE/LymK4ICB+1tuS4pi+54vOXK6mYVzTJq8pxDi+jLqHkpLSwuVlZVkZ2cDkJ2dTWVlJRaLxaFfSUkJeXl56PV6jEYj6enplJaWjqstISGB5ORkvLyG5t7V1rsWNFg66e7tJzFu4q7wutzsBCP+vgY57CWEcNmogWI2m4mOjsZgGLixzmAwEBUVhdlsHtIvNjbW/tpkMtHQ0DCuttHqcmW9qWLwDvmJPiE/yNtLz5zESD472YSqyuXDQoixc+qQ17Xq2LFjQ5ZVVFS4oZKh9n/ejl4PzfWnaWscOIdibjBTW3fWod/0CG9q62pdWmYKVfiq+u+XCk8L6OGApYt3/3qAiOCxfTQ8ZdyGI7WNnafWBVKbqyajtlF/a5hMJhobG1EUBYPBgKIoNDU1YTKZhvSrr68nNTUVcNyDcLVttLpcWe9yKSkp+Pr62l9XVFSQlpY2pm1MlJ0HP2KGSc/tC+YDA7WZYkwktDtOwRIUFETCDQkuLTPFRBFlTPz764QOSg7uoUc/jbS0RJzlSeN2Jalt7Dy1LpDaXKVVbb29vcP+IT5o1ENeERERJCcnU1xcDEBxcTHJyckYjUaHfllZWWzfvh2bzYbFYqG8vJzMzMxxtV2Nq+tNBaqqUnWufdIOdw2KnRZEQkwwHx01j95ZCCGu4NRxjfXr11NQUMCWLVsICQmxX8K7YsUKVq9ezZw5c8jJyeHw4cMsWbIEgFWrVhEfHw/gctvBgwd58skn6ejoQFVVdu/ezTPPPMOiRYuuut5U19zWw4XOvgkPlMFLiS83PzmaNz84jeVCj+ZPiBRCXNucCpTExMRh7/PYunWr/XuDwUBRUdGw67vaNn/+fD788MMxrzfVVZ0bOK8x0Vd4DXcp8dybI9nx/mn+dtTMfXfeOKHvL4S4tsid8h7ozLl29DqYYQqZ9PeeHhlEfHQQ+w/XT/p7CyGmNgkUD1R1tp3pUcH4+brnIrw7UmM5fqaZ1os9bnl/IcTUJIHiYVRV5fTZ1kk/IX+5O1Njsanw8bFr574eIcTEk0DxMOfburFc6CUpIdxtNcwwhRA7LZCP5LCXEGIMJFA8zMmaVmBgKhR30el03Dk3liNVzbR39LqtDiHE1CKB4mFO1Fnw8TYwI3byT8hf7s7UWGw2lb/JPSlCCCdJoHiYkzWt3BwfhpfBvf9pZk4PJSEmmHc+qpG5vYQQTpFA8SB9VoWqc20k3eC+8yeDdDod9901kzP17Zy4dBhOCCGuRgLFg5w5106/ojJ7hvsDBeBb8+II9POieP8Zd5cihJgCJFA8yInagWfMJLnxhPzl/H29uHfBDew/XI/lgtyTIoS4OgkUD3KitpWocH+PmkPrvjtuRLGp/OXj2tE7CyGuaxIoHuRkjcWtlwsPJzYyiHmzoyj9Ww39is3d5QghPJgEiodobuumub3HrTc0jiT7zhuxXOjhb0fkEmIhxMgkUDzEydpLNzTO8Kw9FIB5s6OJiwritb+ckL0UIcSIJFA8xIlaC95eem6Mdd8cXiMx6HX8aOktnDvfwTsf1bi7HCGEh7qunynvSU7UWLgpLgxvL/dm/HAP3fL38+LrydHcenMkfyo7weK0OIICfNxUoRDCUzn126u6upr8/HwyMzPJz8+npqZmSB9FUSgqKiI9PZ2MjAyHB3JNRNuLL77IwoULycnJIScnZ0o/bKunt5/TZ9s94nBXr1Xhs5NNDl/dPf3odDqW338Lnd1W/pyKKnUAABkLSURBVPTuSXeXKYTwQE7toaxbt45ly5aRk5PDzp07KSwsZNu2bQ59du3aRV1dHWVlZbS1tZGbm8vChQuJi4ubkDaA3Nxc1q5dq/2oTLIjp5vpV2zMS4p0dylXdWNsKBm3J7B7XzXfvuNGpkcGubskIYQHGXUPpaWlhcrKSrKzswHIzs6msrISi8Xi0K+kpIS8vDz0ej1Go5H09HRKS0snrO1acvBEI34+Bm6ZGeHuUkb1/azZ+HgbePH/fI4iJ+iFEJcZNVDMZjPR0dEYDAZg4FnuUVFRmM3mIf1iY2Ptr00mEw0NDRPWBrB7926WLl3K8uXLOXTokPM/tQdRVZWKE02k3hSJt5fB3eWMKjzYj5X/mMrxMy3875Iv3F2OEMKDTNmT8g8++CCPPfYY3t7e7N+/n5UrV1JSUkJ4uPP3cRw7dmzIsoqKCi3LHNX5ditNli6+nugz6nubG8zU1p11WDY9wpvautoJXWYKVfiqus3+Ohj4+s2BvPXBabyVVr4W7z/p4zYWUtvYeWpdILW5ajJqGzVQTCYTjY2NKIqCwWBAURSampowmUxD+tXX15Oamgo47l1MRFtk5N/PN9x5552YTCa+/PJLFixY4PQPn5KSgq+vr/11RUUFaWlpTq+vhbf/WgU08p0lXyfaGDBiv4qKCkwxJhLaHfdigoKCSLghYUKXmWKiiDImOixLnatQsHkfuw60ExXqRebib1z153QXd/w3dZan1uapdYHU5iqtauvt7R32D/FBox7yioiIIDk5meLiYgCKi4tJTk7GaHS8IikrK4vt27djs9mwWCyUl5eTmZk5YW2NjY329/7iiy84d+4cN95441jGxiNUnGgkLiroqmHiiby9DBT88wK8vfT89/vNmJs73V2SEMLNnDrktX79egoKCtiyZQshISFs3LgRgBUrVrB69WrmzJlDTk4Ohw8fZsmSJQCsWrWK+Ph4gAlp27RpE8ePH0ev1+Pt7c1zzz3nsNcyFfT09nOsqoX77px6QXixqw9VVflp/m38v68d5Ocvfsgvf7SA5Bmef2GBEGJiOBUoiYmJDveADNq6dav9e4PBMOK9IBPRNhhqU9nRqoHLhdNmR7m7lDHr7unns5NNAHz95gA+Pd3Nr/7rE57+f+7gpvgwN1cnhHAHmXrFjSpONOHrYyAlcWr/VR8cYOA737oJXx8D//b/7WX3vjPy2GAhrkMSKG4ycLlwI3OnwOXCg9OxXP7Va1Uc+oQF+fLvP7qd1Jum8dJbR9nwxwO0d/S6qWIhhDtIoLjJiZpWGlq6WHBLjLtLGdVw07EMN+twgJ8Xjz2QyoMZs/jsZCOPbdzD2389jWKTvRUhrgcSKG5S8rdqAvy8uPu26e4uRTO9VoXPT50nItSff1x8M8H+Pvzhz8d58vm/cvR0s7vLE0JMsCl7Y+NU1t7Ry77P68n6RgL+vtfmf4JpYf5851uJKDaVHe+f5qnf7+eWmRHkp8/i1lmR6HQ6d5cohNDYtfnbzMOVH6ijX7GRdccMd5cyoXQ6HfOSIrn15kg+/PwcpX+rofDlvzFzeig5d8/krrnT8fEeOH90sauP7p5+h/X9/bwIlmnyhZgyJFAmmc2mUvpxDbfMjCAhJsTd5Uy4XqvCydpWjCF+5KfP4ovaVk7WWnj+T4f4w5+Pk7HgBu6ZH4+fj5f9MuRB85KiXA6UwYDy8g+zP99FAkqIiSWBMskOnWqioaWLh/8h2d2lTDqDQU/KzAgezppNQ0sXuz+q5q2/VrHj/dMkxAQTFxXMzOkhhAT6jr6xUQzeJ1Nbd9Y+Xc14AkoIMToJlEn2zkc1hAX5snBO7Oidr1E6nY65syKZOyuS1os97D10jncP1LH/SD37j9RjDPFjhikEf18vQoN98fX27MuqhRADJFAmUXV9O59WNvCP99zs9kf9eorwYD/uvzuRb6SYeL/iK6rrL1BjbufQqYHLk70MepISwpl1Qzg3xYVyU1wY0RGBGPRyUl8ITyOBMkn6FRu/ff0QIUG+5H7zJneX41bDPbe+16oQGuTLrbMiuXVWJH1WBX9fL75q6uD4mWZ27T1jv/fFx0vP9Kgg4qOCMU0LJCYigOiIQKLDA4gI9cNgkLAWwh0kUCbJWx+c5sy5dn7xg68TEnh9H8fvtSocueK+lKQEx+fY+HgbmHtzJBm3D0ylb+23Uddwgapz7XzVeJGzTR2crGtl35F6bJfdOKnX6QgP8cUY4odBr8PW30OPaiEk0Je22F4iw/01u2RZrkwTwpEEyiSoa7jA//zlJHfOjeWO1Ov33Ml4eHvpSYwLIzHOceLJfsXGyRoLHx01c7Grj4udfVzo6qO/30Z9czed3VZOnfsKgDc/OI2Pl57oiACijYFEhfszLcyfyDB/jKF+hAb6EhLkQ3CAD15O7OVcPkHmoOFO/I8UPM6Q0BJTiQTKBLP223jhjc/x9/Xise+kurucKW+4X7AhQb7ERwc7LEtKCOdkbStnamoIj4jhQkcfIYE+dPX202jpoqGlky9qLHR2W4d9Hy+DDl8fL3y9DRgMA3s0g/s1qgoqA/OxWfsHDsPpdAMXG7z119ME+Hnj623A18dAoJ83eh1c7LLi7+tl/5qfHEVXrw1VVa+6x+RsaAnhCSRQJlBHVx//69VPOVnXyr89NJ+w4PFfDns9Gelcy/EzLQ7LrjxcdjmDXkd4sB/hwX7MS4oi6ooHmdU1XGD/4Xo6e6x09yr09PVjDPHDy6Cnp6+f3j4Fm6rS2d1PS3s3MBAeoCM0yIcLHX32cFFVlaAAHxTFRp/VRme3lXNNHXT1WOns7sd22QzMu/adAeC3f95NZJgfkeEBRIUHEBMRQExEIKaIQEzTAl0fPCHcQAJlgpibOyn6r49ptHTxr8vmsegamrNrsjhzrmW8/Hy8CA/xIzzEz75suOBpsnQN2VMY3AtyZtmJGgvWfhtdPf109VqJNgZSXVOLf/A0zrd1c761i4+PmbnQ2eewblCAN0H+3oQF+RIa5EtokA/GYF98fQyEBPrIFDbCozgVKNXV1RQUFNDW1kZYWBgbN25kxowZDn0URWHDhg3s3bsXnU7Ho48+Sl5enlva3Kmj20rZx7X83/e+BGDDY3dwy8yp/byTa8VIezyTQafT4eNtwMfbQFiwL/OSoojxs5CWlmLv02Tp4uPjZi509NHe2Ut7x0C41Jov8FVTBycuBVXZJ3UA+PoYiAr3JzzYD2OIH2HBvgQH+NhDyM/HC18fA34+A+/r7aXHx2vgX28vPV6XXuvlEmyhEacCZd26dSxbtoycnBx27txJYWEh27Ztc+iza9cu6urqKCsro62tjdzcXBYuXEhcXNykt00mVVVpae/h9Nk2Dp1s4r2DX9HTpzAncRo/yZtLbGTQpNYjRubsHo87g8fHy8C0sIGLBQbrG9zjsfbbuNDZy7RQf3qtCo2tXZxv7abtYi9f1FhovdhLnwt1ehkGAsbX24CPtx69TiVk318J8PPGz8dgDyZfH8OlPgZ8LgWSt0GPl0GPwaDHoNdhMOjo7VOw9tvQ63QM7kD5+hjw9/UaOP+kqthUsF06TGizqSi2gX87e6z09g4cZrTZBvoZDDp8vAyAyldnL1LTPvDH2uChR71+4Oo+vV53qYaBWrwu1eZl0OHlpbf/nFf+a9AP9DFc6qu/tK5Op0N/6dyYcM6ogdLS0kJlZSWvvPIKANnZ2Tz99NNYLBaMRqO9X0lJCXl5eej1eoxGI+np6ZSWlvLII49MettoBp8m2NfXN6Stt/fqD4Vqae+meF81bR29XOjso7W9hwtdA9sx6PUsnmciY0ECN8QEO7W9sei39qHH8ReG0m91+zIfLx16FI+o5cplg7WNZd2u7h7OnGt3WDZzeqim9fX09mLwDaa+sc2+rK/fdtV1fb0gMtSHlJlhRFwKnEGd3VZ6evuxKio9vVa6evvp6rZypv4C1n4bNtWGoqgYQ/1obOlCsakoig3FphIU4E1Ley/9ig1FsdHR2UWwn56+fiut3b1Y+xWsVoU+xUZ/v83tz7c5+OXJyX1D3UBg6S4LL+xh8/c+qk3F692/DATRpWDTMxBIBoNu4EoOHeh1oNfr0et0l/YS9egNl8JQrx8INL0evR57QF4emDodl/7VDdR1aZlOBzr+HuIDFQ8wN3Zw9uLAuPl461k4J9almc4Hf2eO9ETWUbdoNpuJjo7GYBiY/sJgMBAVFYXZbHYIFLPZTGzs3y+JNZlMNDQ0uKVtNFbrwJU9p06dGtJ27NixUddPSwDwvvQ19MTpheZajk3A4z/MZ6uIuOLinvbzbW5fFjEjEGjziFquXDZYmyfUcrnz9QM1mc9edFjuzLrms22YzzIqP+BrQ57f1s3McB0D16xdfmn05ReMyMUAnkMFxr93HBcSBHTYX1d9eWFc27Narfj5+Q1Zfl2elA8MDGTWrFl4e3vL7qwQQjhJVVWsViuBgcP/0TFqoJhMJhobG1EUBYPBgKIoNDU1YTKZhvSrr68nNXXgXovL9yAmu200er2e4ODg0TsKIYRwMNyeyaBRbweOiIggOTmZ4uJiAIqLi0lOTnY43AWQlZXF9u3bsdlsWCwWysvLyczMdEubEEKIyefUIa/169dTUFDAli1bCAkJYePGjQCsWLGC1atXM2fOHHJycjh8+DBLliwBYNWqVcTHxwNMepsQQojJp1NHOl0vhBBCjIHM8y2EEEITEihCCCE0IYEihBBCExIoQgghNHHdBEpBQQF33303OTk55OTk8Pvf/97e1tzczPLly8nMzOT+++/n8OHD427TSnV1Nfn5+WRmZpKfn09NTY3m73Gle+65h6ysLPtY7d27F4DPP/+c+++/n8zMTJYvX05Ly9+nkXe17Wo2btzIPffcQ1JSksOsBlcbk4loG0ttI43dZI5fa2srK1asIDMzk6VLl/KTn/wEi8UyYTWMpb6r1ZaUlMTSpUvtY3fy5N+nWHnvvffIysoiIyODJ554gu7u7nG3XWnlypXcf//95ObmsmzZMr744gvAMz5vI9XmCZ83B+p1Yu3atep///d/D9tWUFCgbt68WVVVVf3000/VjIwM1WazjatNKw8//LD69ttvq6qqqm+//bb68MMPa7r94SxevFg9efKkwzJFUdT09HT1008/VVVVVTdv3qwWFBSMq200n376qVpfXz+knquNyUS0jaW24cZutHHQevxaW1vVjz/+2P762WefVX/xi19MSA1jrW+k2lRVVWfNmqV2dHQMWaejo0O944471OrqalVVVfWpp55SX3zxxXG1DefChQv279999101NzdXVVXP+LyNVJsnfN4uJ4Giquqtt96qtrS02F/fd9996uHDh8fVpoXm5mY1LS1N7e/vV1VVVfv7+9W0tDSH95wIw31IDx8+rN5333321y0tLeqtt946rjZX6rnamExE21jHaqT/wd05fqWlpeoPfvCDCalhvPUN1qaqIwdKSUmJ+uijj9pfHzlyRP32t789rrbRvPXWW+p3vvMdj/u8XV6bqnre5+26msvrlVde4Y033iA+Pp5//dd/JTExkdbWVlRVdbjzf3Ciyfj4eJfaBqeDGS9nJ+acCD/72c9QVZW0tDSefPLJIVPbGI1GbDYbbW1tLreFhTk+H94ZVxsTVVU1b3NlnK8cu5CQELeNn81m409/+hP33HPPhNQwnvour23Qww8/jKIo3H333Tz++OP4+PgMeY/Y2FjMZjMwdMolZ9tG8stf/pL9+/ejqir/9V//5VGftytrG+RJn7dr5hzKd77zHW6//fZhvxRFYc2aNbz77rvs2rWLJUuW8Mgjj6Aok/OMi6nmtdde489//jM7duxAVVV+9atfubukKcPTxu7pp58mICCAhx56yK11DOfK2j744APefPNNXnvtNU6fPs3mzZsnvaZnnnmGDz74gDVr1vDcc89N+vtfzXC1edrn7ZoJlLfeeotPPvlk2C+DwUB0dDR6/cCPm5ubS1dXFw0NDYSHDzxgafDEIAz8ZRMTE+Nym1Yun5gTGHFiTq0Nbt/Hx4dly5bx2Wef2SfjHGSxWNDr9YSFhbnc5mptI43JRLS5Uh84jt3g8skev40bN1JbW8tvf/tb9Hr9hNTgan1X1nb52AUFBZGXlzfi2NXX19v7uto2mtzcXD755BNiYmI87vM2WFtra6tHfd7gGgqU0TQ2Ntq/37t3L3q9nujoaGBgosnXX38dgIMHD9LT00NKSsq42rTg7MScWurq6uLixYFndKiqSklJCcnJyaSkpNDT08PBgwcBeP3118nKygJwuc0VVxuTiWjTYuzGM0aujt+mTZs4duwYmzdvxsfHZ8JqcKW+4Wprb2+np6cHgP7+fv7yl7/Yx27RokUcPXrUfiXU66+/zj/8wz+Mq+1KnZ2dDofD3nvvPUJDQz3i8zZSbb6+vh7zeRt03czl9cMf/pCWlhZ0Oh1BQUH827/9G7feeisA58+f5+c//zn19fX4+vpSVFTEvHnzxtWmlaqqKgoKCrhw4YJ9Ys6ZM2dq+h6X++qrr3j88cdRFAWbzUZiYiL//u//TlRUFJ999hnr1q2jt7eX6dOn85vf/IZp06YBuNx2NRs2bKCsrIzm5mbCw8MJCwtj9+7dVx2TiWhztraXXnppxLEbzxiNdfy+/PJLsrOzmTFjhn2q8bi4ODZv3jwhNYylvpFqe+SRRygsLESn09Hf389tt93GU089ZX/uRnl5Ob/5zW+w2WwkJyfz7LPPEhAQMK62yzU3N7Ny5Uq6u7vR6/WEhoaydu1abrnlFrd/3kaqLSQkxCM+b5e7bgJFCCHExLpuDnkJIYSYWBIoQgghNCGBIoQQQhMSKEIIITQhgSKEEEITEihCuMndd9/NJ5984u4yRvS9732PN998091liCnkuprLS4jh3HPPPTQ3N9vnVgIoLS213/gK8Pzzz9PY2Mizzz5rX9bf388tt9zCnj17iIuLm9SahfBEEihCAC+99BJ33HGHu8twSn9/P15eY/tf15V1hBgrOeQlhEa+973v8cILL/Dggw9y22238eMf/5i2tjZ7+5tvvsnixYu5/fbbefnllx3WtdlsvPTSS6Snp3P77bezZs0a2tvbAaitrSUpKYkdO3bwrW99i+XLlwPYX99+++289NJLDofQnn/+eZ544gmefPJJbrvtNv785z9z6NAhvvvd7zJ//nzuuusuNmzYgNVqtdfw4YcfkpmZSVpaGhs2bEDueRZjJYEihIaKi4t59tln+eijj+ju7uaVV14B4OTJkzz99NP853/+J3v37qWpqYnm5mb7eq+++ioffPABr732Gh9++CEBAQFs2LDBYdsHDx7knXfe4eWXX+bkyZNs2LCBTZs2sXfvXiwWi8P2YGDakezsbCoqKvj2t7+NwWDgl7/8JR9//DF/+tOf2Lt3L2+88QYALS0t/PSnP+VnP/sZH3/8MTExMRw5cmSCR0tcayRQhABWrVrF/PnzmT9/PitXrnR5O//0T//EjBkz8Pf3JysrixMnTgAD52Tuvfde0tLS8PHxYc2aNQ57AK+//jpPPvkk0dHR+Pr68pOf/ITS0lJsNpu9z+OPP46/vz9+fn6UlpaSnp7OvHnz8PHx4YknnhhSy7x587jnnnvQ6/X4+fmRmprK3Llz8fLyIj4+nu9+97scOHAAgPfff5/Zs2eTkZGBt7c3y5cvn/Bn7ohrjxxUFQLYvHnzVc+heHl5ORwegoHzEgDe3t72ZZdPoufv709XVxfAkOnJAwMDCQ0Ntb+ur6/nscces0/lPujy53lfvv6V2wsICCAkJMRh3SunQ6+qqmLjxo0cP36c7u5uFEWxPwzuyu1dPhu3EM6SPRQhnGAymTh37pzDsrNnz+Lt7U1kZOSo60dGRjpMQd7Z2Wk/RwIQExPDK6+8wsGDB+1fR48eddi2Tqdz2F5DQ4P9dVdXFxcuXHB4z8v7A6xbt46bb76ZsrIyPvvsM1avXj1ifTabzeGRD0I4QwJFCCd885vf5NSpU+zatQur1UprayvPP/88WVlZQ/YqhpOVlcWePXs4dOgQfX19/Pa3v3X4hf/ggw+yadMm+8ONWlpa2LNnz1W3V15ezueff05fXx8vvPDCqDV0dnYSHBxMQEAAVVVV9vMnAIsXL+bEiROUl5djtVp59dVXHR4eJ4QzJFCEGIaiKNx2220cOnQIGPgL/uWXX+a1117jjjvu4P7778doNFJYWOjU9mbPns0vf/lLnnjiCRYtWkRkZKTD4bEf/ehHLFq0iB/+8IfcdtttPPjggxw9evSq2/vFL37BT3/6UxYtWkRYWBhhYWH2B1YNZ+3atbz11lvMmzePwsJCh4dNTZs2jeeff57f/OY3fOMb36C+vt5+OEwIZ8nzUIS4BnR0dDB//nzef//9CX9EtBAjkT0UIaaoPXv20N3dTWdnJ88++yxf+9rXJEyEW0mgCDFFlZeXs2jRIr75zW9y7tw5Nm3a5O6SxHVODnkJIYTQhOyhCCGE0IQEihBCCE1IoAghhNCEBIoQQghNSKAIIYTQhASKEEIITfz/p2n2T2IrYAgAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = sns.distplot(college[\"F.Undergrad\"])\n" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = sns.distplot(college[\"P.Undergrad\"])\n" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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Fubm5OH78+IwCIicnBzqdzuP+rtTV1SE/P98r6/In3X0jsNquIz9nKfLzP/t/W994BRmLM6b0NyYbYPhCJi50foI3/usyUjJWQhRUyOgTlfvqM+d1/N4UrNvYlVCrOdTqBWZWs9Vq9eiDtdtDTPHx8cjOzkZVVRUAoKqqCtnZ2dDr9U79ioqKUFlZCYfDAYvFgtraWhQWFrptu3LlyuQ6LBYL3nvvPaxYscKjIslzE1cwpXl4iGnCg/cshSAIeP345fkYFhH5MY8OMe3atQvbt2/Hvn37EBMTgz179gAAtmzZgm3btiE3NxclJSWor6/Hxo0bAQBbt25Feno6ALhse/XVV3Hy5Emo1WrIsoyHH34Yd999t9cLDXWtNwLC03MQE+Jjw3HvX6Wj9oNWbPji4vkYGhH5KY8CIjMz0+nehQn79++f/F4URVRUVCi+31Xb008/7ckQaI6udQwiMlyDuOiZH4r72rpl+PN7LTj2fqvbm+yIKHjwTuoQ0doxfgXTbC4hTkmIwpdvS8XxuquwjknzMDoi8kcMiBBxzTyANEPUrN//9fXLMTom4eyVLi+Oioj8GQMiBPQNWtE3OIbFyTM7/3CzpamxyFkaj4YrXZBlPpKUKBQwIELANbPnU2y4sirLgKFRO/oGOcsrUShgQISAiSuY0g1zC4gV6XEAgLYuPrOaKBQwIELAtY4BhGlFJMSFz2k9xoRIhGlFmLqGvDQyIvJnDIgQ0NoxfoJaEOY2CaJKpYIxIRJtDAiikMCACAFXOwbmfP5hQkpCFPqHxjA0YvPK+ojIfzEggtzwqA3dfaNeCwhjQiQAcC+CKAQwIIJca/v4CeqM5BivrC8xLhxqUYCJJ6qJgh4DIsg1m/oBYE73QNxMEFRIjo/gHgRRCGBABLmW9n6E60QYFkV4bZ0pCZHo7hvltBtEQY4BEeRa2wewOClmzlcw3cyYMD5lh6mbexFEwYwBEeRa2vu9dnhpQpI+AoJKxfMQREGOARHEegfG52DKMHrnBPUEjVpA4qJwnocgCnIMiCDWcuMEdYaX9yCA8ctdzT0jkBycuI8oWDEgglhL+0RAeHcPAgASYsPgcMjoG7R6fd1E5B88eqIc+a+B4TGMjNqdloWHqREdoUVL+wBiIrWzeoqcO/qYMABAT/+o19dNRP6BARHgRkbtOH3B7LTsjizDjYDoR0ZyzKyeIudOXPR4QFgYEERBi4eYgpQsy2ht75+X8w/A+InqmEgtA4IoiDEgglRnzwhGrBIWe/kKppvpY8Jg6ec5CKJgxYAIUs3t83cF0wR9TBh6B6ywS455+xlE5DsMiCD12SWu87kHoYNDlmHuGZ63n0FEvsOACFKt7QNIiAtHZLhm3n7GxJVMbZ28YY4oGDEgglTLPJ6gnjBxJROfUU0UnBgQQUhyOHC1Y3BeDy8Bn13JxD0IouDkUUA0NTWhrKwMhYWFKCsrQ3Nz85Q+kiShoqICBQUF2LBhAyorKz1q27t3Lx544AFs2rQJX/va1/Duu+/OvaoQ1949DLvkQIZxfvcggPHDTNe5B0EUlDy6UW7nzp0oLy9HSUkJDh8+jB07duDgwYNOfY4cOYLW1lYcO3YMvb292Lx5M9asWYO0tDSXbXl5eXj00UcRHh6O8+fP4+GHH8aJEycQFhY2LwWHgokpNjLT4ub9Z+ljwlB/qRN2yQG1yB1SomDi9l90d3c3GhsbUVxcDAAoLi5GY2MjLBaLU7/q6mqUlpZCEATo9XoUFBSgpqbGbdvatWsRHh4OAMjKyoIsy+jt7fVqkaGmxTQArUZEmmEh9iB0kBwyTJzZlSjouA0Ik8mEpKQkiKIIABBFEQaDASaTaUq/lJSUyddGoxHt7e1u2272xhtvYPHixUhOTp5dNQRgfA9iaUoMRC8+JGg6E1cyTTz7moiCh9/MxfT+++/jn/7pn/CHP/xhxu9taGjw6ljq6uq8ur75pA6PQ0vrtcnXsiyjxTSAO1bEob7xinNfARgd6lV4f8uU9RpjJVxtUup7zWmZJMlQATj10QWE2Z0/NPizQNrG3hJqNYdavYD3a3YbEEajER0dHZAkCaIoQpIkmM1mGI3GKf3a2tqQl5cHwHmvwVUbAHz00Uf4h3/4B+zbtw9Lly6dcRE5OTnQ6bwzY2ldXR3y8/O9sq6FYLYMI6NPnHzd0z+KMXsfIiIiYbppOTA+iZ9Bn+m0rL7xCjIWZ0xZrzF5at/P/6wJCVcuwi5EBcz/t0Dbxt4QajWHWr3AzGq2Wq0efbB2e4gpPj4e2dnZqKqqAgBUVVUhOzsber3eqV9RUREqKyvhcDhgsVhQW1uLwsJCt21nzpzBD3/4Q/zmN7/Brbfe6lFxND1z7wgAwLAofMF+ZkpiJFo7eIiJKNh4dIhp165d2L59O/bt24eYmBjs2bMHALBlyxZs27YNubm5KCkpQX19PTZu3AgA2Lp1K9LT0wHAZVtFRQVGR0exY8eOyZ/3i1/8AllZWd6rMoR09gxDoxawKHrhrgJLTYzCJ59280omoiDjUUBkZmY63bswYf/+/ZPfi6KIiooKxfe7ajt06JAnQyAPdfaMICUxEsICnKCekJoYBbsk47p50OvPvyYi3+HHvSAiyzI6e0eQvgCXt95s4nLaphsTBBJRcGBABJG+wTHY7A6kJy1sQCTHR0AtCmhu61vQn0tE88tvLnOluZuYdjs9KQpDI3Y3vV2zSw6YLc7TeFttkmJftShgcVI09yCIggwDIoh09oxAFFQwxkfi8rW5fZq32iScudzltCwrY9G0/ZekxODji51z+plE5F94iCmIdPaOID42DKIPriRaYoyBpX8UfYN8BClRsGBABInxE9TDSFwU4ZOff0vK+NVLzTzMRBQ0GBBBom9oDGM2BxLjFu4GuZstMcYCYEAQBRMGRJDovHGCeiHvoL5ZXLQOi6J1aOKVTERBgwERJMw3TlDrY333HI0lxhjuQRAFEQZEkOjsGUZ8bDhEwXebdElKLFrbByBJDp+NgYi8hwERBGRZhrlnxGeHlybckhIDm92B6518BClRMGBABIGJO6gTfRwQS4y8kokomDAggoB58gS1by5xnZBmiIZaVKGpjQFBFAwYEEHA3DM8foI6xncnqAFAoxaQZojmHgRRkGBABAFzzwgS48IXdIrv6SxJieGlrkRBggER4BwOGZ09I0jU+/bw0oRbjLHo7uOUG0TBgAER4NotQ7BLDhh8dAf1501M6NfYZPHxSIhorhgQAW7ieL+v5mD6vBWLF0GnFXHmMmd2JQp0DIgA12zqh1oUsChG5+uhABg/UX3rLfFTpgonosDDgAhwLab+8RPUKt+foJ6QtywBre0D6BkY9fVQiGgOGBABTJIcaO0Y8Pkd1J+XtzwBAHDmEvciiAIZAyKAXTMPjk/x7SdXME1YmhqHyDA1DzMRBTgGRAA739IDAEjykxPUE0RBhZzMBJ6oJgpwDIgAdqHFgqhwDWKjtL4eyhR5yxPQ3j2MDsuwr4dCRLPEgAhg55otyEyNhcqPTlBPWJYWBwA4WX8dZsvw5NfA8JiPR0ZEnvIoIJqamlBWVobCwkKUlZWhubl5Sh9JklBRUYGCggJs2LABlZWVHrWdOHECX/va15CTk4M9e/bMvaIQ0T80hmvmQWTe+EPsb+JjwhCuU+PkmTacvmCe/BoZtft6aETkIbUnnXbu3Iny8nKUlJTg8OHD2LFjBw4ePOjU58iRI2htbcWxY8fQ29uLzZs3Y82aNUhLS3PZlp6ejp/97GeoqanB2Bg/XXrqQsv4ncrL0mIx5Id/dFUqFVITo3DNPAhZlv1yL4eIXHO7B9Hd3Y3GxkYUFxcDAIqLi9HY2AiLxXkqherqapSWlkIQBOj1ehQUFKCmpsZtW0ZGBrKzs6FWe5RVdMP5lh4IggpLjLG+Hsq00gxRGB61w9LP+yGIApHbgDCZTEhKSoIoigAAURRhMBhgMpmm9EtJSZl8bTQa0d7e7raNZud8swVLU2Kg04q+Hsq0lqTEQKUCLrb2+nooRDQLQfGxvaGhwavrq6ur8+r6vE1yyDjX1I1VmZEwtZvQ0nrNqT01XoOW1pYp7zPGSrja5PzHWh0ep9hXaR3TrXeJQQtTu/MHBrUmDF3mNiTGqvHJp50wxlihUqkUx+AL/r6N50Oo1Rxq9QLer9ltQBiNRnR0dECSJIiiCEmSYDabYTQap/Rra2tDXl4eAOe9Bldt3pCTkwOdzjtzEdXV1SE/P98r65ovV671wiZdx1e+mAVjsh4Zfc57EVFRUchYnDHlfcZkAwz6TKdl9Y1XFPsqrWO69erCI9Fsdj5/lJUx3tcu9KLmVAtUOj0ykmMUx7DQAmEbe1uo1Rxq9QIzq9lqtXr0wdrtIab4+HhkZ2ejqqoKAFBVVYXs7Gzo9XqnfkVFRaisrITD4YDFYkFtbS0KCwvdttHMnW8eP/+zMkPvpqfvLUmJQZhWnBwzEQUOjw4x7dq1C9u3b8e+ffsQExMzeTnqli1bsG3bNuTm5qKkpAT19fXYuHEjAGDr1q1IT08HAJdtH374IZ588kkMDo5f7fLWW2/hZz/7GdauXev1YoPFueYe6GPCkLgoHJ09I74ejkuiIGD54kX45NNujI7539VWRDQ9jwIiMzPT6d6FCfv375/8XhRFVFRUKL7fVdvq1avxl7/8xZNh0A3nWizIXqIPmEtHszMW4ezlLly+2ou7cr13aJGI5hfvpA4wlv5RmC3DWLlkka+H4rGEuHDEx4bhHA8zEQUUBkSAaWzqBhAY5x8mqFQqZC/Rw9wzgmvmAV8Ph4g8xIAIMO81tCM6Qovl6f45xcZ0shYvgloU8B//M/UyWSLyTwyIAGKzO/BBYzu+eGsSRDGwNl2YTo2cpfF47xMTTF1Dvh4OEXkgsP7KhLizV7owNGrHmhyj+85+6PasRIiCgMq3L/p6KETkAQZEADnVYEKYVsTtWQZfD2VWIsM0uGdVKt758CrMPXxOBJG/Y0AECIdDxnsNJtyx0gCdxn/nX3Kn6M4MqFTAa/952ddDISI3GBAB4uLVHlj6rQF7eGlCfGw41q9ejGPvtaC7z79v8iMKdQyIAHHqrAmioMLqLyT7eihzVnrvcsiyjH/7j/O+HgoRucCACACyLON/zpqQtywBUeEaXw9nzpLjI1FyTyZqP2jlHE1EfowBEQBaOwbQ1jWENblzO7xklxxOz4c2W4ah1oR5aZQzG8P61emIi9Lht5Ufo2/QuqBjICLPBMXzIILd0VMtEAQVvjTH8w9Wm4Qzl7uclqXGL+weyc1j+OKtSTj2XiuOnmrBNwpWLOg4iMg97kH4OXPPMP7jv5tR8FeLoY9Z2E/7821ZWhxSEyPx2vHL6B/i88iJ/A0Dws+9+ufxm8rKNgTfJ2yVSoW1t6dh1GrH7w7VQ5ZlXw+JiG7CQ0x+rK1zELUftKL4y7cgXKeG2TL15jKrTfLByLwnPjYMJfdk4rXjl5G/shUFX5z6xDoi8g0GhB8aGB7DyKgdfzjyCdSiCl+9Iw29A1Z88mn3lL5ZGYEz7fd07luzBJev9eL/vn4W2bfEIzUxytdDIiLwEJNfGhm149h7LXjvk3bkZibgyvU+2CWHr4c1bxyyjP99XzbUooCf//F9XDcPYmCY5ySIfI0B4YdGrHb8+f1W6LQibl+R6OvhzDurTUKTqR9rV6WipX0Av/n3jzA8YvP1sIhCHgPCz0gOGfsPn0XPwCiK7sxAmDZ0jgIuTYnFHVkGNDZZ8NbJJl8PhyjkMSD8zMs151B/qQtrb0tFmiHa18NZcHfmJCNr8SK8/l9XUPt+q6+HQxTSQufjaQA4eqoZlW9fwldWpeLWpfG+Ho5PqFQqrFudBlFU4beVHyM6QjPnGwSJaHa4B+EHxieuO4ffVtZj1YpElBeuhEql8vWwfEYUBHz/odtwS2osfvbH9/Haf17mPRJEPsCA8LExm4T/8291eLX2IjZ8cTF2PHYn1AH2ONH5EK5T4+ff+zLuyk3BgapP8OtXPsJYgN/zQRRoeIjJhxqudOHF186gpX0A33rgC3ho3bKQ3nP4vDCdGj/536vxau1FvFxzHueaLfjmhix8ZVXqrJ/JPTA8BnV43JSbDsPD1HbOFtYAAA3XSURBVIiO0Hpj2ERBgwHhA919I/jjW404XncNhkXh2PGdL+GvguA5D/NBpVLhmxuysCJ9EV56qxG/+tNp/HvtBWy6eynys5OQHB85o/WNjNpx6uw1ZPQ5P5XvjiwDA4LocxgQC6R/yIqPL3Ti+OlrOH3BDJUKeODLt2DT2lugEUWnT7SBPn3GfLhjpQG3r0jE8dNXUfn2Jbz4+lng9bMwLArHyiV6pCdFI1kfgbhoHQRBBZVKBVmWMTJqx7DVDpvdAa1awIjVjq5+GwxWO8J1/PUncsWjfyFNTU3Yvn07ent7ERcXhz179mDJkiVOfSRJwk9/+lO8++67UKlUePzxx1FaWjqnNn83MSXG54XpRAAqdPeN4NLVXjRc6UL9pS5Y+keh04jIyUxAbmY8YqN0GLM5cPay8xQawTB9xlxNPDfi85anL8KDa5eib3AMrR39aG0fwNnLXfjLR9dntP5T5z9BVLgGCXHhMMZHIiZSi0UxOmjUgfu8byJv8yggdu7cifLycpSUlODw4cPYsWMHDh486NTnyJEjaG1txbFjx9Db24vNmzdjzZo1SEtLm3Wbv5BlGb2D1hsP2RlBR88wzD3D6OoZQXv3EKw2CXZJhl1yQJIck68nxEZpsSwtDqtWJGJZehxPQntA6dkVwHh4qlQqxEXrEBediLxlibgjy4C4aB06LMPoHxqDQ5bhcMgQVCqE69QID1NDIwoYs0to7xpGzYmzELUx6OwdQWfPCJpN/fifBhPUooDk+AgYEyKRHB8JUVBBUKmgVgtQYfz3QAYgqFQQBRVsN7a1dUzCwPAYRq0SJMkBm+SAoFIhTKdGRJgaEWEaREdoEBOpQ0ykBlERWkSHaxEZrka4ToPwMDXCteKsz6sQzRe3AdHd3Y3GxkYcOHAAAFBcXIzdu3fDYrFAr9dP9quurkZpaSkEQYBer0dBQQFqamrw2GOPzbrNnYlLH8fGZj5vz/CIDSfPtsFmd9z4gwLY7BLa2/txuvUjDAzbMDhiQ//gGCz9o7DZnQ/7TPzD12mA6HAN1KIAUVRBEASkGaJgjI9AbJQOqYlRMCZEwtI3ioZPuwHIAD5bl2S3QYDzuj1d5o2+skM1L+uda9+ZvH/UakWXbQwigEWRn+0BCALgcABw2GF3jF+ylxCrQWq8Fqkpn91nMnLjcFNn7zA6LCPo7BnG+w29sI5N3Tu8mUpQQasWodMI0KgF2CV5PFQEFWQZsNls6OkbD5ChUbvbS3UFQQWNWoRGVE0eJhNUgEO+8bsuAzJkSDe+BwCVClBB9dn3Chc5qFQqQHbg/737DrQaAVq1iDCdiMgwLXQ3XqvVAtSiCmpRgHCjBtXEmidXqbppnS5LmTHn/zUTtY7XK8vj83U5JBmSwwGbXcaYJGFsTMKYzYFRmx1jNgdsN8LaLjlgl+x4+b/egUoAtGoBOq0a4ToROo0aWo0AnVaERhShVt9Us2r8y7lcpUJlp28nxulwyJAcMiTJAbtDhs3mwJhNwpjdgaHRMVit499P/M2RHTIAFbSa8TGob/wu6bRq6DTi5LbSaIQbv1fj/53Y5lqNgLvyUpwOlVqtnj2dceJvprvfSbcBYTKZkJSUBFEc/4cniiIMBgNMJpNTQJhMJqSkpEy+NhqNaG9vn1ObOzbb+Hw9Fy9e9Kj/5xkjpi7LSowB4AAg3vgKAxAzwzVLAAYAxwAsHV2wdIwvjVc4B9rX2TtluafLvNHXNjS3cc1X35m8v7Otd2pHF/KWRAK46T031hdvAFYaRADRN75CgQzAdRD6NwGTG3BGJEDhA8j8UAHQzeJ9jhtf07tyqd/pdUNDw4x+gs1mQ1jY9A8iC+izdJGRkVixYgU0Gg0vDyUi8pAsy7DZbIiMdH0VoNuAMBqN6OjogCRJEEURkiTBbDbDaDRO6dfW1oa8vDwAznsGs21zRxAEREeHyic9IiLvcbXnMMHtWbH4+HhkZ2ejqqoKAFBVVYXs7Gynw0sAUFRUhMrKSjgcDlgsFtTW1qKwsHBObURE5Dsq2YNJbq5cuYLt27ejv78fMTEx2LNnD5YuXYotW7Zg27ZtyM3NhSRJePbZZ3Hy5EkAwJYtW1BWVgYAs24jIiLf8SggiIgo9PDCayIiUsSAICIiRQwIIiJSxIAgIiJFDIgbmpqaUFZWhsLCQpSVlaG5udnXQ/KK9evXo6ioCCUlJSgpKcG7774LAPj444/x4IMPorCwEI8++ii6uz+bMNBVm7/Zs2cP1q9fj6ysLKc76l1tz9m2+Yvpap5uWwOBvb17enqwZcsWFBYWYtOmTfjBD34Ai8UCYPZ1BXLNWVlZ2LRp0+R2vnDhwuT73nnnHRQVFWHDhg34u7/7O4yMjHjUNi2ZZFmW5UceeUR+4403ZFmW5TfeeEN+5JFHfDwi71i3bp184cIFp2WSJMkFBQXyBx98IMuyLO/du1fevn272zZ/9MEHH8htbW1T6nS1PWfb5i+mq1lpW8ty4G/vnp4e+dSpU5Ovn3vuOfmpp56adV2BXLMsy/KKFSvkwcHBKe8ZHByU77rrLrmpqUmWZVl++umn5RdeeMFtmysMCFmWu7q65Pz8fNlut8uyLMt2u13Oz8+Xu7u7fTyyuVP6o1FfXy8/8MADk6+7u7vl22+/3W2bP7u5Tlfbc7Zt/sjTgAi27V1TUyN/61vfmnVdgVyzLE8fENXV1fLjjz8++frMmTPy/fff77bNlYCei8lbPJ2QMFD96Ec/gizLyM/Px5NPPjllOhO9Xg+Hw4He3l6XbXFxcb4Y/oy52p6yLM+qLVB+Dz6/rWNiYoJqezscDvzpT3/C+vXrZ11XINc84ZFHHoEkSbjnnnvwxBNPQKvVTqkrJSUFJpMJwNQpjG5uc4XnIILcyy+/jDfffBOHDh2CLMt49tlnfT0kmiehsK13796NiIgIPPzww74eyoL5fM3Hjx/Ha6+9hpdffhmXL1/G3r175+1nMyDgPCEhgGknJAxEEzVotVqUl5fj9OnTkxMkTrBYLBAEAXFxcS7bAoWr7TnbtkCgtK0nlgfD9t6zZw9aWlrw61//GoIgzLquQK4Z+Gw7R0VFobS0dNrt3NbWNtnXVZsrDAh4PiFhoBkeHsbAwACA8el9q6urkZ2djZycHIyOjuLDDz8EALzyyisoKioCAJdtgcLV9pxtm7+bblsDrrdpoGzvX/7yl2hoaMDevXuh1Y4//2G2dQVyzX19fRgdHQUA2O12HD16dHI7r127FmfPnp288u6VV17Bfffd57bNFc7FdMN0ExIGsqtXr+KJJ56AJElwOBzIzMzEP/7jP8JgMOD06dPYuXMnrFYrUlNT8fzzzyMhIQEAXLb5m5/+9Kc4duwYurq6sGjRIsTFxeGtt95yuT1n2+YvlGp+8cUXp93WgOtt6u/b+9KlSyguLsaSJUsmp6hOS0vD3r17Z11XoNb82GOPYceOHVCpVLDb7Vi1ahWefvrpyec61NbW4vnnn4fD4UB2djaee+45REREuG2bDgOCiIgU8RATEREpYkAQEZEiBgQRESliQBARkSIGBBERKWJAEC2ga9euISsrC3a73ddDIXKLczERTWP9+vXo6uqCKIpQq9VYtWoVKioqAubOaqK54h4EkQsvvvgiPvroI5w4cQLx8fHYvXu3r4dEtGAYEEQe0Ol0KCoqwpUrVwAAAwMD+PGPf4w777wT69atw759++BwOACMz765b98+rFu3DmvWrMGPf/zjyWkwPu/o0aNYv349Ll68CKvVih/96Ef40pe+hNWrV+Ohhx5CV1fXgtVI9Hk8xETkgZGREVRXV+O2224DMD7D5sDAAGpra9Hb24vvfOc7SExMRGlpKV577TW8/vrrOHjwIPR6PX7yk5/g2WefxfPPP++0zkOHDuHFF1/EgQMHkJGRgVdeeQWDg4M4fvw4tFotzp07NznNApEvcA+CyIWtW7di9erVWL16NU6ePInvfOc7kCQJ1dXV+Pu//3tERUUhLS0Nf/M3f4M333wTAHDkyBF8+9vfRnp6OiIjI/Hkk0+iurra6cT0Sy+9hN///vf413/9V2RkZAAA1Go1ent70dLSAlEUkZOTg6ioKJ/UTQRwD4LIpb179+Kuu+6CJEl4++238cgjj+D111+HzWab8gCWjo4OAIDZbEZqaupkW2pqKux2u9Nzj3//+99j69atSE5OnlxWUlKC9vZ2PPnkk+jv78eDDz6IH/7wh9BoNAtQKdFU3IMg8oAoiti4cSMEQUB9fT00Go3T/PoTT7EDAIPBgOvXr0+2tbW1Qa1WIz4+fnLZH/7wB/zud7/D0aNHJ5dpNBr84Ac/QHV1NV555RUcP34cb7zxxgJUR6SMAUHkAVmWUVtbi/7+fixfvhxFRUX41a9+hcHBQVy/fh0HDhzAgw8+CAAoLi7GSy+9hKtXr2JoaAi/+tWvcN9990Gt/myHfdmyZfiXf/kXPPvss3j77bcBAKdOncKFCxcgSRKioqKgVqsnHxJD5As8xETkwne/+93JZ1Snpqbiueeew/Lly/HMM89g9+7dKCgogE6nQ2lpKR566CEAwEMPPYSOjg48/PDDsFqtuPvuu/HMM89MWffKlSvx4osv4m//9m+hVqsxMDCAnTt3oqOjAxEREbj//vtRUlKyoPUS3YzPgyAiIkXcfyUiIkUMCCIiUsSAICIiRQwIIiJSxIAgIiJFDAgiIlLEgCAiIkUMCCIiUsSAICIiRf8fbKyfXAAVBvcAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = sns.distplot(college.Books)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = sns.distplot(college.Expend)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = sns.distplot(college.Terminal)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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SE7vmnlm/fj1tbW2sXbu2+z2ff/55Jk+ezIMPPkheXh6LFy9Gq9Xys5/9jJCQEE+3U4gxacsn5wkN8veqeaDsDidWW4vb5a81H9TExAj2Hqmk7lIbUeGBngpPXINbySI1NbXHcxNXvP76692/63Q61q9f32f9d95555rvHRQUxEsvveROGEKIAai82MSBomq+c/skAv2953bZ9k7HgAanr/W0+YRx4ew7Usm5igaiwnt3RQnPkpuUhRiltn5yHp1Wy503+dY8UO4KDtQTHxPM+YoGFEVRO5xRT5KFEKOQ7XIbfztYxrcyEogMHb1dNBMTIqhvbMd2uU3tUEY9SRZCjEL5fzuD3anwT7dfp3Yow2rCuHA0wLkKWad7uEmyEGKUuVjfys7PS7l9biLx0aP7ZpGgQD3xMSGcl7uihp0kCyFGmbd3nwYU7lk8We1QRsT4+DDqG9u53CzrXAwnSRZCjCLVdc3sPlDGkhuSMRmD1A5nRCSYuqYwqbA2qhzJ6CbJQohR5E8fnUan1fCdzElqhzJijGEBBAX6UWFtUjuUUU2ShRCjRInlMnsOlfPtBeOJCjeoHc6I0Wg0JJhCqLA2yS20w0iShRCjgKIovPbucYIN/uQuHjtXFVckmEJpbbfLLbTDyHse6xRCDNonhys4caGOx1bMJDTIH4DGlg5a2+wDep9rTa3h7RJMXXd9ldc0jamrqpEkyUIIH9fS1skb205wXWIEi+f9Y7bX1jY7h09bB/Re15paw9uFBvkTERJAhbWRWZNi1A5nVJJuKCF83Fu7TtPQ1M4jd88YVTPLDlRCbAiVF5txOGXcYjhIshDCh12ovMS2fRdYPC+ZSUm+eVXgKYmmUOwOJzW2ZrVDGZUkWQjhozrtDl74YwFhwf7cf+dUtcNRXXxMMBqgokZuoR0OkiyE8FF/2HmK0upG1uTOJizYX+1wVBfo70dMpEEezhsmkiyE8EEnLtTx7t/PkXVjMnPTYtUOx2skmEKpsbXQ3uGbd3V5M0kWQviYlrZOfvWnw5gig3hg2TTXFcYQc3QwTgVKLDILradJshDChyiKwqvvHMdqa+HJ784hKFCvdkheJe7r+bDOV0qy8DRJFkL4kI8OlPH3wxV8N2sK0yZEqR2O1wkM8CMiNIBzMmW5x0myEMJHlFgu8+t3jzPruhhW3D72pvRwV5wxiPOVl2SeKA+TZCGED2hrt7Nh80GCDXp+9L056Mbww3euxEUF09TSiaVWnrfwJJnuQwgvpygKL759hEprEz/+XgadnU6sthaX9Xx1nqehiovqGrc4VWojPmZ0rxQ4kiRZCOHlPjpQxv5jVcybGktru/vzPfnqPE9DZQwLxBDgx6mSem6bm6R2OKOGdEMJ4cWKqy7x63ePM3W8kQx5nsItGo2GCePCOVliUzuUUUWShRBeqqWts3uc4qG70tFqZJzCXanjwimrvkxLW6faoYwakiyE8FK/2fIVltpmnrp3LuEhAWqH41NSEyJwKnCmrF7tUEYNSRZCeKF9Ryv528FyVmROYvrEaLXD8TkT4sPQaOBUqSQLT5FkIYSXuVjfysa/HGNyUiT3LJ6sdjg+KShQT1JsqIxbeJBbyaK4uJjc3FyysrLIzc2lpKSkVxmHw8H69evJzMxk8eLF5Ofnd+/bv38/d999N+np6WzYsKFHvZdffpn58+eTk5NDTk4O69evH1qLhPABjS0dWG0tPX78DBFU1zazYfNB7HYn9985FdulNqy2ljF7G+xQTEkxcrq0HqcshuQRbt06u27dOlauXElOTg5bt25l7dq1bN68uUeZbdu2UVZWxq5du2hoaGD58uXMnz+fhIQEEhMTee6559i5cycdHR293n/58uX85Cc/8UyLhPABfS15WlpWga2tjtNl9dw2N5HKi01UXuxam2Gs3gY7FFOSI/nwi1KqaptIMIWqHY7Pc3llUVdXR1FREdnZ2QBkZ2dTVFSEzdbz8m7Hjh2sWLECrVaL0WgkMzOTnTt3ApCcnExaWhp+fvJYhxDX0tzm4MvCalLMYUyR5DBkExO7/g3Plcs8UZ7gMllYLBZiY2PR6XQA6HQ6TCYTFoulV7n4+Pju12azmerqareCeP/991m2bBkPPPAAR44cGUj8QowKiqJwrLgFnU7DrXMS0MhtskOWaArBX6/jrEwq6BGqf9W/5557eOSRR9Dr9Xz66ac8+uij7Nixg8hI979ZFRYWDmOEvRUUFIzo8YaLtEM9foYISssqul+XWtuxNTqYkWKg9mIVtVeVHxelp7SsdEDHGIk61yrf33t46hj9STH5Y6luJS4ygGOnqzlWFNRveT8ttDX3nVR88fPVl6G2w2WyMJvN1NTU4HA40Ol0OBwOrFYrZrO5V7mqqipmzJgB9L7SuJaYmJju3xcuXIjZbObs2bPMmzfP7Uakp6cTEDAy96EXFBSQkZExIscaTtIOdVltLSRf6rpab2rp4MPDp4kK8+OmjOv6vKoICQkhOSl5QMcYiTp9lS8tK+33PTxxDFcCDMGUWDuICAuiqNhGZYO234ca50w2YTKm9truq5+vq13djvb29gF/yXbZDRUVFUVaWhrbt28HYPv27aSlpWE0GnuUW7p0Kfn5+TidTmw2G7t37yYrK8tlADU1Nd2/nzx5ksrKSsaPHz+gRgjhy/Yfq0JRFGakGKT7ycNMkQbsDif1l9vVDsXnudUN9fTTT5OXl8emTZsICwvrvv111apVrFmzhunTp5OTk8OxY8dYsmQJAKtXryYxMRGAQ4cO8aMf/YimpiYUReH999/nueeeY9GiRbzwwgucOHECrVaLXq/n+eef73G1IcRoVl7TyPnKS9wwLY7gwDa1wxl1TJFd3U8X61uICg9UORrf5laySE1N7fHcxBWvv/569+86ne6az0jMnTuXvXv39rnv6ucuhBgrHE4ne49WEh7iz+xJMVRUlqsd0qgTERqA3k+Ltb6FKSlG1xXENckT3EKo5NjZWhoa27lp5jh0OjkVh4NGoyEmwoC1vlXtUHyefEKFUEH95TYOnawhxRxGijlM7XBGNVNkELUNrTjkSe4hkWQhhAre+fs5nE6Fm2a6vmNQDI3JaMDhVLBdljGhoZBkIcQIO1fRwOdfWZh5XYxMPT4CYr4xyC0GT5KFECNIURTeeO8EIUF65kwxqR3OmBAe7I+/XivjFkMkyUKIEXTwZA1fna8lZ1EqAXqd2uGMCRqNBlNkEFa5shgSSRZCjBCHw8mb204wLiaYm2ePUzucMcUUaaCuoQ2Hw6l2KD5LkoUQI2TXl6VUWJv45+xp+MmtsiMqJjIIp6JQe0kGuQdLPrFCjIC2djt/3HWaaROiuGFanNrhjDkxEQYAahtk3GKwJFkIMQK27jtPQ2M7998xVeZ/UkHY14PcFyVZDJokCyGG2eXmDt7dc44bpsWRNl6mnFBD15PcQXL77BBIshBimP3l47O0ttu57440tUMZ02IiDNRdapMnuQdJkoUQw6i2oZXt+y/wrYxEkuNkWg81xUR2PcldL09yD4okCyGG0Vu7TqMo8L2sKWqHMubFRHYNcsu4xeCovqyqEL6usaWD1jZ7r+2W2mY+OlDK7XOTgK7V8a5o73SMWHyiS0RI13TlFxtakQ7BgZNkIcQQtbbZOXza2mv7zs9L8NNpSYwN6bV/crL7a8wLz9BoNESHG2SQe5CkG0qIYWC1tXC+8hKzroshKFCvdjjiazGRBmob2nAqMsg9UJIshBgGXxRaCPTXMWuSLBHsTWIiutbkbmiUNbkHSpKFEB5WYW2k3NpExpRY/GWyQK8ig9yDJ8lCCA9SFIXPv6omxKAnPTVK7XDEVSJDA9FpNVyU6coHTJKFEB50vvIS1voWrp8aK5MFeiGtVkNUuIHaBhnkHij5NAvhIQ6nwheFFoxhgUxJkWk9vJUp0sDF+lYUGeQeEEkWQnjIyeI6LjV1MD/djFYmC/RaMZEGOuxOLjV3qB2KT5FkIYQHdNgdHCiqwRwdTLI5VO1wRD+uTFcu4xYDI8lCCA84duYire12Fkw3yxTkXs4YHohWq5GH8wZIkoUQQ3SpqZ0jZy4yYVw4cVHBaocjXNBptUSFB8rtswMkyUKIIfrr38/hcCjMn25WOxThppgIGeQeKEkWQgzBhcpL7D9WxfSJ0USEBKgdjnBTTGQQ7Z0OLssgt9vcShbFxcXk5uaSlZVFbm4uJSUlvco4HA7Wr19PZmYmixcvJj8/v3vf/v37ufvuu0lPT2fDhg1u1xPCmymKwu/eKyTYoOf6tFi1wxEDYIqQJ7kHyq1ksW7dOlauXMmHH37IypUrWbt2ba8y27Zto6ysjF27dvH222/z8ssvU1FRAUBiYiLPPfccDz744IDqCeHNvjxRzfFzteTcnEqAv0zr4UuiwgPRamSQeyBcJou6ujqKiorIzs4GIDs7m6KiImw2W49yO3bsYMWKFWi1WoxGI5mZmezcuROA5ORk0tLS8PPrPSN6f/WE8FaddgdvbjtBYmwIt8wZp3Y4YoB0Oi3G8ECscvus21yuZ2GxWIiNjUWn6/rmpNPpMJlMWCwWjEZjj3Lx8fHdr81mM9XV1S4DGGy9byosLBxQ+aEqKCgY0eMNF2nH4O07cZmq2mbuvTUaq7WG0rKBXQ2Pi9JTWlbaa3tf2/orP5hjeLLOQNvhyWMMtY5B76C6ro2S0hLM4Q7Kixv6LCfnSZdRsfhReno6AQEjM7hYUFBARkbGiBxrOEk7Bs9a38K+/I+ZP91M7rJ5WG0tJF8aWDdUSEgIyUnJPbaVlpX22tZf+cEcw9N1BtoOTx3DE3UaO2spv1iJMdqMOc6MyZjaq8xoPU/a29sH/CXbZTeU2WympqYGh6NrGUiHw4HVasVsNvcqV1VV1f3aYrEQFxfnMoDB1hNCLb97r+skeygnXeVIxFDERAYBSFeUm1wmi6ioKNLS0ti+fTsA27dvJy0trUcXFMDSpUvJz8/H6XRis9nYvXs3WVlZLgMYbD0h1HD4lJXPjlvIzZyE6es/NsI3dQ1yy7Qf7nKrG+rpp58mLy+PTZs2ERYW1n3766pVq1izZg3Tp08nJyeHY8eOsWTJEgBWr15NYmIiAIcOHeJHP/oRTU1NKIrC+++/z3PPPceiRYv6rSeEN+nodPCbLceJjw7mf9zau8tC+Ba/rwe55Y4o97iVLFJTU/t8/uH111/v/l2n07F+/fo+68+dO5e9e/f2ua+/ekJ4k/y/naXyYjPrH56P3k9ulR0NYiKCuFB1SZ7kdoM8wS2EG8qqL/OXj89wa0YCcyab1A5HeEhMpIH2Dgd1l9rUDsXrSbIQwgWnU+GV/GMYAvQ8dJcMao8mV8adSiyXVY7E+42KW2eF8KTGlg5a2+zdr/9eUM7JEhsPLptGe4cDq61nH3d7p2OkQxQeEv31k9zFVZfUDsXrSbIQ4iqtbXYOn7YC0NTaydu7z5BgCiHAX9e9/ZsmJ0eOdIjCQ3Q6LdERgRRXyZWFK9INJcQ1KIrC3wvKcSoKt85JkEWNRqlYYxAllss4nDLI3R9JFkJcw+myekqrG7kx3Uy4TD8+asUau6YrL69pVDsUrybJQog+NLd2sv9oFeaoIGZMjFY7HDGMYo1dqxueLq1XORLvJslCiKsoisInRyqwO5zcNjdJup9GufAQf4IC/ThbLsmiP5IshLjKlyeqKa66zA3T4ogIle6n0U6j0TA+PlyuLFyQZCHEN9gut/GHD08Rawxi5qQYtcMRI2S8OYyy6su0tdtdFx6jJFkI8TVFUdiYf4xOu5Pbr09EK91PY8aEceE4FThX0feaFkKShRDd9hSUc6Comv/5rYlEhgaqHY4YQePjwwE4UybJ4lokWQgB1F1q5Td//YppE6K4/foktcMRIyws2B+TMYgzZTJucS2SLMSYpygKL/35KHanwprcWdL9NEZNTorkjNwRdU2SLMSY99GBMg6fsvLPd04lPjpE7XCESiYlRXCxvpX6yzIDbV8kWYgxzWpr4bdbC5kxMZo7FoxXOxyhoklJXXN8nZauqD5JshBjVlf30xFAYU3ubLRa6X4ay1ITIvDTaThZbFM7FK8kyUKMWR98XsKxs7X8y7J0Yo2ynvZYF6DXcV1iJNOg4PYAABX/SURBVCcu1KkdileSZCHGpOq6Zt7cdoJZk2JYemOy2uEILzFtQhTnKhrk4bw+SLIQY47TqfDS20fRaDQ8/p1ZMveT6DZtQhQOpyLjFn2QZCHGnA8+K+ar87U8lJPevaymEABpKUY0GqQrqg+SLMSYYqlt5s33i5gzxcTiefLwnegp2KBnfHy4JIs+SLIQY4bTqfDi20fQaTU8vkK6n0Tfpk2I4lRpPZ12p9qheBVJFmLMeG/fBU5cqOPh5dOJjjCoHY7wUtPGR9HR6eB8pcwT9U2SLMSYUF7TyOYdRcybGsdtcxPVDkd4sakTjAAUSVdUD5IsxKjncDj51Z8OE+iv47EVM6X7SfQrMjSQcTHBnLggD+d9kyQLMer9Zc9ZzpQ18IO7ZxIZJlOPC9emTYimqLgOp6KoHYrX8FM7ACGG09EzVt768DTXT41lcnIkVluLyzrtnY4RiEx4s2kTjOz6spSLl+ThvCvcShbFxcXk5eXR0NBAREQEGzZsICUlpUcZh8PBs88+y759+9BoNDz88MOsWLHC5b6XX36ZP/7xj5hMJgDmzJnDunXrPNhEMVa1tdt5Jf8YhgA/ZkyM5vBpq1v1JidHDnNkwttNmxANQElNu8qReA+3ksW6detYuXIlOTk5bN26lbVr17J58+YeZbZt20ZZWRm7du2ioaGB5cuXM3/+fBISEvrdB7B8+XJ+8pOfeL51Ykx7Y9sJrLYW7ro5lUB/uYgW7os1BmGOCua8RaYrv8LlmEVdXR1FRUVkZ2cDkJ2dTVFRETZbz8GfHTt2sGLFCrRaLUajkczMTHbu3OlynxDD4UBRNR98XkLWjckkmGSNCjFwc6aYKK5pp0O6JQE3riwsFguxsbHodDoAdDodJpMJi8WC0WjsUS4+Pr77tdlsprq62uU+gPfff5/9+/cTExPD448/zuzZswfUiMLCwgGVH6qCgoIRPd5wGa3taGi28+sPrMRF6rlxSjCHikoH9H7jovSUlrlfZ6Dl+6tzrffx5DE8WWeg7fDkMTxZxxzuoLy453MV4X6tdDoUtuz6gtQ4378xYqjnu+rX5vfccw+PPPIIer2eTz/9lEcffZQdO3YQGel+v3F6ejoBAQHDGOU/FBQUkJGRMSLHGk6jtR2ddic/3bQfNFrWP3IzflotF5v0A3rPkJAQkpPcn4l2oOWvVae0rPSa7+OpY3i6zkDb4aljeLqOOc6EyZjaY9u0dDtv73ufRkc4GRnpAzq+t7n6PGlvbx/wl2yX3VBms5mamhocjq5LMYfDgdVqxWw29ypXVVXV/dpisRAXF+dyX0xMDHp918m8cOFCzGYzZ8+eHVAjhLji/7xfxOnSen6YO1uWSBVDEhjgR7IpgIJTNWqH4hVcJouoqCjS0tLYvn07ANu3byctLa1HFxTA0qVLyc/Px+l0YrPZ2L17N1lZWS731dT84z/i5MmTVFZWMn68LG8pBu6z41Vs3XueZYsmsHBmvOsKQrhwXXwg5TVNbt1yPdq51Q319NNPk5eXx6ZNmwgLC2PDhg0ArFq1ijVr1jB9+nRycnI4duwYS5YsAWD16tUkJnZNq9DfvhdeeIETJ06g1WrR6/U8//zzxMTEeLyhYnQ7X9HAC28dZnJSJP+SPU3tcMQoMdEcyIdcouC0lW/PT1E7HFW5lSxSU1PJz8/vtf3111/v/l2n07F+/fo+6/e370riEWKw6i618swbXxIa5M+//8s89H4yMYHwjOgwP0yRBgpO1oz5ZCFnlfBpHXYnz7zxJS1tnax98AaZzkN4lEajIWNKLMfPXRzzU5ZLshA+q9Pu5C/7bRRXXuKpe+cyPj5c7ZDEKDRnionWdgcnS8b2LLSSLIRPsjuc/PL3hzhT1cb/c/cMrp8ap3ZIYpSaeV0MfjotX56odl14FJNkIXyOw+Hkv/54mM+/spA1J5w7Fsjdc2L4GAL8yJhiYv/RShzOsTsLrSQL4VM67U5eeOswe49W8i/ZU5k/JVTtkMQYcMucBGyX2yk8X6t2KKqRZCF8RnNrJ+t/+zl7j1Ty/TvSuPtb16kdkhgj5k2LwxCg45PDFWqHohpJFsIn1Da0krdxP4Xn63jintmsuH2S2iGJMSRAr2P+9Hg+O141ZicWlGQhvN7JYhs/fnEvNbYW1j10I7dfn6R2SGIMumV2As1t9jE7/YckC+G1FEXhvX3n+emm/QTodWx47CZmTzapHZYYo2ZeF01ESACfHK5UOxRVqD7rrBi7Gls6aG3re9nKlrZONn9wkoNFNcy6LoYH75pGVIRhhCMUY4Xd4exz/ic/Q0SP7RlTTHxypJJSy2WM4YGEBvmPZJiqkmQhVNPaZu9zqdOq2iZ2HyijqbWTG9PjmDPZxKnSembodb2Sy9Un89VkPW3hjvZOB8fP9b7TqbSsguRLuu7XEaEB2B1O3v37Ob6XNUWShRBqcDidHCqqoeCUldBgf+6+dSJxUcHd+/s6oa8+ma8m62kLT4o1BhEe4k/h+VoUZWw9cyHJQniFukut7D5YTm1DK1OSI1k0axz++msnASHUoNFomHVdDJ8cqeRMWT2x3/gyM9rJALdQlVNROHzayp//dpbm1k6+PT+F269PkkQhvNaUFCOGAD8++HxgS736OrmyEKqx1Dbz7p5z1NhamDAunFvnJGAIkI+k8G5+Oi0zJkbz5YlqSiyXSTGHqR3SiJArCzHiHE6Fd/ec4+nffkFDUzuL5yWx9MZkSRTCZ6SnRuGv1/LunrGzBLScnWJElVou8+LbRzhb3sDsSTHMnBRDcKBe7bCEGJBAfz9unpXAnoJy7v12GqbIILVDGnZyZSFGRKfdwVsfnuKJ//o7NbYWnro3g9X/NFMShfBZi29IQgHe3XNO7VBGhFxZiGF37MxFXn33OJUXm7h1TgIP5aQTHhLQ7/MRQni76HADWTck88FnxWRen8TExAi1QxpWcmUhhk3dpVZ++ftD/L+//gynU2H9qvn8+HsZhIcEqB2aEB7x/TunEhEawMv5R3E4Rveyq3JlITyupa2Td/ec46+fnMfpVPjuksn8023Xye2wYtQJMeh5+H/M4Bf/5yBb954f1dPmS7IQHtPWYWfXF6Xkf3yWhsZ2bp41ju/fOZVY4+gf/BNj14LpZm6YFscfPjzNghnxPWYdGE2kG0oMWXNrJ+98fJZVz+3m9a2FJJhC+M81i3jqvrmSKMSop9FoeOTuGei0Gl744+FROx+ZXFmIQbtQeYkdnxXzyeEK2joczJoUQ27mJNJTo9UOTYgRFR1h4PHvzOKXvz/E85sP8W//fD063ej6Li7JQgxIja2FfUcr2Xe0kguVl/D303Lz7ARuzUjA/PXlt7t3OY3Wb2BibFo0axyNLR28+s5xXvrzUX6YOxutVqN2WB4jyUL0q9Pu5HSpjcOnrRScsnKh8hIAk5IiWJWTzrfmJhIa5I/V1tLndOP9kRlhxWhzx4LxXG7u4A87TxGg17Fq+XT0fqPjCkOShcqutQCQoijYHf+YAlmjAZ1WQ5BBP2xz6DucCpbaJkqrGzlbVs+p0nrOltXTYXei1WpISzFy/51TuWnm6B3EE2KocjMn0dZu55095zhTXs+PV2aQGBuqdlhDJslCBc2tnVRebKKqtplz5fWcKWugua2T5tZO2trtdNiddNp737Ot0XRNM2AI0BFs0BMcqCckyJ+QoK4EEmLQExSoJzjQjyCDHn8/LXo/LX46LQrgdCjYnU5a2uwUnW3iQsMZ6i61Ya1v4WJ9K1UXm+j4+rh+Og2p4yJYuiCFaeOjmHldDMEGedpaCFc0Gg3/nD2NKSlGXnr7KE/81yfc9+00ls5PJtDfd//kuhV5cXExeXl5NDQ0EBERwYYNG0hJSelRxuFw8Oyzz7Jv3z40Gg0PP/wwK1asGNI+X9fS1klZTSOllkbKai5TVt1IeU0jdZfaepQLCvQj+OsrBlNkEHo/Lf5+WnQ6LZqvuzwVpWvpx4iQADrsTlraOmltt3OxvoUSi53m1q7XA9NAsEGPKdKAKTKIWZNiSI4LI9kcijEsEMc3rmyaW7uS2bXI+IMQPd2YbmZSUiQv/ukIv3uvkD/vPs3S+SncsWA80T64RLBbyWLdunWsXLmSnJwctm7dytq1a9m8eXOPMtu2baOsrIxdu3bR0NDA8uXLmT9/PgkJCYPe5+067U4aGtupb2yjxtbS/VN1sYkKayO2y+3dZf31OhJjQ5gxMZqkuDDGxYQQHxOMTqOh8EKd28ecnBzJ6dL6Pvc5nQoddgcdnU46Oh04nAoOh5Nkcxh6nRatVoNWqyHQ34/mRhvjk669wFBLm50TA4xLCNGTMSyQp1fdyIkLdby37wJ/+fgs+X87S1JcKDMmRpM+IZpxphDM0cEEePlDqy6TRV1dHUVFRbz55psAZGdn88wzz2Cz2TAajd3lduzYwYoVK9BqtRiNRjIzM9m5cycPPfTQoPe5cmVZw46OjgE3vLm1k0+PV9Fpd6KgoChd3TROpevH4VCw253YnU7aO5y0d9jp6HRQ23CZP3zyMS3tHTS39v4mH2zQE2cM4sZpMZijQjBHBzEuJoSocEOfd0bUNbSixf1v5Q575zXLa7Xg568hyF8H/OODlxwb1D0wDdDUDJVVVlrt1+5WmjAu3GNxeapOX+X9/TT9vodacQ2mTn9tGYl2DKbOSPyfqPl/2F9b7J0dtLe79wf+uoRQfvzdmVysv45DJ62cLKnjy68q2X+krLtMeEgAocF6QgL9CTbo8ddr8ffXEeCnQ6fToNNo0Oq0aDVdXV3+ei0LZ4wjKNC9rq329n98eb3yN3MgS8O6PIrFYiE2NhadrusfRafTYTKZsFgsPZKFxWIhPj6++7XZbKa6unpI+1zp7OzqFjlz5oxb5a8WP6AxWr+vf2IGUKcJOpqoqbRSU3ntUlEDGK++dLFhQOWvVScqJRho8NhxPBXXQMt7uh2eimswdfpry0i0YzB1RvNnC/pvi6WiAUvFwOICSAyDxBkBLJlhcqO04+ufvl04d8rt4xYWFvba1tnZSWBgoFv1fXe0BQgODmbSpEno9Xo0mtFzP7MQQgwnRVHo7OwkONj9b8wuk4XZbKampgaHw4FOp8PhcGC1WjGbzb3KVVVVMWPGDKDnFcNg97mi1WoJDfX9W9KEEGKkuXtFcYXLp0WioqJIS0tj+/btAGzfvp20tLQeXVAAS5cuJT8/H6fTic1mY/fu3WRlZQ1pnxBCCO+gUdwY4Th//jx5eXlcvnyZsLAwNmzYwIQJE1i1ahVr1qxh+vTpOBwOfvazn/Hpp58CsGrVKnJzcwEGvU8IIYR3cCtZCCGEGNtGx6QlQgghhpUkCyGEEC5JshBCCOGSJAshhBAuSbJwU3FxMbm5uWRlZZGbm0tJSYnaIbmlvr6eVatWkZWVxbJly3jsscew2WwAHD16lLvuuousrCweeOAB6urcnwtKTa+88gqTJ0/ufnLfF9vR3t7OunXrWLJkCcuWLeM//uM/AN/7nO3Zs4fly5eTk5PDXXfdxa5duwDvb8eGDRu47bbbenyOoP+4vbVNfbWlv/MeBnnOKMIt9913n7JlyxZFURRly5Ytyn333adyRO6pr69Xvvjii+7Xv/jFL5Sf/vSnisPhUDIzM5WDBw8qiqIoGzduVPLy8tQK022FhYXKgw8+qHzrW99STp8+7bPteOaZZ5TnnntOcTqdiqIoysWLFxVF8a3PmdPpVObOnaucPn1aURRFOXnypDJr1izF4XB4fTsOHjyoVFVVdX+Orugvbm9tU19tudZ5ryjKoM8ZSRZuqK2tVTIyMhS73a4oiqLY7XYlIyNDqaurUzmygdu5c6dy//33K8eOHVPuvPPO7u11dXXKrFmzVIzMtfb2duU73/mOUl5e3n1i+GI7mpqalIyMDKWpqanHdl/7nDmdTmXevHnKoUOHFEVRlAMHDihLlizxqXZ88w9sf3H7QpuuTnzfdOW8VxRl0OeMT88NNVLcnUzR2zmdTt566y1uu+22XtOqGI1GnE5n95ol3ujFF1/krrvu6jF9vS+2o7y8nIiICF555RW+/PJLgoOD+eEPf0hgYKBPfc40Gg2/+tWvePTRRwkKCqK5uZnf/OY3Pnu+9Be3oig+2Sboed7D4M8ZGbMYQ5555hmCgoK499571Q5lwI4cOUJhYSErV65UO5QhczgclJeXM3XqVN59913+9V//lccff5yWlha1QxsQu93Or3/9azZt2sSePXt49dVXeeKJJ3yuHaOdp857ubJwg7uTKXqzDRs2UFpaymuvvYZWq+2ewPEKm82GVqv12m/jBw8e5Pz589x+++0AVFdX8+CDD3Lffff5VDug6/Pk5+dHdnY2ADNnziQyMpLAwECf+pydPHkSq9VKRkYGABkZGRgMBgICAnyqHVf0d54riuKTbbr6vAcGfe7LlYUb3J1M0Vu98MILFBYWsnHjRvz9uybtT09Pp62tjUOHDgHwpz/9iaVLl6oZZr8efvhh9u/fz8cff8zHH39MXFwcv/vd73jooYd8qh3Qddl/ww03dM+HVlxcTF1dHSkpKT71OYuLi6O6upoLFy4AXXPI1dXVkZyc7FPtuKK/89wX/wb0dd7D4M99mRvKTdeaTNHbnT17luzsbFJSUrqnJE5ISGDjxo0cPnyYdevW0d7ezrhx4/jlL39JdHS0yhG757bbbuO1115j0qRJPtmO8vJy/u3f/o2Ghgb8/Px44oknuOWWW3zuc/bee+/x+uuvd68ns2bNGjIzM72+Hc8++yy7du2itraWyMhIIiIieP/99/uN21vb1FdbfvWrX13zvAcGdc5IshBCCOGSdEMJIYRwSZKFEEIIlyRZCCGEcEmShRBCCJckWQghhHBJkoUQHnLfffeRn5+vdhhCDAt5gluIAbrtttuora1Fp9NhMBi4+eabu6cYv5aKigpuv/12goKCADAYDEyfPp3vf//7LFy4cCTCFmJI5MpCiEF47bXXOHLkCH/9618pLCzk1VdfdavewYMHOXLkCFu3bmXBggU89thjvPvuu8McrRBDJ8lCiCGIjY1l0aJFnD17FoDKykruueceZs+ezQMPPNBjwZlviomJ4f777+exxx7jP//zP3E6nSMZthADJslCiCGwWCzs3buXtLQ0oGvOoJ///Od8/vnndHZ28sYbb/Rbf8mSJdTV1VFcXDwS4QoxaJIshBiE1atXM3fuXFauXMn111/PI488AsDdd9/N+PHjCQwMZOnSpZw8ebLf9zGZTAA0NDQMe8xCDIUMcAsxCBs3bmTBggW9tsfExHT/bjAYXK7tUFNTA+DVU6oLAXJlIYSqPvroI6Kiohg/frzaoQjRL7myEEIFtbW17Ny5k1deeYV///d/716YRghvJclCiBF0/fXXoygKBoOB9PR0XnzxRW6++Wa1wxLCJVnPQgghhEty7SuEEMIlSRZCCCFckmQhhBDCJUkWQgghXJJkIYQQwiVJFkIIIVySZCGEEMIlSRZCCCFckmQhhBDCpf8f9oZcfPpxRYoAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = sns.distplot(college.PhD)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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Unnamed: 0mpgcylindersdisplacementhorsepowerweightaccelerationyearorigin
count392.000000392.000000392.000000392.000000392.000000392.000000392.000000392.000000392.000000
mean198.52040823.4459185.471939194.411990104.4693882977.58418415.54132775.9795921.576531
std114.4380677.8050071.705783104.64400438.491160849.4025602.7588643.6837370.805518
min1.0000009.0000003.00000068.00000046.0000001613.0000008.00000070.0000001.000000
25%99.75000017.0000004.000000105.00000075.0000002225.25000013.77500073.0000001.000000
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75%296.25000029.0000008.000000275.750000126.0000003614.75000017.02500079.0000002.000000
max397.00000046.6000008.000000455.000000230.0000005140.00000024.80000082.0000003.000000
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" + }, + "metadata": {}, + "execution_count": 4 + } + ], + "source": [ + "auto = pd.read_csv(\"./../../datasets/Auto.csv\")\n", + "# auto.set_index(\"name\", inplace=True)\n", + "auto.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "auto.drop(range(10,66), inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": " Unnamed: 0 mpg cylinders displacement horsepower \\\ncount 336.000000 336.000000 336.000000 336.000000 336.000000 \nmean 225.089286 24.041071 5.407738 189.672619 102.261905 \nstd 101.406281 7.889493 1.686770 101.903056 36.666913 \nmin 1.000000 11.000000 3.000000 68.000000 46.000000 \n25% 142.750000 17.675000 4.000000 100.250000 75.000000 \n50% 226.500000 23.100000 4.000000 145.500000 92.000000 \n75% 310.250000 30.000000 6.000000 258.500000 120.000000 \nmax 397.000000 46.600000 8.000000 455.000000 230.000000 \n\n weight acceleration year origin \ncount 336.000000 336.000000 336.000000 336.000000 \nmean 2959.779762 15.656845 76.836310 1.601190 \nstd 824.796492 2.697807 3.256221 0.818735 \nmin 1649.000000 8.500000 70.000000 1.000000 \n25% 2219.750000 14.000000 74.000000 1.000000 \n50% 2803.500000 15.500000 77.000000 1.000000 \n75% 3571.000000 17.200000 80.000000 2.000000 \nmax 4997.000000 24.800000 82.000000 3.000000 ", + "text/html": "
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
Unnamed: 0mpgcylindersdisplacementhorsepowerweightaccelerationyearorigin
count336.000000336.000000336.000000336.000000336.000000336.000000336.000000336.000000336.000000
mean225.08928624.0410715.407738189.672619102.2619052959.77976215.65684576.8363101.601190
std101.4062817.8894931.686770101.90305636.666913824.7964922.6978073.2562210.818735
min1.00000011.0000003.00000068.00000046.0000001649.0000008.50000070.0000001.000000
25%142.75000017.6750004.000000100.25000075.0000002219.75000014.00000074.0000001.000000
50%226.50000023.1000004.000000145.50000092.0000002803.50000015.50000077.0000001.000000
75%310.25000030.0000006.000000258.500000120.0000003571.00000017.20000080.0000002.000000
max397.00000046.6000008.000000455.000000230.0000004997.00000024.80000082.0000003.000000
\n
" + }, + "metadata": {}, + "execution_count": 6 + } + ], + "source": [ + "auto.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "output_type": "error", + "ename": "SyntaxError", + "evalue": "invalid syntax (, line 1)", + "traceback": [ + "\u001b[0;36m File \u001b[0;32m\"\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m range(Auto[,5])\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n" + ] + } + ], + "source": [ + "range(Auto[,5])" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "
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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n", + "image/png": 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Unnamed: 01.0000000.622918-0.407201-0.434889-0.468482-0.3961900.3054130.9959180.205620
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" + ], + "text/plain": [ + " Unnamed: 0 mpg cylinders displacement horsepower \\\n", + "Unnamed: 0 1.000000 0.622918 -0.407201 -0.434889 -0.468482 \n", + "mpg 0.622918 1.000000 -0.763358 -0.795919 -0.772484 \n", + "cylinders -0.407201 -0.763358 1.000000 0.947652 0.834880 \n", + "displacement -0.434889 -0.795919 0.947652 1.000000 0.898653 \n", + "horsepower -0.468482 -0.772484 0.834880 0.898653 1.000000 \n", + "weight -0.396190 -0.835404 0.892985 0.939702 0.865636 \n", + "acceleration 0.305413 0.397465 -0.466391 -0.499334 -0.686725 \n", + "year 0.995918 0.618078 -0.389445 -0.414558 -0.459743 \n", + "origin 0.205620 0.546191 -0.556291 -0.608198 -0.451026 \n", + "\n", + " weight acceleration year origin \n", + "Unnamed: 0 -0.396190 0.305413 0.995918 0.205620 \n", + "mpg -0.835404 0.397465 0.618078 0.546191 \n", + "cylinders 0.892985 -0.466391 -0.389445 -0.556291 \n", + "displacement 0.939702 -0.499334 -0.414558 -0.608198 \n", + "horsepower 0.865636 -0.686725 -0.459743 -0.451026 \n", + "weight 1.000000 -0.378763 -0.381168 -0.585219 \n", + "acceleration -0.378763 1.000000 0.307771 0.189902 \n", + "year -0.381168 0.307771 1.000000 0.182583 \n", + "origin -0.585219 0.189902 0.182583 1.000000 " + ] + }, + "execution_count": 63, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "auto.corr()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ax = sns.violinplot(x=\"Private\", y=\"Outstate\", data=college)" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = sns.boxplot(x=\"Private\", y=\"Outstate\", data=college)" + ] + }, + { + "cell_type": "code", + "execution_count": 85, + "metadata": {}, + "outputs": [], + "source": [ + "sep =pd.cut(college.Top10perc, pd.interval_range(start=0, end=100, periods=2), labels=[\"Not elite\", \"Elite\"])\n", + "college[\"Elite\"] = sep " + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = sns.violinplot(x=\"Elite\", y=\"Outstate\", data=college)" + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Index(['Private', 'Apps', 'Accept', 'Enroll', 'Top10perc', 'Top25perc',\n", + "# 'F.Undergrad', 'P.Undergrad', 'Outstate', 'Room.Board', 'Books',\n", + "# 'Personal', 'PhD', 'Terminal', 'S.F.Ratio', 'perc.alumni', 'Expend',\n", + "# 'Grad.Rate'],\n", + "# dtype='object')\n", + "ax = sns.distplot(college.Apps)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 94, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Index(['Private', 'Apps', 'Accept', 'Enroll', 'Top10perc', 'Top25perc',\n", + "# 'F.Undergrad', 'P.Undergrad', 'Outstate', 'Room.Board', 'Books',\n", + "# 'Personal', 'PhD', 'Terminal', 'S.F.Ratio', 'perc.alumni', 'Expend',\n", + "# 'Grad.Rate'],\n", + "sns.distplot(college.Accept)\n", + "sns.distplot(college.Enroll)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = sns.distplot(college.Top10perc)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 96, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = sns.distplot(college[\"F.Undergrad\"])\n" + ] + }, + { + "cell_type": "code", + "execution_count": 97, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = sns.distplot(college[\"P.Undergrad\"])\n" + ] + }, + { + "cell_type": "code", + "execution_count": 98, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = sns.distplot(college.Books)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ax = sns.distplot(college.Expend)\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.2-final" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} \ No newline at end of file diff --git a/ISLR/notebooks/ch2-9R.ipynb b/ISLR/notebooks/ch2-9R.ipynb new file mode 100644 index 0000000..4015a3d --- /dev/null +++ b/ISLR/notebooks/ch2-9R.ipynb @@ -0,0 +1,593 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "library(ISLR)\n", + "library(repr)\n", + "options(repr.plot.width=16, repr.plot.height=16)" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\n", + "
A data.frame: 6 × 9
mpgcylindersdisplacementhorsepowerweightaccelerationyearoriginname
<dbl><dbl><dbl><dbl><dbl><dbl><dbl><dbl><fct>
1188307130350412.0701chevrolet chevelle malibu
2158350165369311.5701buick skylark 320
3188318150343611.0701plymouth satellite
4168304150343312.0701amc rebel sst
5178302140344910.5701ford torino
6158429198434110.0701ford galaxie 500
\n" + ], + "text/latex": [ + "A data.frame: 6 × 9\n", + "\\begin{tabular}{r|lllllllll}\n", + " & mpg & cylinders & displacement & horsepower & weight & acceleration & year & origin & name\\\\\n", + " & & & & & & & & & \\\\\n", + "\\hline\n", + "\t1 & 18 & 8 & 307 & 130 & 3504 & 12.0 & 70 & 1 & chevrolet chevelle malibu\\\\\n", + "\t2 & 15 & 8 & 350 & 165 & 3693 & 11.5 & 70 & 1 & buick skylark 320 \\\\\n", + "\t3 & 18 & 8 & 318 & 150 & 3436 & 11.0 & 70 & 1 & plymouth satellite \\\\\n", + "\t4 & 16 & 8 & 304 & 150 & 3433 & 12.0 & 70 & 1 & amc rebel sst \\\\\n", + "\t5 & 17 & 8 & 302 & 140 & 3449 & 10.5 & 70 & 1 & ford torino \\\\\n", + "\t6 & 15 & 8 & 429 & 198 & 4341 & 10.0 & 70 & 1 & ford galaxie 500 \\\\\n", + "\\end{tabular}\n" + ], + "text/markdown": [ + "\n", + "A data.frame: 6 × 9\n", + "\n", + "| | mpg <dbl> | cylinders <dbl> | displacement <dbl> | horsepower <dbl> | weight <dbl> | acceleration <dbl> | year <dbl> | origin <dbl> | name <fct> |\n", + "|---|---|---|---|---|---|---|---|---|---|\n", + "| 1 | 18 | 8 | 307 | 130 | 3504 | 12.0 | 70 | 1 | chevrolet chevelle malibu |\n", + "| 2 | 15 | 8 | 350 | 165 | 3693 | 11.5 | 70 | 1 | buick skylark 320 |\n", + "| 3 | 18 | 8 | 318 | 150 | 3436 | 11.0 | 70 | 1 | plymouth satellite |\n", + "| 4 | 16 | 8 | 304 | 150 | 3433 | 12.0 | 70 | 1 | amc rebel sst |\n", + "| 5 | 17 | 8 | 302 | 140 | 3449 | 10.5 | 70 | 1 | ford torino |\n", + "| 6 | 15 | 8 | 429 | 198 | 4341 | 10.0 | 70 | 1 | ford galaxie 500 |\n", + "\n" + ], + "text/plain": [ + " mpg cylinders displacement horsepower weight acceleration year origin\n", + "1 18 8 307 130 3504 12.0 70 1 \n", + "2 15 8 350 165 3693 11.5 70 1 \n", + "3 18 8 318 150 3436 11.0 70 1 \n", + "4 16 8 304 150 3433 12.0 70 1 \n", + "5 17 8 302 140 3449 10.5 70 1 \n", + "6 15 8 429 198 4341 10.0 70 1 \n", + " name \n", + "1 chevrolet chevelle malibu\n", + "2 buick skylark 320 \n", + "3 plymouth satellite \n", + "4 amc rebel sst \n", + "5 ford torino \n", + "6 ford galaxie 500 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# rownames(Auto) = Auto[ ,9]\n", + "\n", + "head(Auto)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "
Auto {ISLR}R Documentation
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\n", + "Auto Data Set\n", + "

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Description

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Gas mileage, horsepower, and other information for 392 vehicles.

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Usage

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Auto
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Format

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A data frame with 392 observations on the following 9 variables.\n", + "

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mpg

miles per gallon

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cylinders

Number of cylinders between 4 and 8

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displacement

Engine displacement (cu. inches)

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horsepower

Engine horsepower

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weight

Vehicle weight (lbs.)

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acceleration

Time to accelerate from 0 to 60 mph (sec.)

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year

Model year (modulo 100)

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origin

Origin of car (1. American, 2. European, 3. Japanese)

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name

Vehicle name

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The orginal data contained 408 observations but 16 observations with\n", + "missing values were removed.

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Source

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This dataset was taken from the StatLib library which is maintained at Carnegie Mellon University. The dataset was used in the 1983 American Statistical Association Exposition.\n", + "

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References

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James, G., Witten, D., Hastie, T., and Tibshirani, R. (2013)\n", + "An Introduction to Statistical Learning with applications in R,\n", + "www.StatLearning.com,\n", + "Springer-Verlag, New York\n", + "

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Examples

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\n",
+       "pairs(Auto)\n",
+       "attach(Auto)\n",
+       "hist(mpg)\n",
+       "
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[Package ISLR version 1.2 ]
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European, 3. Japanese)\n", + "\\item[\\code{name}] Vehicle name\n", + "\\end{description}\n", + "\n", + "\n", + "The orginal data contained 408 observations but 16 observations with\n", + "missing values were removed.\n", + "\\end{Format}\n", + "%\n", + "\\begin{Source}\\relax\n", + "This dataset was taken from the StatLib library which is maintained at Carnegie Mellon University. The dataset was used in the 1983 American Statistical Association Exposition.\n", + "\\end{Source}\n", + "%\n", + "\\begin{References}\\relax\n", + "James, G., Witten, D., Hastie, T., and Tibshirani, R. (2013)\n", + "\\emph{An Introduction to Statistical Learning with applications in R},\n", + "\\url{www.StatLearning.com},\n", + "Springer-Verlag, New York\n", + "\\end{References}\n", + "%\n", + "\\begin{Examples}\n", + "\\begin{ExampleCode}\n", + "pairs(Auto)\n", + "attach(Auto)\n", + "hist(mpg)\n", + "\\end{ExampleCode}\n", + "\\end{Examples}" + ], + "text/plain": [ + "Auto package:ISLR R Documentation\n", + "\n", + "_\bA_\bu_\bt_\bo _\bD_\ba_\bt_\ba _\bS_\be_\bt\n", + "\n", + "_\bD_\be_\bs_\bc_\br_\bi_\bp_\bt_\bi_\bo_\bn:\n", + "\n", + " Gas mileage, horsepower, and other information for 392 vehicles.\n", + "\n", + "_\bU_\bs_\ba_\bg_\be:\n", + "\n", + " Auto\n", + " \n", + "_\bF_\bo_\br_\bm_\ba_\bt:\n", + "\n", + " A data frame with 392 observations on the following 9 variables.\n", + "\n", + " ‘mpg’ miles per gallon\n", + "\n", + " ‘cylinders’ Number of cylinders between 4 and 8\n", + "\n", + " ‘displacement’ Engine displacement (cu. inches)\n", + "\n", + " ‘horsepower’ Engine horsepower\n", + "\n", + " ‘weight’ Vehicle weight (lbs.)\n", + "\n", + " ‘acceleration’ Time to accelerate from 0 to 60 mph (sec.)\n", + "\n", + " ‘year’ Model year (modulo 100)\n", + "\n", + " ‘origin’ Origin of car (1. American, 2. European, 3. Japanese)\n", + "\n", + " ‘name’ Vehicle name\n", + "\n", + " The orginal data contained 408 observations but 16 observations\n", + " with missing values were removed.\n", + "\n", + "_\bS_\bo_\bu_\br_\bc_\be:\n", + "\n", + " This dataset was taken from the StatLib library which is\n", + " maintained at Carnegie Mellon University. The dataset was used in\n", + " the 1983 American Statistical Association Exposition.\n", + "\n", + "_\bR_\be_\bf_\be_\br_\be_\bn_\bc_\be_\bs:\n", + "\n", + " James, G., Witten, D., Hastie, T., and Tibshirani, R. (2013) _An\n", + " Introduction to Statistical Learning with applications in R_,\n", + " , Springer-Verlag, New York\n", + "\n", + "_\bE_\bx_\ba_\bm_\bp_\bl_\be_\bs:\n", + "\n", + " pairs(Auto)\n", + " attach(Auto)\n", + " hist(mpg)\n", + " " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "?Auto" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + " mpg cylinders displacement horsepower weight \n", + " Min. : 9.00 Min. :3.000 Min. : 68.0 Min. : 46.0 Min. :1613 \n", + " 1st Qu.:17.00 1st Qu.:4.000 1st Qu.:105.0 1st Qu.: 75.0 1st Qu.:2225 \n", + " Median :22.75 Median :4.000 Median :151.0 Median : 93.5 Median :2804 \n", + " Mean :23.45 Mean :5.472 Mean :194.4 Mean :104.5 Mean :2978 \n", + " 3rd Qu.:29.00 3rd Qu.:8.000 3rd Qu.:275.8 3rd Qu.:126.0 3rd Qu.:3615 \n", + " Max. :46.60 Max. :8.000 Max. :455.0 Max. :230.0 Max. :5140 \n", + " \n", + " acceleration year origin name \n", + " Min. : 8.00 Min. :70.00 Min. :1.000 amc matador : 5 \n", + " 1st Qu.:13.78 1st Qu.:73.00 1st Qu.:1.000 ford pinto : 5 \n", + " Median :15.50 Median :76.00 Median :1.000 toyota corolla : 5 \n", + " Mean :15.54 Mean :75.98 Mean :1.577 amc gremlin : 4 \n", + " 3rd Qu.:17.02 3rd Qu.:79.00 3rd Qu.:2.000 amc hornet : 4 \n", + " Max. :24.80 Max. :82.00 Max. :3.000 chevrolet chevette: 4 \n", + " (Other) :365 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "summary(Auto)" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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48Lpu6GALhdB3xtZY+8+IiTqw3ZIAnjCkgmQY31brTeyjuQ6s2um+BnIIABF6IG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\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EzeN8+zYdJVQzC0W0JQs2/8suY4pvws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\nK+k1GYJ9IBKDAixzUIBzzY4WFbobN0R5PbV69amvjW7KDRsavfc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+ "text/plain": [ + "plot without title" + ] + }, + "metadata": { + "image/png": { + "height": 960, + "width": 960 + }, + "text/plain": { + "height": 960, + "width": 960 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "pairs(Auto[,1:4])" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + " mpg cylinders displacement horsepower weight \n", + " Min. :11.00 Min. :3.000 Min. : 68.0 Min. : 46.0 Min. :1649 \n", + " 1st Qu.:17.68 1st Qu.:4.000 1st Qu.:100.2 1st Qu.: 75.0 1st Qu.:2220 \n", + " Median :23.10 Median :4.000 Median :145.5 Median : 92.0 Median :2804 \n", + " Mean :24.05 Mean :5.408 Mean :189.4 Mean :102.1 Mean :2959 \n", + " 3rd Qu.:30.00 3rd Qu.:6.000 3rd Qu.:258.5 3rd Qu.:120.0 3rd Qu.:3571 \n", + " Max. :46.60 Max. :8.000 Max. :455.0 Max. :230.0 Max. :4997 \n", + " \n", + " acceleration year origin \n", + " Min. : 8.50 Min. :70.00 Min. :1.000 \n", + " 1st Qu.:14.00 1st Qu.:74.00 1st Qu.:1.000 \n", + " Median :15.50 Median :77.00 Median :1.000 \n", + " Mean :15.67 Mean :76.84 Mean :1.601 \n", + " 3rd Qu.:17.20 3rd Qu.:80.00 3rd Qu.:2.000 \n", + " Max. :24.80 Max. :82.00 Max. :3.000 \n", + " \n", + " name \n", + " ford pinto : 5 \n", + " toyota corolla : 5 \n", + " amc matador : 4 \n", + " chevrolet chevette : 4 \n", + " amc hornet : 3 \n", + " chevrolet caprice classic: 3 \n", + " (Other) :312 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "auto2 = Auto[-c(10:65),] \n", + "summary(auto2)" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\t\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\n", + "
A matrix: 8 × 8 of type dbl
mpgcylindersdisplacementhorsepowerweightaccelerationyearorigin
mpg 1.0000000-0.7776175-0.8051269-0.7784268-0.8322442 0.4233285 0.5805410 0.5652088
cylinders-0.7776175 1.0000000 0.9508233 0.8429834 0.8975273-0.5046834-0.3456474-0.5689316
displacement-0.8051269 0.9508233 1.0000000 0.8972570 0.9329944-0.5438005-0.3698552-0.6145351
horsepower-0.7784268 0.8429834 0.8972570 1.0000000 0.8645377-0.6891955-0.4163615-0.4551715
weight-0.8322442 0.8975273 0.9329944 0.8645377 1.0000000-0.4168392-0.3091199-0.5850054
acceleration 0.4233285-0.5046834-0.5438005-0.6891955-0.4168392 1.0000000 0.2903161 0.2127458
year 0.5805410-0.3456474-0.3698552-0.4163615-0.3091199 0.2903161 1.0000000 0.1815277
origin 0.5652088-0.5689316-0.6145351-0.4551715-0.5850054 0.2127458 0.1815277 1.0000000
\n" + ], + "text/latex": [ + "A matrix: 8 × 8 of type dbl\n", + "\\begin{tabular}{r|llllllll}\n", + " & mpg & cylinders & displacement & horsepower & weight & acceleration & year & origin\\\\\n", + "\\hline\n", + "\tmpg & 1.0000000 & -0.7776175 & -0.8051269 & -0.7784268 & -0.8322442 & 0.4233285 & 0.5805410 & 0.5652088\\\\\n", + "\tcylinders & -0.7776175 & 1.0000000 & 0.9508233 & 0.8429834 & 0.8975273 & -0.5046834 & -0.3456474 & -0.5689316\\\\\n", + "\tdisplacement & -0.8051269 & 0.9508233 & 1.0000000 & 0.8972570 & 0.9329944 & -0.5438005 & -0.3698552 & -0.6145351\\\\\n", + "\thorsepower & -0.7784268 & 0.8429834 & 0.8972570 & 1.0000000 & 0.8645377 & -0.6891955 & -0.4163615 & -0.4551715\\\\\n", + "\tweight & -0.8322442 & 0.8975273 & 0.9329944 & 0.8645377 & 1.0000000 & -0.4168392 & -0.3091199 & -0.5850054\\\\\n", + "\tacceleration & 0.4233285 & -0.5046834 & -0.5438005 & -0.6891955 & -0.4168392 & 1.0000000 & 0.2903161 & 0.2127458\\\\\n", + "\tyear & 0.5805410 & -0.3456474 & -0.3698552 & -0.4163615 & -0.3091199 & 0.2903161 & 1.0000000 & 0.1815277\\\\\n", + "\torigin & 0.5652088 & -0.5689316 & -0.6145351 & -0.4551715 & -0.5850054 & 0.2127458 & 0.1815277 & 1.0000000\\\\\n", + "\\end{tabular}\n" + ], + "text/markdown": [ + "\n", + "A matrix: 8 × 8 of type dbl\n", + "\n", + "| | mpg | cylinders | displacement | horsepower | weight | acceleration | year | origin |\n", + "|---|---|---|---|---|---|---|---|---|\n", + "| mpg | 1.0000000 | -0.7776175 | -0.8051269 | -0.7784268 | -0.8322442 | 0.4233285 | 0.5805410 | 0.5652088 |\n", + "| cylinders | -0.7776175 | 1.0000000 | 0.9508233 | 0.8429834 | 0.8975273 | -0.5046834 | -0.3456474 | -0.5689316 |\n", + "| displacement | -0.8051269 | 0.9508233 | 1.0000000 | 0.8972570 | 0.9329944 | -0.5438005 | -0.3698552 | -0.6145351 |\n", + "| horsepower | -0.7784268 | 0.8429834 | 0.8972570 | 1.0000000 | 0.8645377 | -0.6891955 | -0.4163615 | -0.4551715 |\n", + "| weight | -0.8322442 | 0.8975273 | 0.9329944 | 0.8645377 | 1.0000000 | -0.4168392 | -0.3091199 | -0.5850054 |\n", + "| acceleration | 0.4233285 | -0.5046834 | -0.5438005 | -0.6891955 | -0.4168392 | 1.0000000 | 0.2903161 | 0.2127458 |\n", + "| year | 0.5805410 | -0.3456474 | -0.3698552 | -0.4163615 | -0.3091199 | 0.2903161 | 1.0000000 | 0.1815277 |\n", + "| origin | 0.5652088 | -0.5689316 | -0.6145351 | -0.4551715 | -0.5850054 | 0.2127458 | 0.1815277 | 1.0000000 |\n", + "\n" + ], + "text/plain": [ + " mpg cylinders displacement horsepower weight \n", + "mpg 1.0000000 -0.7776175 -0.8051269 -0.7784268 -0.8322442\n", + "cylinders -0.7776175 1.0000000 0.9508233 0.8429834 0.8975273\n", + "displacement -0.8051269 0.9508233 1.0000000 0.8972570 0.9329944\n", + "horsepower -0.7784268 0.8429834 0.8972570 1.0000000 0.8645377\n", + "weight -0.8322442 0.8975273 0.9329944 0.8645377 1.0000000\n", + "acceleration 0.4233285 -0.5046834 -0.5438005 -0.6891955 -0.4168392\n", + "year 0.5805410 -0.3456474 -0.3698552 -0.4163615 -0.3091199\n", + "origin 0.5652088 -0.5689316 -0.6145351 -0.4551715 -0.5850054\n", + " acceleration year origin \n", + "mpg 0.4233285 0.5805410 0.5652088\n", + "cylinders -0.5046834 -0.3456474 -0.5689316\n", + "displacement -0.5438005 -0.3698552 -0.6145351\n", + "horsepower -0.6891955 -0.4163615 -0.4551715\n", + "weight -0.4168392 -0.3091199 -0.5850054\n", + "acceleration 1.0000000 0.2903161 0.2127458\n", + "year 0.2903161 1.0000000 0.1815277\n", + "origin 0.2127458 0.1815277 1.0000000" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "cor(Auto[-c(9)])" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\t\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\n", + "
A matrix: 8 × 8 of type dbl
mpgcylindersdisplacementhorsepowerweightaccelerationyearorigin
mpg 60.918142 -10.3529281 -657.58521 -233.85793 -5517.4407 9.1155144 16.6914766 3.5535101
cylinders -10.352928 2.9096965 169.72195 55.34824 1300.4244 -2.3750522 -2.1719296 -0.7817344
displacement -657.585207 169.721948610950.36755 3614.03374 82929.1001-156.9944354-142.5721332 -51.8007921
horsepower -233.857926 55.3482436 3614.03374 1481.56939 28265.6202 -73.1869670 -59.0364320 -14.1127407
weight-5517.4407041300.424363282929.1001428265.62023721484.7090-976.8152526-967.2284566-400.2660499
acceleration 9.115514 -2.3750522 -156.99444 -73.18697 -976.8153 7.6113312 2.9504619 0.4727882
year 16.691477 -2.1719296 -142.57213 -59.03643 -967.2285 2.9504619 13.5699149 0.5386502
origin 3.553510 -0.7817344 -51.80079 -14.11274 -400.2660 0.4727882 0.5386502 0.6488595
\n" + ], + "text/latex": [ + "A matrix: 8 × 8 of type dbl\n", + "\\begin{tabular}{r|llllllll}\n", + " & mpg & cylinders & displacement & horsepower & weight & acceleration & year & origin\\\\\n", + "\\hline\n", + "\tmpg & 60.918142 & -10.3529281 & -657.58521 & -233.85793 & -5517.4407 & 9.1155144 & 16.6914766 & 3.5535101\\\\\n", + "\tcylinders & -10.352928 & 2.9096965 & 169.72195 & 55.34824 & 1300.4244 & -2.3750522 & -2.1719296 & -0.7817344\\\\\n", + "\tdisplacement & -657.585207 & 169.7219486 & 10950.36755 & 3614.03374 & 82929.1001 & -156.9944354 & -142.5721332 & -51.8007921\\\\\n", + "\thorsepower & -233.857926 & 55.3482436 & 3614.03374 & 1481.56939 & 28265.6202 & -73.1869670 & -59.0364320 & -14.1127407\\\\\n", + "\tweight & -5517.440704 & 1300.4243632 & 82929.10014 & 28265.62023 & 721484.7090 & -976.8152526 & -967.2284566 & -400.2660499\\\\\n", + "\tacceleration & 9.115514 & -2.3750522 & -156.99444 & -73.18697 & -976.8153 & 7.6113312 & 2.9504619 & 0.4727882\\\\\n", + "\tyear & 16.691477 & -2.1719296 & -142.57213 & -59.03643 & -967.2285 & 2.9504619 & 13.5699149 & 0.5386502\\\\\n", + "\torigin & 3.553510 & -0.7817344 & -51.80079 & -14.11274 & -400.2660 & 0.4727882 & 0.5386502 & 0.6488595\\\\\n", + "\\end{tabular}\n" + ], + "text/markdown": [ + "\n", + "A matrix: 8 × 8 of type dbl\n", + "\n", + "| | mpg | cylinders | displacement | horsepower | weight | acceleration | year | origin |\n", + "|---|---|---|---|---|---|---|---|---|\n", + "| mpg | 60.918142 | -10.3529281 | -657.58521 | -233.85793 | -5517.4407 | 9.1155144 | 16.6914766 | 3.5535101 |\n", + "| cylinders | -10.352928 | 2.9096965 | 169.72195 | 55.34824 | 1300.4244 | -2.3750522 | -2.1719296 | -0.7817344 |\n", + "| displacement | -657.585207 | 169.7219486 | 10950.36755 | 3614.03374 | 82929.1001 | -156.9944354 | -142.5721332 | -51.8007921 |\n", + "| horsepower | -233.857926 | 55.3482436 | 3614.03374 | 1481.56939 | 28265.6202 | -73.1869670 | -59.0364320 | -14.1127407 |\n", + "| weight | -5517.440704 | 1300.4243632 | 82929.10014 | 28265.62023 | 721484.7090 | -976.8152526 | -967.2284566 | -400.2660499 |\n", + "| acceleration | 9.115514 | -2.3750522 | -156.99444 | -73.18697 | -976.8153 | 7.6113312 | 2.9504619 | 0.4727882 |\n", + "| year | 16.691477 | -2.1719296 | -142.57213 | -59.03643 | -967.2285 | 2.9504619 | 13.5699149 | 0.5386502 |\n", + "| origin | 3.553510 | -0.7817344 | -51.80079 | -14.11274 | -400.2660 | 0.4727882 | 0.5386502 | 0.6488595 |\n", + "\n" + ], + "text/plain": [ + " mpg cylinders displacement horsepower weight \n", + "mpg 60.918142 -10.3529281 -657.58521 -233.85793 -5517.4407\n", + "cylinders -10.352928 2.9096965 169.72195 55.34824 1300.4244\n", + "displacement -657.585207 169.7219486 10950.36755 3614.03374 82929.1001\n", + "horsepower -233.857926 55.3482436 3614.03374 1481.56939 28265.6202\n", + "weight -5517.440704 1300.4243632 82929.10014 28265.62023 721484.7090\n", + "acceleration 9.115514 -2.3750522 -156.99444 -73.18697 -976.8153\n", + "year 16.691477 -2.1719296 -142.57213 -59.03643 -967.2285\n", + "origin 3.553510 -0.7817344 -51.80079 -14.11274 -400.2660\n", + " acceleration year origin \n", + "mpg 9.1155144 16.6914766 3.5535101\n", + "cylinders -2.3750522 -2.1719296 -0.7817344\n", + "displacement -156.9944354 -142.5721332 -51.8007921\n", + "horsepower -73.1869670 -59.0364320 -14.1127407\n", + "weight -976.8152526 -967.2284566 -400.2660499\n", + "acceleration 7.6113312 2.9504619 0.4727882\n", + "year 2.9504619 13.5699149 0.5386502\n", + "origin 0.4727882 0.5386502 0.6488595" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "cov(Auto[-c(9)])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "R", + "language": "R", + "name": "ir" + }, + "language_info": { + "codemirror_mode": "r", + "file_extension": ".r", + "mimetype": "text/x-r-source", + "name": "R", + "pygments_lexer": "r", + "version": "3.6.3" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/ISLR/pics/ch2-1.png b/ISLR/pics/ch2-1.png new file mode 100644 index 0000000..f5656ab Binary files /dev/null and b/ISLR/pics/ch2-1.png differ diff --git a/ISLR/pics/ch2-2.png b/ISLR/pics/ch2-2.png new file mode 100644 index 0000000..bad622a Binary files /dev/null and b/ISLR/pics/ch2-2.png differ diff --git a/ISLR/pics/ch2-3.png b/ISLR/pics/ch2-3.png new file mode 100644 index 0000000..cf0a4f0 Binary files /dev/null and b/ISLR/pics/ch2-3.png differ diff --git a/ISLR/pics/ch3-1.png b/ISLR/pics/ch3-1.png new file mode 100644 index 0000000..f6c244d Binary files /dev/null and b/ISLR/pics/ch3-1.png differ diff --git a/ISLR/pics/ch3-2.png b/ISLR/pics/ch3-2.png new file mode 100644 index 0000000..0b61e38 Binary files /dev/null and b/ISLR/pics/ch3-2.png differ diff --git a/ISLR/pics/ch3-3.png b/ISLR/pics/ch3-3.png new file mode 100644 index 0000000..2e0cad2 Binary files /dev/null and b/ISLR/pics/ch3-3.png differ diff --git a/ISLR/pics/ch3-4.png b/ISLR/pics/ch3-4.png new file mode 100644 index 0000000..3d7c9bc Binary files /dev/null and b/ISLR/pics/ch3-4.png differ diff --git a/ISLR/pics/ch3-5.png b/ISLR/pics/ch3-5.png new file mode 100644 index 0000000..de960fe Binary files /dev/null and b/ISLR/pics/ch3-5.png differ diff --git a/ISLR/pics/ch3-6.png b/ISLR/pics/ch3-6.png new file mode 100644 index 0000000..6198c78 Binary files /dev/null and b/ISLR/pics/ch3-6.png differ diff --git a/ISLR/pics/ch3-7.png b/ISLR/pics/ch3-7.png new file mode 100644 index 0000000..e1d9272 Binary files /dev/null and b/ISLR/pics/ch3-7.png differ diff --git a/ISLR/pics/ch3-8.png b/ISLR/pics/ch3-8.png new file mode 100644 index 0000000..cb30bcf Binary files /dev/null and b/ISLR/pics/ch3-8.png differ diff --git a/datasets/Advertising.csv b/datasets/Advertising.csv new file mode 100644 index 0000000..95194fa --- /dev/null +++ b/datasets/Advertising.csv @@ -0,0 +1,201 @@ +,TV,radio,newspaper,sales +1,230.1,37.8,69.2,22.1 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+"","mpg","cylinders","displacement","horsepower","weight","acceleration","year","origin","name" +"1",18,8,307,130,3504,12,70,1,"chevrolet chevelle malibu" +"2",15,8,350,165,3693,11.5,70,1,"buick skylark 320" +"3",18,8,318,150,3436,11,70,1,"plymouth satellite" +"4",16,8,304,150,3433,12,70,1,"amc rebel sst" +"5",17,8,302,140,3449,10.5,70,1,"ford torino" +"6",15,8,429,198,4341,10,70,1,"ford galaxie 500" +"7",14,8,454,220,4354,9,70,1,"chevrolet impala" +"8",14,8,440,215,4312,8.5,70,1,"plymouth fury iii" +"9",14,8,455,225,4425,10,70,1,"pontiac catalina" +"10",15,8,390,190,3850,8.5,70,1,"amc ambassador dpl" +"11",15,8,383,170,3563,10,70,1,"dodge challenger se" +"12",14,8,340,160,3609,8,70,1,"plymouth 'cuda 340" +"13",15,8,400,150,3761,9.5,70,1,"chevrolet monte carlo" +"14",14,8,455,225,3086,10,70,1,"buick estate wagon (sw)" +"15",24,4,113,95,2372,15,70,3,"toyota corona mark ii" +"16",22,6,198,95,2833,15.5,70,1,"plymouth duster" +"17",18,6,199,97,2774,15.5,70,1,"amc hornet" +"18",21,6,200,85,2587,16,70,1,"ford maverick" +"19",27,4,97,88,2130,14.5,70,3,"datsun pl510" +"20",26,4,97,46,1835,20.5,70,2,"volkswagen 1131 deluxe sedan" +"21",25,4,110,87,2672,17.5,70,2,"peugeot 504" +"22",24,4,107,90,2430,14.5,70,2,"audi 100 ls" +"23",25,4,104,95,2375,17.5,70,2,"saab 99e" +"24",26,4,121,113,2234,12.5,70,2,"bmw 2002" +"25",21,6,199,90,2648,15,70,1,"amc gremlin" +"26",10,8,360,215,4615,14,70,1,"ford f250" +"27",10,8,307,200,4376,15,70,1,"chevy c20" +"28",11,8,318,210,4382,13.5,70,1,"dodge d200" +"29",9,8,304,193,4732,18.5,70,1,"hi 1200d" +"30",27,4,97,88,2130,14.5,71,3,"datsun pl510" +"31",28,4,140,90,2264,15.5,71,1,"chevrolet vega 2300" +"32",25,4,113,95,2228,14,71,3,"toyota corona" +"34",19,6,232,100,2634,13,71,1,"amc gremlin" +"35",16,6,225,105,3439,15.5,71,1,"plymouth satellite custom" +"36",17,6,250,100,3329,15.5,71,1,"chevrolet chevelle malibu" +"37",19,6,250,88,3302,15.5,71,1,"ford torino 500" +"38",18,6,232,100,3288,15.5,71,1,"amc matador" +"39",14,8,350,165,4209,12,71,1,"chevrolet impala" +"40",14,8,400,175,4464,11.5,71,1,"pontiac catalina brougham" +"41",14,8,351,153,4154,13.5,71,1,"ford galaxie 500" +"42",14,8,318,150,4096,13,71,1,"plymouth fury iii" +"43",12,8,383,180,4955,11.5,71,1,"dodge monaco (sw)" +"44",13,8,400,170,4746,12,71,1,"ford country squire (sw)" +"45",13,8,400,175,5140,12,71,1,"pontiac safari (sw)" +"46",18,6,258,110,2962,13.5,71,1,"amc hornet sportabout (sw)" +"47",22,4,140,72,2408,19,71,1,"chevrolet vega (sw)" +"48",19,6,250,100,3282,15,71,1,"pontiac firebird" +"49",18,6,250,88,3139,14.5,71,1,"ford mustang" +"50",23,4,122,86,2220,14,71,1,"mercury capri 2000" +"51",28,4,116,90,2123,14,71,2,"opel 1900" +"52",30,4,79,70,2074,19.5,71,2,"peugeot 304" +"53",30,4,88,76,2065,14.5,71,2,"fiat 124b" +"54",31,4,71,65,1773,19,71,3,"toyota corolla 1200" +"55",35,4,72,69,1613,18,71,3,"datsun 1200" +"56",27,4,97,60,1834,19,71,2,"volkswagen model 111" +"57",26,4,91,70,1955,20.5,71,1,"plymouth cricket" +"58",24,4,113,95,2278,15.5,72,3,"toyota corona hardtop" +"59",25,4,97.5,80,2126,17,72,1,"dodge colt hardtop" +"60",23,4,97,54,2254,23.5,72,2,"volkswagen type 3" +"61",20,4,140,90,2408,19.5,72,1,"chevrolet vega" +"62",21,4,122,86,2226,16.5,72,1,"ford pinto runabout" +"63",13,8,350,165,4274,12,72,1,"chevrolet impala" +"64",14,8,400,175,4385,12,72,1,"pontiac catalina" +"65",15,8,318,150,4135,13.5,72,1,"plymouth fury iii" +"66",14,8,351,153,4129,13,72,1,"ford galaxie 500" +"67",17,8,304,150,3672,11.5,72,1,"amc ambassador sst" +"68",11,8,429,208,4633,11,72,1,"mercury marquis" +"69",13,8,350,155,4502,13.5,72,1,"buick lesabre custom" +"70",12,8,350,160,4456,13.5,72,1,"oldsmobile delta 88 royale" +"71",13,8,400,190,4422,12.5,72,1,"chrysler newport royal" +"72",19,3,70,97,2330,13.5,72,3,"mazda rx2 coupe" +"73",15,8,304,150,3892,12.5,72,1,"amc matador (sw)" +"74",13,8,307,130,4098,14,72,1,"chevrolet chevelle concours (sw)" +"75",13,8,302,140,4294,16,72,1,"ford gran torino (sw)" +"76",14,8,318,150,4077,14,72,1,"plymouth satellite custom (sw)" +"77",18,4,121,112,2933,14.5,72,2,"volvo 145e (sw)" +"78",22,4,121,76,2511,18,72,2,"volkswagen 411 (sw)" +"79",21,4,120,87,2979,19.5,72,2,"peugeot 504 (sw)" +"80",26,4,96,69,2189,18,72,2,"renault 12 (sw)" +"81",22,4,122,86,2395,16,72,1,"ford pinto (sw)" +"82",28,4,97,92,2288,17,72,3,"datsun 510 (sw)" +"83",23,4,120,97,2506,14.5,72,3,"toyouta corona mark ii (sw)" +"84",28,4,98,80,2164,15,72,1,"dodge colt (sw)" +"85",27,4,97,88,2100,16.5,72,3,"toyota corolla 1600 (sw)" +"86",13,8,350,175,4100,13,73,1,"buick century 350" +"87",14,8,304,150,3672,11.5,73,1,"amc matador" +"88",13,8,350,145,3988,13,73,1,"chevrolet malibu" +"89",14,8,302,137,4042,14.5,73,1,"ford gran torino" +"90",15,8,318,150,3777,12.5,73,1,"dodge coronet custom" +"91",12,8,429,198,4952,11.5,73,1,"mercury marquis brougham" +"92",13,8,400,150,4464,12,73,1,"chevrolet caprice classic" +"93",13,8,351,158,4363,13,73,1,"ford ltd" +"94",14,8,318,150,4237,14.5,73,1,"plymouth fury gran sedan" +"95",13,8,440,215,4735,11,73,1,"chrysler new yorker brougham" +"96",12,8,455,225,4951,11,73,1,"buick electra 225 custom" +"97",13,8,360,175,3821,11,73,1,"amc ambassador brougham" +"98",18,6,225,105,3121,16.5,73,1,"plymouth valiant" +"99",16,6,250,100,3278,18,73,1,"chevrolet nova custom" +"100",18,6,232,100,2945,16,73,1,"amc hornet" +"101",18,6,250,88,3021,16.5,73,1,"ford maverick" +"102",23,6,198,95,2904,16,73,1,"plymouth duster" +"103",26,4,97,46,1950,21,73,2,"volkswagen super beetle" +"104",11,8,400,150,4997,14,73,1,"chevrolet impala" +"105",12,8,400,167,4906,12.5,73,1,"ford country" +"106",13,8,360,170,4654,13,73,1,"plymouth custom suburb" +"107",12,8,350,180,4499,12.5,73,1,"oldsmobile vista cruiser" +"108",18,6,232,100,2789,15,73,1,"amc gremlin" +"109",20,4,97,88,2279,19,73,3,"toyota carina" +"110",21,4,140,72,2401,19.5,73,1,"chevrolet vega" +"111",22,4,108,94,2379,16.5,73,3,"datsun 610" +"112",18,3,70,90,2124,13.5,73,3,"maxda rx3" +"113",19,4,122,85,2310,18.5,73,1,"ford pinto" +"114",21,6,155,107,2472,14,73,1,"mercury capri v6" +"115",26,4,98,90,2265,15.5,73,2,"fiat 124 sport coupe" +"116",15,8,350,145,4082,13,73,1,"chevrolet monte carlo s" +"117",16,8,400,230,4278,9.5,73,1,"pontiac grand prix" +"118",29,4,68,49,1867,19.5,73,2,"fiat 128" +"119",24,4,116,75,2158,15.5,73,2,"opel manta" +"120",20,4,114,91,2582,14,73,2,"audi 100ls" +"121",19,4,121,112,2868,15.5,73,2,"volvo 144ea" +"122",15,8,318,150,3399,11,73,1,"dodge dart custom" +"123",24,4,121,110,2660,14,73,2,"saab 99le" +"124",20,6,156,122,2807,13.5,73,3,"toyota mark ii" +"125",11,8,350,180,3664,11,73,1,"oldsmobile omega" +"126",20,6,198,95,3102,16.5,74,1,"plymouth duster" +"128",19,6,232,100,2901,16,74,1,"amc hornet" +"129",15,6,250,100,3336,17,74,1,"chevrolet nova" +"130",31,4,79,67,1950,19,74,3,"datsun b210" +"131",26,4,122,80,2451,16.5,74,1,"ford pinto" +"132",32,4,71,65,1836,21,74,3,"toyota corolla 1200" +"133",25,4,140,75,2542,17,74,1,"chevrolet vega" +"134",16,6,250,100,3781,17,74,1,"chevrolet chevelle malibu classic" +"135",16,6,258,110,3632,18,74,1,"amc matador" +"136",18,6,225,105,3613,16.5,74,1,"plymouth satellite sebring" +"137",16,8,302,140,4141,14,74,1,"ford gran torino" +"138",13,8,350,150,4699,14.5,74,1,"buick century luxus (sw)" +"139",14,8,318,150,4457,13.5,74,1,"dodge coronet custom (sw)" +"140",14,8,302,140,4638,16,74,1,"ford gran torino (sw)" +"141",14,8,304,150,4257,15.5,74,1,"amc matador (sw)" +"142",29,4,98,83,2219,16.5,74,2,"audi fox" +"143",26,4,79,67,1963,15.5,74,2,"volkswagen dasher" +"144",26,4,97,78,2300,14.5,74,2,"opel manta" +"145",31,4,76,52,1649,16.5,74,3,"toyota corona" +"146",32,4,83,61,2003,19,74,3,"datsun 710" +"147",28,4,90,75,2125,14.5,74,1,"dodge colt" +"148",24,4,90,75,2108,15.5,74,2,"fiat 128" +"149",26,4,116,75,2246,14,74,2,"fiat 124 tc" +"150",24,4,120,97,2489,15,74,3,"honda civic" +"151",26,4,108,93,2391,15.5,74,3,"subaru" +"152",31,4,79,67,2000,16,74,2,"fiat x1.9" +"153",19,6,225,95,3264,16,75,1,"plymouth valiant custom" +"154",18,6,250,105,3459,16,75,1,"chevrolet nova" +"155",15,6,250,72,3432,21,75,1,"mercury monarch" +"156",15,6,250,72,3158,19.5,75,1,"ford maverick" +"157",16,8,400,170,4668,11.5,75,1,"pontiac catalina" +"158",15,8,350,145,4440,14,75,1,"chevrolet bel air" +"159",16,8,318,150,4498,14.5,75,1,"plymouth grand fury" +"160",14,8,351,148,4657,13.5,75,1,"ford ltd" +"161",17,6,231,110,3907,21,75,1,"buick century" +"162",16,6,250,105,3897,18.5,75,1,"chevroelt chevelle malibu" +"163",15,6,258,110,3730,19,75,1,"amc matador" +"164",18,6,225,95,3785,19,75,1,"plymouth fury" +"165",21,6,231,110,3039,15,75,1,"buick skyhawk" +"166",20,8,262,110,3221,13.5,75,1,"chevrolet monza 2+2" +"167",13,8,302,129,3169,12,75,1,"ford mustang ii" +"168",29,4,97,75,2171,16,75,3,"toyota corolla" +"169",23,4,140,83,2639,17,75,1,"ford pinto" +"170",20,6,232,100,2914,16,75,1,"amc gremlin" +"171",23,4,140,78,2592,18.5,75,1,"pontiac astro" +"172",24,4,134,96,2702,13.5,75,3,"toyota corona" +"173",25,4,90,71,2223,16.5,75,2,"volkswagen dasher" +"174",24,4,119,97,2545,17,75,3,"datsun 710" +"175",18,6,171,97,2984,14.5,75,1,"ford pinto" +"176",29,4,90,70,1937,14,75,2,"volkswagen rabbit" +"177",19,6,232,90,3211,17,75,1,"amc pacer" +"178",23,4,115,95,2694,15,75,2,"audi 100ls" +"179",23,4,120,88,2957,17,75,2,"peugeot 504" +"180",22,4,121,98,2945,14.5,75,2,"volvo 244dl" +"181",25,4,121,115,2671,13.5,75,2,"saab 99le" +"182",33,4,91,53,1795,17.5,75,3,"honda civic cvcc" +"183",28,4,107,86,2464,15.5,76,2,"fiat 131" +"184",25,4,116,81,2220,16.9,76,2,"opel 1900" +"185",25,4,140,92,2572,14.9,76,1,"capri ii" +"186",26,4,98,79,2255,17.7,76,1,"dodge colt" +"187",27,4,101,83,2202,15.3,76,2,"renault 12tl" +"188",17.5,8,305,140,4215,13,76,1,"chevrolet chevelle malibu classic" +"189",16,8,318,150,4190,13,76,1,"dodge coronet brougham" +"190",15.5,8,304,120,3962,13.9,76,1,"amc matador" +"191",14.5,8,351,152,4215,12.8,76,1,"ford gran torino" +"192",22,6,225,100,3233,15.4,76,1,"plymouth valiant" +"193",22,6,250,105,3353,14.5,76,1,"chevrolet nova" +"194",24,6,200,81,3012,17.6,76,1,"ford maverick" +"195",22.5,6,232,90,3085,17.6,76,1,"amc hornet" +"196",29,4,85,52,2035,22.2,76,1,"chevrolet chevette" +"197",24.5,4,98,60,2164,22.1,76,1,"chevrolet woody" +"198",29,4,90,70,1937,14.2,76,2,"vw rabbit" +"199",33,4,91,53,1795,17.4,76,3,"honda civic" +"200",20,6,225,100,3651,17.7,76,1,"dodge aspen se" +"201",18,6,250,78,3574,21,76,1,"ford granada ghia" +"202",18.5,6,250,110,3645,16.2,76,1,"pontiac ventura sj" +"203",17.5,6,258,95,3193,17.8,76,1,"amc pacer d/l" +"204",29.5,4,97,71,1825,12.2,76,2,"volkswagen rabbit" +"205",32,4,85,70,1990,17,76,3,"datsun b-210" +"206",28,4,97,75,2155,16.4,76,3,"toyota corolla" +"207",26.5,4,140,72,2565,13.6,76,1,"ford pinto" +"208",20,4,130,102,3150,15.7,76,2,"volvo 245" +"209",13,8,318,150,3940,13.2,76,1,"plymouth volare premier v8" +"210",19,4,120,88,3270,21.9,76,2,"peugeot 504" +"211",19,6,156,108,2930,15.5,76,3,"toyota mark ii" +"212",16.5,6,168,120,3820,16.7,76,2,"mercedes-benz 280s" +"213",16.5,8,350,180,4380,12.1,76,1,"cadillac seville" +"214",13,8,350,145,4055,12,76,1,"chevy c10" +"215",13,8,302,130,3870,15,76,1,"ford f108" +"216",13,8,318,150,3755,14,76,1,"dodge d100" +"217",31.5,4,98,68,2045,18.5,77,3,"honda accord cvcc" +"218",30,4,111,80,2155,14.8,77,1,"buick opel isuzu deluxe" +"219",36,4,79,58,1825,18.6,77,2,"renault 5 gtl" +"220",25.5,4,122,96,2300,15.5,77,1,"plymouth arrow gs" +"221",33.5,4,85,70,1945,16.8,77,3,"datsun f-10 hatchback" +"222",17.5,8,305,145,3880,12.5,77,1,"chevrolet caprice classic" +"223",17,8,260,110,4060,19,77,1,"oldsmobile cutlass supreme" +"224",15.5,8,318,145,4140,13.7,77,1,"dodge monaco brougham" +"225",15,8,302,130,4295,14.9,77,1,"mercury cougar brougham" +"226",17.5,6,250,110,3520,16.4,77,1,"chevrolet concours" +"227",20.5,6,231,105,3425,16.9,77,1,"buick skylark" +"228",19,6,225,100,3630,17.7,77,1,"plymouth volare custom" +"229",18.5,6,250,98,3525,19,77,1,"ford granada" +"230",16,8,400,180,4220,11.1,77,1,"pontiac grand prix lj" +"231",15.5,8,350,170,4165,11.4,77,1,"chevrolet monte carlo landau" +"232",15.5,8,400,190,4325,12.2,77,1,"chrysler cordoba" +"233",16,8,351,149,4335,14.5,77,1,"ford thunderbird" +"234",29,4,97,78,1940,14.5,77,2,"volkswagen rabbit custom" +"235",24.5,4,151,88,2740,16,77,1,"pontiac sunbird coupe" +"236",26,4,97,75,2265,18.2,77,3,"toyota corolla liftback" +"237",25.5,4,140,89,2755,15.8,77,1,"ford mustang ii 2+2" +"238",30.5,4,98,63,2051,17,77,1,"chevrolet chevette" +"239",33.5,4,98,83,2075,15.9,77,1,"dodge colt m/m" +"240",30,4,97,67,1985,16.4,77,3,"subaru dl" +"241",30.5,4,97,78,2190,14.1,77,2,"volkswagen dasher" +"242",22,6,146,97,2815,14.5,77,3,"datsun 810" +"243",21.5,4,121,110,2600,12.8,77,2,"bmw 320i" +"244",21.5,3,80,110,2720,13.5,77,3,"mazda rx-4" +"245",43.1,4,90,48,1985,21.5,78,2,"volkswagen rabbit custom diesel" +"246",36.1,4,98,66,1800,14.4,78,1,"ford fiesta" +"247",32.8,4,78,52,1985,19.4,78,3,"mazda glc deluxe" +"248",39.4,4,85,70,2070,18.6,78,3,"datsun b210 gx" +"249",36.1,4,91,60,1800,16.4,78,3,"honda civic cvcc" +"250",19.9,8,260,110,3365,15.5,78,1,"oldsmobile cutlass salon brougham" +"251",19.4,8,318,140,3735,13.2,78,1,"dodge diplomat" +"252",20.2,8,302,139,3570,12.8,78,1,"mercury monarch ghia" +"253",19.2,6,231,105,3535,19.2,78,1,"pontiac phoenix lj" +"254",20.5,6,200,95,3155,18.2,78,1,"chevrolet malibu" +"255",20.2,6,200,85,2965,15.8,78,1,"ford fairmont (auto)" +"256",25.1,4,140,88,2720,15.4,78,1,"ford fairmont (man)" +"257",20.5,6,225,100,3430,17.2,78,1,"plymouth volare" +"258",19.4,6,232,90,3210,17.2,78,1,"amc concord" +"259",20.6,6,231,105,3380,15.8,78,1,"buick century special" +"260",20.8,6,200,85,3070,16.7,78,1,"mercury zephyr" +"261",18.6,6,225,110,3620,18.7,78,1,"dodge aspen" +"262",18.1,6,258,120,3410,15.1,78,1,"amc concord d/l" +"263",19.2,8,305,145,3425,13.2,78,1,"chevrolet monte carlo landau" +"264",17.7,6,231,165,3445,13.4,78,1,"buick regal sport coupe (turbo)" +"265",18.1,8,302,139,3205,11.2,78,1,"ford futura" +"266",17.5,8,318,140,4080,13.7,78,1,"dodge magnum xe" +"267",30,4,98,68,2155,16.5,78,1,"chevrolet chevette" +"268",27.5,4,134,95,2560,14.2,78,3,"toyota corona" +"269",27.2,4,119,97,2300,14.7,78,3,"datsun 510" +"270",30.9,4,105,75,2230,14.5,78,1,"dodge omni" +"271",21.1,4,134,95,2515,14.8,78,3,"toyota celica gt liftback" +"272",23.2,4,156,105,2745,16.7,78,1,"plymouth sapporo" +"273",23.8,4,151,85,2855,17.6,78,1,"oldsmobile starfire sx" +"274",23.9,4,119,97,2405,14.9,78,3,"datsun 200-sx" +"275",20.3,5,131,103,2830,15.9,78,2,"audi 5000" +"276",17,6,163,125,3140,13.6,78,2,"volvo 264gl" +"277",21.6,4,121,115,2795,15.7,78,2,"saab 99gle" +"278",16.2,6,163,133,3410,15.8,78,2,"peugeot 604sl" +"279",31.5,4,89,71,1990,14.9,78,2,"volkswagen scirocco" +"280",29.5,4,98,68,2135,16.6,78,3,"honda accord lx" +"281",21.5,6,231,115,3245,15.4,79,1,"pontiac lemans v6" +"282",19.8,6,200,85,2990,18.2,79,1,"mercury zephyr 6" +"283",22.3,4,140,88,2890,17.3,79,1,"ford fairmont 4" +"284",20.2,6,232,90,3265,18.2,79,1,"amc concord dl 6" +"285",20.6,6,225,110,3360,16.6,79,1,"dodge aspen 6" +"286",17,8,305,130,3840,15.4,79,1,"chevrolet caprice classic" +"287",17.6,8,302,129,3725,13.4,79,1,"ford ltd landau" +"288",16.5,8,351,138,3955,13.2,79,1,"mercury grand marquis" +"289",18.2,8,318,135,3830,15.2,79,1,"dodge st. regis" +"290",16.9,8,350,155,4360,14.9,79,1,"buick estate wagon (sw)" +"291",15.5,8,351,142,4054,14.3,79,1,"ford country squire (sw)" +"292",19.2,8,267,125,3605,15,79,1,"chevrolet malibu classic (sw)" +"293",18.5,8,360,150,3940,13,79,1,"chrysler lebaron town @ country (sw)" +"294",31.9,4,89,71,1925,14,79,2,"vw rabbit custom" +"295",34.1,4,86,65,1975,15.2,79,3,"maxda glc deluxe" +"296",35.7,4,98,80,1915,14.4,79,1,"dodge colt hatchback custom" +"297",27.4,4,121,80,2670,15,79,1,"amc spirit dl" +"298",25.4,5,183,77,3530,20.1,79,2,"mercedes benz 300d" +"299",23,8,350,125,3900,17.4,79,1,"cadillac eldorado" +"300",27.2,4,141,71,3190,24.8,79,2,"peugeot 504" +"301",23.9,8,260,90,3420,22.2,79,1,"oldsmobile cutlass salon brougham" +"302",34.2,4,105,70,2200,13.2,79,1,"plymouth horizon" +"303",34.5,4,105,70,2150,14.9,79,1,"plymouth horizon tc3" +"304",31.8,4,85,65,2020,19.2,79,3,"datsun 210" +"305",37.3,4,91,69,2130,14.7,79,2,"fiat strada custom" +"306",28.4,4,151,90,2670,16,79,1,"buick skylark limited" +"307",28.8,6,173,115,2595,11.3,79,1,"chevrolet citation" +"308",26.8,6,173,115,2700,12.9,79,1,"oldsmobile omega brougham" +"309",33.5,4,151,90,2556,13.2,79,1,"pontiac phoenix" +"310",41.5,4,98,76,2144,14.7,80,2,"vw rabbit" +"311",38.1,4,89,60,1968,18.8,80,3,"toyota corolla tercel" +"312",32.1,4,98,70,2120,15.5,80,1,"chevrolet chevette" +"313",37.2,4,86,65,2019,16.4,80,3,"datsun 310" +"314",28,4,151,90,2678,16.5,80,1,"chevrolet citation" +"315",26.4,4,140,88,2870,18.1,80,1,"ford fairmont" +"316",24.3,4,151,90,3003,20.1,80,1,"amc concord" +"317",19.1,6,225,90,3381,18.7,80,1,"dodge aspen" +"318",34.3,4,97,78,2188,15.8,80,2,"audi 4000" +"319",29.8,4,134,90,2711,15.5,80,3,"toyota corona liftback" +"320",31.3,4,120,75,2542,17.5,80,3,"mazda 626" +"321",37,4,119,92,2434,15,80,3,"datsun 510 hatchback" +"322",32.2,4,108,75,2265,15.2,80,3,"toyota corolla" +"323",46.6,4,86,65,2110,17.9,80,3,"mazda glc" +"324",27.9,4,156,105,2800,14.4,80,1,"dodge colt" +"325",40.8,4,85,65,2110,19.2,80,3,"datsun 210" +"326",44.3,4,90,48,2085,21.7,80,2,"vw rabbit c (diesel)" +"327",43.4,4,90,48,2335,23.7,80,2,"vw dasher (diesel)" +"328",36.4,5,121,67,2950,19.9,80,2,"audi 5000s (diesel)" +"329",30,4,146,67,3250,21.8,80,2,"mercedes-benz 240d" +"330",44.6,4,91,67,1850,13.8,80,3,"honda civic 1500 gl" +"332",33.8,4,97,67,2145,18,80,3,"subaru dl" +"333",29.8,4,89,62,1845,15.3,80,2,"vokswagen rabbit" +"334",32.7,6,168,132,2910,11.4,80,3,"datsun 280-zx" +"335",23.7,3,70,100,2420,12.5,80,3,"mazda rx-7 gs" +"336",35,4,122,88,2500,15.1,80,2,"triumph tr7 coupe" +"338",32.4,4,107,72,2290,17,80,3,"honda accord" +"339",27.2,4,135,84,2490,15.7,81,1,"plymouth reliant" +"340",26.6,4,151,84,2635,16.4,81,1,"buick skylark" +"341",25.8,4,156,92,2620,14.4,81,1,"dodge aries wagon (sw)" +"342",23.5,6,173,110,2725,12.6,81,1,"chevrolet citation" +"343",30,4,135,84,2385,12.9,81,1,"plymouth reliant" +"344",39.1,4,79,58,1755,16.9,81,3,"toyota starlet" +"345",39,4,86,64,1875,16.4,81,1,"plymouth champ" +"346",35.1,4,81,60,1760,16.1,81,3,"honda civic 1300" +"347",32.3,4,97,67,2065,17.8,81,3,"subaru" +"348",37,4,85,65,1975,19.4,81,3,"datsun 210 mpg" +"349",37.7,4,89,62,2050,17.3,81,3,"toyota tercel" +"350",34.1,4,91,68,1985,16,81,3,"mazda glc 4" +"351",34.7,4,105,63,2215,14.9,81,1,"plymouth horizon 4" +"352",34.4,4,98,65,2045,16.2,81,1,"ford escort 4w" +"353",29.9,4,98,65,2380,20.7,81,1,"ford escort 2h" +"354",33,4,105,74,2190,14.2,81,2,"volkswagen jetta" +"356",33.7,4,107,75,2210,14.4,81,3,"honda prelude" +"357",32.4,4,108,75,2350,16.8,81,3,"toyota corolla" +"358",32.9,4,119,100,2615,14.8,81,3,"datsun 200sx" +"359",31.6,4,120,74,2635,18.3,81,3,"mazda 626" +"360",28.1,4,141,80,3230,20.4,81,2,"peugeot 505s turbo diesel" +"361",30.7,6,145,76,3160,19.6,81,2,"volvo diesel" +"362",25.4,6,168,116,2900,12.6,81,3,"toyota cressida" +"363",24.2,6,146,120,2930,13.8,81,3,"datsun 810 maxima" +"364",22.4,6,231,110,3415,15.8,81,1,"buick century" +"365",26.6,8,350,105,3725,19,81,1,"oldsmobile cutlass ls" +"366",20.2,6,200,88,3060,17.1,81,1,"ford granada gl" +"367",17.6,6,225,85,3465,16.6,81,1,"chrysler lebaron salon" +"368",28,4,112,88,2605,19.6,82,1,"chevrolet cavalier" +"369",27,4,112,88,2640,18.6,82,1,"chevrolet cavalier wagon" +"370",34,4,112,88,2395,18,82,1,"chevrolet cavalier 2-door" +"371",31,4,112,85,2575,16.2,82,1,"pontiac j2000 se hatchback" +"372",29,4,135,84,2525,16,82,1,"dodge aries se" +"373",27,4,151,90,2735,18,82,1,"pontiac phoenix" +"374",24,4,140,92,2865,16.4,82,1,"ford fairmont futura" +"375",36,4,105,74,1980,15.3,82,2,"volkswagen rabbit l" +"376",37,4,91,68,2025,18.2,82,3,"mazda glc custom l" +"377",31,4,91,68,1970,17.6,82,3,"mazda glc custom" +"378",38,4,105,63,2125,14.7,82,1,"plymouth horizon miser" +"379",36,4,98,70,2125,17.3,82,1,"mercury lynx l" +"380",36,4,120,88,2160,14.5,82,3,"nissan stanza xe" +"381",36,4,107,75,2205,14.5,82,3,"honda accord" +"382",34,4,108,70,2245,16.9,82,3,"toyota corolla" +"383",38,4,91,67,1965,15,82,3,"honda civic" +"384",32,4,91,67,1965,15.7,82,3,"honda civic (auto)" +"385",38,4,91,67,1995,16.2,82,3,"datsun 310 gx" +"386",25,6,181,110,2945,16.4,82,1,"buick century limited" +"387",38,6,262,85,3015,17,82,1,"oldsmobile cutlass ciera (diesel)" +"388",26,4,156,92,2585,14.5,82,1,"chrysler lebaron medallion" +"389",22,6,232,112,2835,14.7,82,1,"ford granada l" +"390",32,4,144,96,2665,13.9,82,3,"toyota celica gt" +"391",36,4,135,84,2370,13,82,1,"dodge charger 2.2" +"392",27,4,151,90,2950,17.3,82,1,"chevrolet camaro" +"393",27,4,140,86,2790,15.6,82,1,"ford mustang gl" +"394",44,4,97,52,2130,24.6,82,2,"vw pickup" +"395",32,4,135,84,2295,11.6,82,1,"dodge rampage" +"396",28,4,120,79,2625,18.6,82,1,"ford ranger" +"397",31,4,119,82,2720,19.4,82,1,"chevy s-10" diff --git a/datasets/Auto.data b/datasets/Auto.data new file mode 100644 index 0000000..236ae22 --- /dev/null +++ b/datasets/Auto.data @@ -0,0 +1,398 @@ +mpg cylinders displacement horsepower weight acceleration year origin name +18.0 8 307.0 130.0 3504. 12.0 70 1 "chevrolet chevelle malibu" +15.0 8 350.0 165.0 3693. 11.5 70 1 "buick skylark 320" +18.0 8 318.0 150.0 3436. 11.0 70 1 "plymouth satellite" +16.0 8 304.0 150.0 3433. 12.0 70 1 "amc rebel sst" +17.0 8 302.0 140.0 3449. 10.5 70 1 "ford torino" +15.0 8 429.0 198.0 4341. 10.0 70 1 "ford galaxie 500" +14.0 8 454.0 220.0 4354. 9.0 70 1 "chevrolet impala" +14.0 8 440.0 215.0 4312. 8.5 70 1 "plymouth fury iii" +14.0 8 455.0 225.0 4425. 10.0 70 1 "pontiac catalina" +15.0 8 390.0 190.0 3850. 8.5 70 1 "amc ambassador dpl" +15.0 8 383.0 170.0 3563. 10.0 70 1 "dodge challenger se" +14.0 8 340.0 160.0 3609. 8.0 70 1 "plymouth 'cuda 340" +15.0 8 400.0 150.0 3761. 9.5 70 1 "chevrolet monte carlo" +14.0 8 455.0 225.0 3086. 10.0 70 1 "buick estate wagon (sw)" +24.0 4 113.0 95.00 2372. 15.0 70 3 "toyota corona mark ii" +22.0 6 198.0 95.00 2833. 15.5 70 1 "plymouth duster" +18.0 6 199.0 97.00 2774. 15.5 70 1 "amc hornet" +21.0 6 200.0 85.00 2587. 16.0 70 1 "ford maverick" +27.0 4 97.00 88.00 2130. 14.5 70 3 "datsun pl510" +26.0 4 97.00 46.00 1835. 20.5 70 2 "volkswagen 1131 deluxe sedan" +25.0 4 110.0 87.00 2672. 17.5 70 2 "peugeot 504" +24.0 4 107.0 90.00 2430. 14.5 70 2 "audi 100 ls" +25.0 4 104.0 95.00 2375. 17.5 70 2 "saab 99e" +26.0 4 121.0 113.0 2234. 12.5 70 2 "bmw 2002" +21.0 6 199.0 90.00 2648. 15.0 70 1 "amc gremlin" +10.0 8 360.0 215.0 4615. 14.0 70 1 "ford f250" +10.0 8 307.0 200.0 4376. 15.0 70 1 "chevy c20" +11.0 8 318.0 210.0 4382. 13.5 70 1 "dodge d200" +9.0 8 304.0 193.0 4732. 18.5 70 1 "hi 1200d" +27.0 4 97.00 88.00 2130. 14.5 71 3 "datsun pl510" +28.0 4 140.0 90.00 2264. 15.5 71 1 "chevrolet vega 2300" +25.0 4 113.0 95.00 2228. 14.0 71 3 "toyota corona" +25.0 4 98.00 ? 2046. 19.0 71 1 "ford pinto" +19.0 6 232.0 100.0 2634. 13.0 71 1 "amc gremlin" +16.0 6 225.0 105.0 3439. 15.5 71 1 "plymouth satellite custom" +17.0 6 250.0 100.0 3329. 15.5 71 1 "chevrolet chevelle malibu" +19.0 6 250.0 88.00 3302. 15.5 71 1 "ford torino 500" +18.0 6 232.0 100.0 3288. 15.5 71 1 "amc matador" +14.0 8 350.0 165.0 4209. 12.0 71 1 "chevrolet impala" +14.0 8 400.0 175.0 4464. 11.5 71 1 "pontiac catalina brougham" +14.0 8 351.0 153.0 4154. 13.5 71 1 "ford galaxie 500" +14.0 8 318.0 150.0 4096. 13.0 71 1 "plymouth fury iii" +12.0 8 383.0 180.0 4955. 11.5 71 1 "dodge monaco (sw)" +13.0 8 400.0 170.0 4746. 12.0 71 1 "ford country squire (sw)" +13.0 8 400.0 175.0 5140. 12.0 71 1 "pontiac safari (sw)" +18.0 6 258.0 110.0 2962. 13.5 71 1 "amc hornet sportabout (sw)" +22.0 4 140.0 72.00 2408. 19.0 71 1 "chevrolet vega (sw)" +19.0 6 250.0 100.0 3282. 15.0 71 1 "pontiac firebird" +18.0 6 250.0 88.00 3139. 14.5 71 1 "ford mustang" +23.0 4 122.0 86.00 2220. 14.0 71 1 "mercury capri 2000" +28.0 4 116.0 90.00 2123. 14.0 71 2 "opel 1900" +30.0 4 79.00 70.00 2074. 19.5 71 2 "peugeot 304" +30.0 4 88.00 76.00 2065. 14.5 71 2 "fiat 124b" +31.0 4 71.00 65.00 1773. 19.0 71 3 "toyota corolla 1200" +35.0 4 72.00 69.00 1613. 18.0 71 3 "datsun 1200" +27.0 4 97.00 60.00 1834. 19.0 71 2 "volkswagen model 111" +26.0 4 91.00 70.00 1955. 20.5 71 1 "plymouth cricket" +24.0 4 113.0 95.00 2278. 15.5 72 3 "toyota corona hardtop" +25.0 4 97.50 80.00 2126. 17.0 72 1 "dodge colt hardtop" +23.0 4 97.00 54.00 2254. 23.5 72 2 "volkswagen type 3" +20.0 4 140.0 90.00 2408. 19.5 72 1 "chevrolet vega" +21.0 4 122.0 86.00 2226. 16.5 72 1 "ford pinto runabout" +13.0 8 350.0 165.0 4274. 12.0 72 1 "chevrolet impala" +14.0 8 400.0 175.0 4385. 12.0 72 1 "pontiac catalina" +15.0 8 318.0 150.0 4135. 13.5 72 1 "plymouth fury iii" +14.0 8 351.0 153.0 4129. 13.0 72 1 "ford galaxie 500" +17.0 8 304.0 150.0 3672. 11.5 72 1 "amc ambassador sst" +11.0 8 429.0 208.0 4633. 11.0 72 1 "mercury marquis" +13.0 8 350.0 155.0 4502. 13.5 72 1 "buick lesabre custom" +12.0 8 350.0 160.0 4456. 13.5 72 1 "oldsmobile delta 88 royale" +13.0 8 400.0 190.0 4422. 12.5 72 1 "chrysler newport royal" +19.0 3 70.00 97.00 2330. 13.5 72 3 "mazda rx2 coupe" +15.0 8 304.0 150.0 3892. 12.5 72 1 "amc matador (sw)" +13.0 8 307.0 130.0 4098. 14.0 72 1 "chevrolet chevelle concours (sw)" +13.0 8 302.0 140.0 4294. 16.0 72 1 "ford gran torino (sw)" +14.0 8 318.0 150.0 4077. 14.0 72 1 "plymouth satellite custom (sw)" +18.0 4 121.0 112.0 2933. 14.5 72 2 "volvo 145e (sw)" +22.0 4 121.0 76.00 2511. 18.0 72 2 "volkswagen 411 (sw)" +21.0 4 120.0 87.00 2979. 19.5 72 2 "peugeot 504 (sw)" +26.0 4 96.00 69.00 2189. 18.0 72 2 "renault 12 (sw)" +22.0 4 122.0 86.00 2395. 16.0 72 1 "ford pinto (sw)" +28.0 4 97.00 92.00 2288. 17.0 72 3 "datsun 510 (sw)" +23.0 4 120.0 97.00 2506. 14.5 72 3 "toyouta corona mark ii (sw)" +28.0 4 98.00 80.00 2164. 15.0 72 1 "dodge colt (sw)" +27.0 4 97.00 88.00 2100. 16.5 72 3 "toyota corolla 1600 (sw)" +13.0 8 350.0 175.0 4100. 13.0 73 1 "buick century 350" +14.0 8 304.0 150.0 3672. 11.5 73 1 "amc matador" +13.0 8 350.0 145.0 3988. 13.0 73 1 "chevrolet malibu" +14.0 8 302.0 137.0 4042. 14.5 73 1 "ford gran torino" +15.0 8 318.0 150.0 3777. 12.5 73 1 "dodge coronet custom" +12.0 8 429.0 198.0 4952. 11.5 73 1 "mercury marquis brougham" +13.0 8 400.0 150.0 4464. 12.0 73 1 "chevrolet caprice classic" +13.0 8 351.0 158.0 4363. 13.0 73 1 "ford ltd" +14.0 8 318.0 150.0 4237. 14.5 73 1 "plymouth fury gran sedan" +13.0 8 440.0 215.0 4735. 11.0 73 1 "chrysler new yorker brougham" +12.0 8 455.0 225.0 4951. 11.0 73 1 "buick electra 225 custom" +13.0 8 360.0 175.0 3821. 11.0 73 1 "amc ambassador brougham" +18.0 6 225.0 105.0 3121. 16.5 73 1 "plymouth valiant" +16.0 6 250.0 100.0 3278. 18.0 73 1 "chevrolet nova custom" +18.0 6 232.0 100.0 2945. 16.0 73 1 "amc hornet" +18.0 6 250.0 88.00 3021. 16.5 73 1 "ford maverick" +23.0 6 198.0 95.00 2904. 16.0 73 1 "plymouth duster" +26.0 4 97.00 46.00 1950. 21.0 73 2 "volkswagen super beetle" +11.0 8 400.0 150.0 4997. 14.0 73 1 "chevrolet impala" +12.0 8 400.0 167.0 4906. 12.5 73 1 "ford country" +13.0 8 360.0 170.0 4654. 13.0 73 1 "plymouth custom suburb" +12.0 8 350.0 180.0 4499. 12.5 73 1 "oldsmobile vista cruiser" +18.0 6 232.0 100.0 2789. 15.0 73 1 "amc gremlin" +20.0 4 97.00 88.00 2279. 19.0 73 3 "toyota carina" +21.0 4 140.0 72.00 2401. 19.5 73 1 "chevrolet vega" +22.0 4 108.0 94.00 2379. 16.5 73 3 "datsun 610" +18.0 3 70.00 90.00 2124. 13.5 73 3 "maxda rx3" +19.0 4 122.0 85.00 2310. 18.5 73 1 "ford pinto" +21.0 6 155.0 107.0 2472. 14.0 73 1 "mercury capri v6" +26.0 4 98.00 90.00 2265. 15.5 73 2 "fiat 124 sport coupe" +15.0 8 350.0 145.0 4082. 13.0 73 1 "chevrolet monte carlo s" +16.0 8 400.0 230.0 4278. 9.50 73 1 "pontiac grand prix" +29.0 4 68.00 49.00 1867. 19.5 73 2 "fiat 128" +24.0 4 116.0 75.00 2158. 15.5 73 2 "opel manta" +20.0 4 114.0 91.00 2582. 14.0 73 2 "audi 100ls" +19.0 4 121.0 112.0 2868. 15.5 73 2 "volvo 144ea" +15.0 8 318.0 150.0 3399. 11.0 73 1 "dodge dart custom" +24.0 4 121.0 110.0 2660. 14.0 73 2 "saab 99le" +20.0 6 156.0 122.0 2807. 13.5 73 3 "toyota mark ii" +11.0 8 350.0 180.0 3664. 11.0 73 1 "oldsmobile omega" +20.0 6 198.0 95.00 3102. 16.5 74 1 "plymouth duster" +21.0 6 200.0 ? 2875. 17.0 74 1 "ford maverick" +19.0 6 232.0 100.0 2901. 16.0 74 1 "amc hornet" +15.0 6 250.0 100.0 3336. 17.0 74 1 "chevrolet nova" +31.0 4 79.00 67.00 1950. 19.0 74 3 "datsun b210" +26.0 4 122.0 80.00 2451. 16.5 74 1 "ford pinto" +32.0 4 71.00 65.00 1836. 21.0 74 3 "toyota corolla 1200" +25.0 4 140.0 75.00 2542. 17.0 74 1 "chevrolet vega" +16.0 6 250.0 100.0 3781. 17.0 74 1 "chevrolet chevelle malibu classic" +16.0 6 258.0 110.0 3632. 18.0 74 1 "amc matador" +18.0 6 225.0 105.0 3613. 16.5 74 1 "plymouth satellite sebring" +16.0 8 302.0 140.0 4141. 14.0 74 1 "ford gran torino" +13.0 8 350.0 150.0 4699. 14.5 74 1 "buick century luxus (sw)" +14.0 8 318.0 150.0 4457. 13.5 74 1 "dodge coronet custom (sw)" +14.0 8 302.0 140.0 4638. 16.0 74 1 "ford gran torino (sw)" +14.0 8 304.0 150.0 4257. 15.5 74 1 "amc matador (sw)" +29.0 4 98.00 83.00 2219. 16.5 74 2 "audi fox" +26.0 4 79.00 67.00 1963. 15.5 74 2 "volkswagen dasher" +26.0 4 97.00 78.00 2300. 14.5 74 2 "opel manta" +31.0 4 76.00 52.00 1649. 16.5 74 3 "toyota corona" +32.0 4 83.00 61.00 2003. 19.0 74 3 "datsun 710" +28.0 4 90.00 75.00 2125. 14.5 74 1 "dodge colt" +24.0 4 90.00 75.00 2108. 15.5 74 2 "fiat 128" +26.0 4 116.0 75.00 2246. 14.0 74 2 "fiat 124 tc" +24.0 4 120.0 97.00 2489. 15.0 74 3 "honda civic" +26.0 4 108.0 93.00 2391. 15.5 74 3 "subaru" +31.0 4 79.00 67.00 2000. 16.0 74 2 "fiat x1.9" +19.0 6 225.0 95.00 3264. 16.0 75 1 "plymouth valiant custom" +18.0 6 250.0 105.0 3459. 16.0 75 1 "chevrolet nova" +15.0 6 250.0 72.00 3432. 21.0 75 1 "mercury monarch" +15.0 6 250.0 72.00 3158. 19.5 75 1 "ford maverick" +16.0 8 400.0 170.0 4668. 11.5 75 1 "pontiac catalina" +15.0 8 350.0 145.0 4440. 14.0 75 1 "chevrolet bel air" +16.0 8 318.0 150.0 4498. 14.5 75 1 "plymouth grand fury" +14.0 8 351.0 148.0 4657. 13.5 75 1 "ford ltd" +17.0 6 231.0 110.0 3907. 21.0 75 1 "buick century" +16.0 6 250.0 105.0 3897. 18.5 75 1 "chevroelt chevelle malibu" +15.0 6 258.0 110.0 3730. 19.0 75 1 "amc matador" +18.0 6 225.0 95.00 3785. 19.0 75 1 "plymouth fury" +21.0 6 231.0 110.0 3039. 15.0 75 1 "buick skyhawk" +20.0 8 262.0 110.0 3221. 13.5 75 1 "chevrolet monza 2+2" +13.0 8 302.0 129.0 3169. 12.0 75 1 "ford mustang ii" +29.0 4 97.00 75.00 2171. 16.0 75 3 "toyota corolla" +23.0 4 140.0 83.00 2639. 17.0 75 1 "ford pinto" +20.0 6 232.0 100.0 2914. 16.0 75 1 "amc gremlin" +23.0 4 140.0 78.00 2592. 18.5 75 1 "pontiac astro" +24.0 4 134.0 96.00 2702. 13.5 75 3 "toyota corona" +25.0 4 90.00 71.00 2223. 16.5 75 2 "volkswagen dasher" +24.0 4 119.0 97.00 2545. 17.0 75 3 "datsun 710" +18.0 6 171.0 97.00 2984. 14.5 75 1 "ford pinto" +29.0 4 90.00 70.00 1937. 14.0 75 2 "volkswagen rabbit" +19.0 6 232.0 90.00 3211. 17.0 75 1 "amc pacer" +23.0 4 115.0 95.00 2694. 15.0 75 2 "audi 100ls" +23.0 4 120.0 88.00 2957. 17.0 75 2 "peugeot 504" +22.0 4 121.0 98.00 2945. 14.5 75 2 "volvo 244dl" +25.0 4 121.0 115.0 2671. 13.5 75 2 "saab 99le" +33.0 4 91.00 53.00 1795. 17.5 75 3 "honda civic cvcc" +28.0 4 107.0 86.00 2464. 15.5 76 2 "fiat 131" +25.0 4 116.0 81.00 2220. 16.9 76 2 "opel 1900" +25.0 4 140.0 92.00 2572. 14.9 76 1 "capri ii" +26.0 4 98.00 79.00 2255. 17.7 76 1 "dodge colt" +27.0 4 101.0 83.00 2202. 15.3 76 2 "renault 12tl" +17.5 8 305.0 140.0 4215. 13.0 76 1 "chevrolet chevelle malibu classic" +16.0 8 318.0 150.0 4190. 13.0 76 1 "dodge coronet brougham" +15.5 8 304.0 120.0 3962. 13.9 76 1 "amc matador" +14.5 8 351.0 152.0 4215. 12.8 76 1 "ford gran torino" +22.0 6 225.0 100.0 3233. 15.4 76 1 "plymouth valiant" +22.0 6 250.0 105.0 3353. 14.5 76 1 "chevrolet nova" +24.0 6 200.0 81.00 3012. 17.6 76 1 "ford maverick" +22.5 6 232.0 90.00 3085. 17.6 76 1 "amc hornet" +29.0 4 85.00 52.00 2035. 22.2 76 1 "chevrolet chevette" +24.5 4 98.00 60.00 2164. 22.1 76 1 "chevrolet woody" +29.0 4 90.00 70.00 1937. 14.2 76 2 "vw rabbit" +33.0 4 91.00 53.00 1795. 17.4 76 3 "honda civic" +20.0 6 225.0 100.0 3651. 17.7 76 1 "dodge aspen se" +18.0 6 250.0 78.00 3574. 21.0 76 1 "ford granada ghia" +18.5 6 250.0 110.0 3645. 16.2 76 1 "pontiac ventura sj" +17.5 6 258.0 95.00 3193. 17.8 76 1 "amc pacer d/l" +29.5 4 97.00 71.00 1825. 12.2 76 2 "volkswagen rabbit" +32.0 4 85.00 70.00 1990. 17.0 76 3 "datsun b-210" +28.0 4 97.00 75.00 2155. 16.4 76 3 "toyota corolla" +26.5 4 140.0 72.00 2565. 13.6 76 1 "ford pinto" +20.0 4 130.0 102.0 3150. 15.7 76 2 "volvo 245" +13.0 8 318.0 150.0 3940. 13.2 76 1 "plymouth volare premier v8" +19.0 4 120.0 88.00 3270. 21.9 76 2 "peugeot 504" +19.0 6 156.0 108.0 2930. 15.5 76 3 "toyota mark ii" +16.5 6 168.0 120.0 3820. 16.7 76 2 "mercedes-benz 280s" +16.5 8 350.0 180.0 4380. 12.1 76 1 "cadillac seville" +13.0 8 350.0 145.0 4055. 12.0 76 1 "chevy c10" +13.0 8 302.0 130.0 3870. 15.0 76 1 "ford f108" +13.0 8 318.0 150.0 3755. 14.0 76 1 "dodge d100" +31.5 4 98.00 68.00 2045. 18.5 77 3 "honda accord cvcc" +30.0 4 111.0 80.00 2155. 14.8 77 1 "buick opel isuzu deluxe" +36.0 4 79.00 58.00 1825. 18.6 77 2 "renault 5 gtl" +25.5 4 122.0 96.00 2300. 15.5 77 1 "plymouth arrow gs" +33.5 4 85.00 70.00 1945. 16.8 77 3 "datsun f-10 hatchback" +17.5 8 305.0 145.0 3880. 12.5 77 1 "chevrolet caprice classic" +17.0 8 260.0 110.0 4060. 19.0 77 1 "oldsmobile cutlass supreme" +15.5 8 318.0 145.0 4140. 13.7 77 1 "dodge monaco brougham" +15.0 8 302.0 130.0 4295. 14.9 77 1 "mercury cougar brougham" +17.5 6 250.0 110.0 3520. 16.4 77 1 "chevrolet concours" +20.5 6 231.0 105.0 3425. 16.9 77 1 "buick skylark" +19.0 6 225.0 100.0 3630. 17.7 77 1 "plymouth volare custom" +18.5 6 250.0 98.00 3525. 19.0 77 1 "ford granada" +16.0 8 400.0 180.0 4220. 11.1 77 1 "pontiac grand prix lj" +15.5 8 350.0 170.0 4165. 11.4 77 1 "chevrolet monte carlo landau" +15.5 8 400.0 190.0 4325. 12.2 77 1 "chrysler cordoba" +16.0 8 351.0 149.0 4335. 14.5 77 1 "ford thunderbird" +29.0 4 97.00 78.00 1940. 14.5 77 2 "volkswagen rabbit custom" +24.5 4 151.0 88.00 2740. 16.0 77 1 "pontiac sunbird coupe" +26.0 4 97.00 75.00 2265. 18.2 77 3 "toyota corolla liftback" +25.5 4 140.0 89.00 2755. 15.8 77 1 "ford mustang ii 2+2" +30.5 4 98.00 63.00 2051. 17.0 77 1 "chevrolet chevette" +33.5 4 98.00 83.00 2075. 15.9 77 1 "dodge colt m/m" +30.0 4 97.00 67.00 1985. 16.4 77 3 "subaru dl" +30.5 4 97.00 78.00 2190. 14.1 77 2 "volkswagen dasher" +22.0 6 146.0 97.00 2815. 14.5 77 3 "datsun 810" +21.5 4 121.0 110.0 2600. 12.8 77 2 "bmw 320i" +21.5 3 80.00 110.0 2720. 13.5 77 3 "mazda rx-4" +43.1 4 90.00 48.00 1985. 21.5 78 2 "volkswagen rabbit custom diesel" +36.1 4 98.00 66.00 1800. 14.4 78 1 "ford fiesta" +32.8 4 78.00 52.00 1985. 19.4 78 3 "mazda glc deluxe" +39.4 4 85.00 70.00 2070. 18.6 78 3 "datsun b210 gx" +36.1 4 91.00 60.00 1800. 16.4 78 3 "honda civic cvcc" +19.9 8 260.0 110.0 3365. 15.5 78 1 "oldsmobile cutlass salon brougham" +19.4 8 318.0 140.0 3735. 13.2 78 1 "dodge diplomat" +20.2 8 302.0 139.0 3570. 12.8 78 1 "mercury monarch ghia" +19.2 6 231.0 105.0 3535. 19.2 78 1 "pontiac phoenix lj" +20.5 6 200.0 95.00 3155. 18.2 78 1 "chevrolet malibu" +20.2 6 200.0 85.00 2965. 15.8 78 1 "ford fairmont (auto)" +25.1 4 140.0 88.00 2720. 15.4 78 1 "ford fairmont (man)" +20.5 6 225.0 100.0 3430. 17.2 78 1 "plymouth volare" +19.4 6 232.0 90.00 3210. 17.2 78 1 "amc concord" +20.6 6 231.0 105.0 3380. 15.8 78 1 "buick century special" +20.8 6 200.0 85.00 3070. 16.7 78 1 "mercury zephyr" +18.6 6 225.0 110.0 3620. 18.7 78 1 "dodge aspen" +18.1 6 258.0 120.0 3410. 15.1 78 1 "amc concord d/l" +19.2 8 305.0 145.0 3425. 13.2 78 1 "chevrolet monte carlo landau" +17.7 6 231.0 165.0 3445. 13.4 78 1 "buick regal sport coupe (turbo)" +18.1 8 302.0 139.0 3205. 11.2 78 1 "ford futura" +17.5 8 318.0 140.0 4080. 13.7 78 1 "dodge magnum xe" +30.0 4 98.00 68.00 2155. 16.5 78 1 "chevrolet chevette" +27.5 4 134.0 95.00 2560. 14.2 78 3 "toyota corona" +27.2 4 119.0 97.00 2300. 14.7 78 3 "datsun 510" +30.9 4 105.0 75.00 2230. 14.5 78 1 "dodge omni" +21.1 4 134.0 95.00 2515. 14.8 78 3 "toyota celica gt liftback" +23.2 4 156.0 105.0 2745. 16.7 78 1 "plymouth sapporo" +23.8 4 151.0 85.00 2855. 17.6 78 1 "oldsmobile starfire sx" +23.9 4 119.0 97.00 2405. 14.9 78 3 "datsun 200-sx" +20.3 5 131.0 103.0 2830. 15.9 78 2 "audi 5000" +17.0 6 163.0 125.0 3140. 13.6 78 2 "volvo 264gl" +21.6 4 121.0 115.0 2795. 15.7 78 2 "saab 99gle" +16.2 6 163.0 133.0 3410. 15.8 78 2 "peugeot 604sl" +31.5 4 89.00 71.00 1990. 14.9 78 2 "volkswagen scirocco" +29.5 4 98.00 68.00 2135. 16.6 78 3 "honda accord lx" +21.5 6 231.0 115.0 3245. 15.4 79 1 "pontiac lemans v6" +19.8 6 200.0 85.00 2990. 18.2 79 1 "mercury zephyr 6" +22.3 4 140.0 88.00 2890. 17.3 79 1 "ford fairmont 4" +20.2 6 232.0 90.00 3265. 18.2 79 1 "amc concord dl 6" +20.6 6 225.0 110.0 3360. 16.6 79 1 "dodge aspen 6" +17.0 8 305.0 130.0 3840. 15.4 79 1 "chevrolet caprice classic" +17.6 8 302.0 129.0 3725. 13.4 79 1 "ford ltd landau" +16.5 8 351.0 138.0 3955. 13.2 79 1 "mercury grand marquis" +18.2 8 318.0 135.0 3830. 15.2 79 1 "dodge st. regis" +16.9 8 350.0 155.0 4360. 14.9 79 1 "buick estate wagon (sw)" +15.5 8 351.0 142.0 4054. 14.3 79 1 "ford country squire (sw)" +19.2 8 267.0 125.0 3605. 15.0 79 1 "chevrolet malibu classic (sw)" +18.5 8 360.0 150.0 3940. 13.0 79 1 "chrysler lebaron town @ country (sw)" +31.9 4 89.00 71.00 1925. 14.0 79 2 "vw rabbit custom" +34.1 4 86.00 65.00 1975. 15.2 79 3 "maxda glc deluxe" +35.7 4 98.00 80.00 1915. 14.4 79 1 "dodge colt hatchback custom" +27.4 4 121.0 80.00 2670. 15.0 79 1 "amc spirit dl" +25.4 5 183.0 77.00 3530. 20.1 79 2 "mercedes benz 300d" +23.0 8 350.0 125.0 3900. 17.4 79 1 "cadillac eldorado" +27.2 4 141.0 71.00 3190. 24.8 79 2 "peugeot 504" +23.9 8 260.0 90.00 3420. 22.2 79 1 "oldsmobile cutlass salon brougham" +34.2 4 105.0 70.00 2200. 13.2 79 1 "plymouth horizon" +34.5 4 105.0 70.00 2150. 14.9 79 1 "plymouth horizon tc3" +31.8 4 85.00 65.00 2020. 19.2 79 3 "datsun 210" +37.3 4 91.00 69.00 2130. 14.7 79 2 "fiat strada custom" +28.4 4 151.0 90.00 2670. 16.0 79 1 "buick skylark limited" +28.8 6 173.0 115.0 2595. 11.3 79 1 "chevrolet citation" +26.8 6 173.0 115.0 2700. 12.9 79 1 "oldsmobile omega brougham" +33.5 4 151.0 90.00 2556. 13.2 79 1 "pontiac phoenix" +41.5 4 98.00 76.00 2144. 14.7 80 2 "vw rabbit" +38.1 4 89.00 60.00 1968. 18.8 80 3 "toyota corolla tercel" +32.1 4 98.00 70.00 2120. 15.5 80 1 "chevrolet chevette" +37.2 4 86.00 65.00 2019. 16.4 80 3 "datsun 310" +28.0 4 151.0 90.00 2678. 16.5 80 1 "chevrolet citation" +26.4 4 140.0 88.00 2870. 18.1 80 1 "ford fairmont" +24.3 4 151.0 90.00 3003. 20.1 80 1 "amc concord" +19.1 6 225.0 90.00 3381. 18.7 80 1 "dodge aspen" +34.3 4 97.00 78.00 2188. 15.8 80 2 "audi 4000" +29.8 4 134.0 90.00 2711. 15.5 80 3 "toyota corona liftback" +31.3 4 120.0 75.00 2542. 17.5 80 3 "mazda 626" +37.0 4 119.0 92.00 2434. 15.0 80 3 "datsun 510 hatchback" +32.2 4 108.0 75.00 2265. 15.2 80 3 "toyota corolla" +46.6 4 86.00 65.00 2110. 17.9 80 3 "mazda glc" +27.9 4 156.0 105.0 2800. 14.4 80 1 "dodge colt" +40.8 4 85.00 65.00 2110. 19.2 80 3 "datsun 210" +44.3 4 90.00 48.00 2085. 21.7 80 2 "vw rabbit c (diesel)" +43.4 4 90.00 48.00 2335. 23.7 80 2 "vw dasher (diesel)" +36.4 5 121.0 67.00 2950. 19.9 80 2 "audi 5000s (diesel)" +30.0 4 146.0 67.00 3250. 21.8 80 2 "mercedes-benz 240d" +44.6 4 91.00 67.00 1850. 13.8 80 3 "honda civic 1500 gl" +40.9 4 85.00 ? 1835. 17.3 80 2 "renault lecar deluxe" +33.8 4 97.00 67.00 2145. 18.0 80 3 "subaru dl" +29.8 4 89.00 62.00 1845. 15.3 80 2 "vokswagen rabbit" +32.7 6 168.0 132.0 2910. 11.4 80 3 "datsun 280-zx" +23.7 3 70.00 100.0 2420. 12.5 80 3 "mazda rx-7 gs" +35.0 4 122.0 88.00 2500. 15.1 80 2 "triumph tr7 coupe" +23.6 4 140.0 ? 2905. 14.3 80 1 "ford mustang cobra" +32.4 4 107.0 72.00 2290. 17.0 80 3 "honda accord" +27.2 4 135.0 84.00 2490. 15.7 81 1 "plymouth reliant" +26.6 4 151.0 84.00 2635. 16.4 81 1 "buick skylark" +25.8 4 156.0 92.00 2620. 14.4 81 1 "dodge aries wagon (sw)" +23.5 6 173.0 110.0 2725. 12.6 81 1 "chevrolet citation" +30.0 4 135.0 84.00 2385. 12.9 81 1 "plymouth reliant" +39.1 4 79.00 58.00 1755. 16.9 81 3 "toyota starlet" +39.0 4 86.00 64.00 1875. 16.4 81 1 "plymouth champ" +35.1 4 81.00 60.00 1760. 16.1 81 3 "honda civic 1300" +32.3 4 97.00 67.00 2065. 17.8 81 3 "subaru" +37.0 4 85.00 65.00 1975. 19.4 81 3 "datsun 210 mpg" +37.7 4 89.00 62.00 2050. 17.3 81 3 "toyota tercel" +34.1 4 91.00 68.00 1985. 16.0 81 3 "mazda glc 4" +34.7 4 105.0 63.00 2215. 14.9 81 1 "plymouth horizon 4" +34.4 4 98.00 65.00 2045. 16.2 81 1 "ford escort 4w" +29.9 4 98.00 65.00 2380. 20.7 81 1 "ford escort 2h" +33.0 4 105.0 74.00 2190. 14.2 81 2 "volkswagen jetta" +34.5 4 100.0 ? 2320. 15.8 81 2 "renault 18i" +33.7 4 107.0 75.00 2210. 14.4 81 3 "honda prelude" +32.4 4 108.0 75.00 2350. 16.8 81 3 "toyota corolla" +32.9 4 119.0 100.0 2615. 14.8 81 3 "datsun 200sx" +31.6 4 120.0 74.00 2635. 18.3 81 3 "mazda 626" +28.1 4 141.0 80.00 3230. 20.4 81 2 "peugeot 505s turbo diesel" +30.7 6 145.0 76.00 3160. 19.6 81 2 "volvo diesel" +25.4 6 168.0 116.0 2900. 12.6 81 3 "toyota cressida" +24.2 6 146.0 120.0 2930. 13.8 81 3 "datsun 810 maxima" +22.4 6 231.0 110.0 3415. 15.8 81 1 "buick century" +26.6 8 350.0 105.0 3725. 19.0 81 1 "oldsmobile cutlass ls" +20.2 6 200.0 88.00 3060. 17.1 81 1 "ford granada gl" +17.6 6 225.0 85.00 3465. 16.6 81 1 "chrysler lebaron salon" +28.0 4 112.0 88.00 2605. 19.6 82 1 "chevrolet cavalier" +27.0 4 112.0 88.00 2640. 18.6 82 1 "chevrolet cavalier wagon" +34.0 4 112.0 88.00 2395. 18.0 82 1 "chevrolet cavalier 2-door" +31.0 4 112.0 85.00 2575. 16.2 82 1 "pontiac j2000 se hatchback" +29.0 4 135.0 84.00 2525. 16.0 82 1 "dodge aries se" +27.0 4 151.0 90.00 2735. 18.0 82 1 "pontiac phoenix" +24.0 4 140.0 92.00 2865. 16.4 82 1 "ford fairmont futura" +36.0 4 105.0 74.00 1980. 15.3 82 2 "volkswagen rabbit l" +37.0 4 91.00 68.00 2025. 18.2 82 3 "mazda glc custom l" +31.0 4 91.00 68.00 1970. 17.6 82 3 "mazda glc custom" +38.0 4 105.0 63.00 2125. 14.7 82 1 "plymouth horizon miser" +36.0 4 98.00 70.00 2125. 17.3 82 1 "mercury lynx l" +36.0 4 120.0 88.00 2160. 14.5 82 3 "nissan stanza xe" +36.0 4 107.0 75.00 2205. 14.5 82 3 "honda accord" +34.0 4 108.0 70.00 2245 16.9 82 3 "toyota corolla" +38.0 4 91.00 67.00 1965. 15.0 82 3 "honda civic" +32.0 4 91.00 67.00 1965. 15.7 82 3 "honda civic (auto)" +38.0 4 91.00 67.00 1995. 16.2 82 3 "datsun 310 gx" +25.0 6 181.0 110.0 2945. 16.4 82 1 "buick century limited" +38.0 6 262.0 85.00 3015. 17.0 82 1 "oldsmobile cutlass ciera (diesel)" +26.0 4 156.0 92.00 2585. 14.5 82 1 "chrysler lebaron medallion" +22.0 6 232.0 112.0 2835 14.7 82 1 "ford granada l" +32.0 4 144.0 96.00 2665. 13.9 82 3 "toyota celica gt" +36.0 4 135.0 84.00 2370. 13.0 82 1 "dodge charger 2.2" +27.0 4 151.0 90.00 2950. 17.3 82 1 "chevrolet camaro" +27.0 4 140.0 86.00 2790. 15.6 82 1 "ford mustang gl" +44.0 4 97.00 52.00 2130. 24.6 82 2 "vw pickup" +32.0 4 135.0 84.00 2295. 11.6 82 1 "dodge rampage" +28.0 4 120.0 79.00 2625. 18.6 82 1 "ford ranger" +31.0 4 119.0 82.00 2720. 19.4 82 1 "chevy s-10" diff --git a/datasets/Boston.csv b/datasets/Boston.csv new file mode 100644 index 0000000..8c2d22a --- /dev/null +++ b/datasets/Boston.csv @@ -0,0 +1,507 @@ +"","crim","zn","indus","chas","nox","rm","age","dis","rad","tax","ptratio","black","lstat","medv" +"1",0.00632,18,2.31,0,0.538,6.575,65.2,4.09,1,296,15.3,396.9,4.98,24 +"2",0.02731,0,7.07,0,0.469,6.421,78.9,4.9671,2,242,17.8,396.9,9.14,21.6 +"3",0.02729,0,7.07,0,0.469,7.185,61.1,4.9671,2,242,17.8,392.83,4.03,34.7 +"4",0.03237,0,2.18,0,0.458,6.998,45.8,6.0622,3,222,18.7,394.63,2.94,33.4 +"5",0.06905,0,2.18,0,0.458,7.147,54.2,6.0622,3,222,18.7,396.9,5.33,36.2 +"6",0.02985,0,2.18,0,0.458,6.43,58.7,6.0622,3,222,18.7,394.12,5.21,28.7 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+-1.465006,2.034465,0.4408494,-0.5304421,1.075337,0.2981279,2.515097,0.191902,0.3253761,0.7907912,-0.3074093,-1.445376,-0.4621784,0.2865637,-0.000340997,-0.2713901,0.9863574,0.493799,-0.1435576,1.882245,0.6516502,-1.494485,-0.8857061,0.826793,-0.07812493,1.152476,0.8536542,0.4022551,0.2391626,1.045731,-1.421523,-0.3110446,0.9141036,-1.549967,1.324033,1.027569,0.4646951,-1.259852,0.7379093,0.9574745 +1.075148,3.003267,-0.1234407,-1.03674,-1.270604,-1.277029,-0.2785037,1.249723,-0.7069937,-0.7046713,0.1374137,-0.545526,1.237348,-0.1151673,-0.1885763,-0.3354451,-1.039042,2.098071,1.189881,-0.4883022,-1.131076,0.5326998,1.715767,-0.5847613,-1.416804,-0.9343693,-0.825359,-0.09631337,-0.5033496,-0.2163598,0.8421608,-0.7621541,0.5468812,1.586981,-0.2420434,0.5071895,1.297424,0.3142901,-1.513097,-0.07470855 +-1.226125,-0.5017017,-0.7174301,-0.1691128,0.5995296,-0.9979873,0.0282364,0.2005076,-1.364865,0.5649572,0.03299788,-1.902298,-0.4371406,-1.046251,0.6651386,-0.4431168,0.1799518,-0.5040884,-0.2979136,1.380388,-1.166284,1.143079,0.4112727,1.201187,0.2153674,-0.07230739,-0.1710817,-0.5238425,1.125239,-1.952056,-1.012523,0.5932517,-0.5945063,-1.443559,-0.02887016,0.05217033,-0.8672269,0.2285312,-0.2077585,-0.2096647 +-3.056328,0.4498887,1.880362,-0.742841,2.238346,-0.2917377,1.270233,0.6964153,1.242857,0.429148,1.56024,1.698944,-2.109933,-0.8072399,-1.146654,-2.11941,-1.382769,0.9753073,-0.8158415,-1.797123,1.583854,1.546694,1.932612,-1.480001,-0.7217243,0.1664868,0.7904981,-0.2317101,-1.906912,-0.718626,0.135085,-0.7320773,-0.03746764,-0.8366888,0.02027417,-0.8033058,-0.9072765,-0.781791,0.06990843,1.336894 +1.450658,1.310348,0.3838369,-0.4088601,-0.4711108,-1.392396,-0.8058084,0.2109001,1.727079,0.8628701,0.8207546,-0.7488937,1.560224,-0.5095834,1.071049,-0.9695467,-1.436005,0.4245734,-0.688211,-0.4130026,-0.3670095,-2.349555,1.323857,-0.7776493,-0.05239478,1.011977,1.719617,-0.5714752,1.165922,1.456871,0.1090179,-0.1285215,0.8602701,0.7650145,-2.36009,0.2526993,-1.461818,-0.8123422,-1.095099,-1.460114 +0.7179769,0.7634819,0.313576,-0.3264731,-0.1587002,0.468113,0.5191607,-0.4270991,2.759068,-2.571514,-1.037164,-1.530438,1.692381,0.3000961,-0.6435787,0.0567591,-1.265215,0.2781767,-0.499156,-0.4427016,1.20461,0.3110264,-0.8861183,-0.2463007,-0.8881552,-0.4879487,0.9232075,-0.5642434,0.1745982,-0.3590661,-1.105732,-0.8769501,-0.2987923,-0.5761456,-1.19678,0.4090315,-0.03228221,-0.5620644,-0.315811,0.1928633 diff --git a/datasets/College.csv b/datasets/College.csv new file mode 100644 index 0000000..b644848 --- /dev/null +++ b/datasets/College.csv @@ -0,0 +1,778 @@ +,Private,Apps,Accept,Enroll,Top10perc,Top25perc,F.Undergrad,P.Undergrad,Outstate,Room.Board,Books,Personal,PhD,Terminal,S.F.Ratio,perc.alumni,Expend,Grad.Rate +Abilene Christian University,Yes,1660,1232,721,23,52,2885,537,7440,3300,450,2200,70,78,18.1,12,7041,60 +Adelphi University,Yes,2186,1924,512,16,29,2683,1227,12280,6450,750,1500,29,30,12.2,16,10527,56 +Adrian College,Yes,1428,1097,336,22,50,1036,99,11250,3750,400,1165,53,66,12.9,30,8735,54 +Agnes Scott College,Yes,417,349,137,60,89,510,63,12960,5450,450,875,92,97,7.7,37,19016,59 +Alaska Pacific University,Yes,193,146,55,16,44,249,869,7560,4120,800,1500,76,72,11.9,2,10922,15 +Albertson College,Yes,587,479,158,38,62,678,41,13500,3335,500,675,67,73,9.4,11,9727,55 +Albertus Magnus College,Yes,353,340,103,17,45,416,230,13290,5720,500,1500,90,93,11.5,26,8861,63 +Albion College,Yes,1899,1720,489,37,68,1594,32,13868,4826,450,850,89,100,13.7,37,11487,73 +Albright College,Yes,1038,839,227,30,63,973,306,15595,4400,300,500,79,84,11.3,23,11644,80 +Alderson-Broaddus College,Yes,582,498,172,21,44,799,78,10468,3380,660,1800,40,41,11.5,15,8991,52 +Alfred University,Yes,1732,1425,472,37,75,1830,110,16548,5406,500,600,82,88,11.3,31,10932,73 +Allegheny College,Yes,2652,1900,484,44,77,1707,44,17080,4440,400,600,73,91,9.9,41,11711,76 +Allentown Coll. of St. Francis de Sales,Yes,1179,780,290,38,64,1130,638,9690,4785,600,1000,60,84,13.3,21,7940,74 +Alma College,Yes,1267,1080,385,44,73,1306,28,12572,4552,400,400,79,87,15.3,32,9305,68 +Alverno College,Yes,494,313,157,23,46,1317,1235,8352,3640,650,2449,36,69,11.1,26,8127,55 +American International College,Yes,1420,1093,220,9,22,1018,287,8700,4780,450,1400,78,84,14.7,19,7355,69 +Amherst College,Yes,4302,992,418,83,96,1593,5,19760,5300,660,1598,93,98,8.4,63,21424,100 +Anderson University,Yes,1216,908,423,19,40,1819,281,10100,3520,550,1100,48,61,12.1,14,7994,59 +Andrews University,Yes,1130,704,322,14,23,1586,326,9996,3090,900,1320,62,66,11.5,18,10908,46 +Angelo State University,No,3540,2001,1016,24,54,4190,1512,5130,3592,500,2000,60,62,23.1,5,4010,34 +Antioch University,Yes,713,661,252,25,44,712,23,15476,3336,400,1100,69,82,11.3,35,42926,48 +Appalachian State University,No,7313,4664,1910,20,63,9940,1035,6806,2540,96,2000,83,96,18.3,14,5854,70 +Aquinas College,Yes,619,516,219,20,51,1251,767,11208,4124,350,1615,55,65,12.7,25,6584,65 +Arizona State University Main campus,No,12809,10308,3761,24,49,22593,7585,7434,4850,700,2100,88,93,18.9,5,4602,48 +Arkansas College (Lyon College),Yes,708,334,166,46,74,530,182,8644,3922,500,800,79,88,12.6,24,14579,54 +Arkansas Tech University,No,1734,1729,951,12,52,3602,939,3460,2650,450,1000,57,60,19.6,5,4739,48 +Assumption College,Yes,2135,1700,491,23,59,1708,689,12000,5920,500,500,93,93,13.8,30,7100,88 +Auburn University-Main Campus,No,7548,6791,3070,25,57,16262,1716,6300,3933,600,1908,85,91,16.7,18,6642,69 +Augsburg College,Yes,662,513,257,12,30,2074,726,11902,4372,540,950,65,65,12.8,31,7836,58 +Augustana College IL,Yes,1879,1658,497,36,69,1950,38,13353,4173,540,821,78,83,12.7,40,9220,71 +Augustana College,Yes,761,725,306,21,58,1337,300,10990,3244,600,1021,66,70,10.4,30,6871,69 +Austin College,Yes,948,798,295,42,74,1120,15,11280,4342,400,1150,81,95,13,33,11361,71 +Averett College,Yes,627,556,172,16,40,777,538,9925,4135,750,1350,59,67,22.4,11,6523,48 +Baker University,Yes,602,483,206,21,47,958,466,8620,4100,400,2250,58,68,11,21,6136,65 +Baldwin-Wallace College,Yes,1690,1366,662,30,61,2718,1460,10995,4410,1000,1000,68,74,17.6,20,8086,85 +Barat College,Yes,261,192,111,15,36,453,266,9690,4300,500,500,57,77,9.7,35,9337,71 +Bard College,Yes,1910,838,285,50,85,1004,15,19264,6206,750,750,98,98,10.4,30,13894,79 +Barnard College,Yes,2496,1402,531,53,95,2121,69,17926,8124,600,850,83,93,10.3,33,12580,91 +Barry University,Yes,990,784,279,18,45,1811,3144,11290,5360,600,1800,76,78,12.6,11,9084,72 +Baylor University,Yes,6075,5349,2367,34,66,9919,484,6450,3920,600,1346,71,76,18.5,38,7503,72 +Beaver College,Yes,1163,850,348,23,56,878,519,12850,5400,400,800,78,89,12.2,30,8954,73 +Bellarmine College,Yes,807,707,308,39,63,1198,605,8840,2950,750,1290,74,82,13.1,31,6668,84 +Belmont Abbey College,Yes,632,494,129,17,36,709,131,9000,4850,300,2480,78,85,13.2,10,7550,52 +Belmont University,Yes,1220,974,481,28,67,1964,623,7800,3664,650,900,61,61,11.1,19,7614,49 +Beloit College,Yes,1320,923,284,26,54,1085,81,16304,3616,355,715,87,95,11.1,26,12957,69 +Bemidji State University,No,1208,877,546,12,36,3796,824,4425,2700,660,1800,57,62,19.6,16,3752,46 +Benedictine College,Yes,632,620,222,14,24,702,501,9550,3850,350,250,64,84,14.1,18,5922,58 +Bennington College,Yes,519,327,114,25,53,457,2,21700,4100,600,500,35,59,10.1,33,16364,55 +Bentley College,Yes,3466,2330,640,20,60,3095,1533,13800,5510,630,850,87,87,17.5,20,10941,82 +Berry College,Yes,1858,1221,480,37,68,1620,49,8050,3940,350,2375,80,80,16.3,17,10511,63 +Bethany College,Yes,878,816,200,16,41,706,62,8740,3363,550,1700,62,68,11.6,29,7718,48 +Bethel College KS,Yes,202,184,122,19,42,537,101,8540,3580,500,1400,61,80,8.8,32,8324,56 +Bethel College,Yes,502,384,104,11,28,347,74,6200,2900,600,800,63,63,11.7,13,7623,35 +Bethune Cookman College,Yes,1646,1150,542,12,30,2128,82,5188,3396,650,2500,48,48,13.8,9,6817,58 +Birmingham-Southern College,Yes,805,588,287,67,88,1376,207,11660,4325,400,900,74,79,14,34,8649,72 +Blackburn College,Yes,500,336,156,25,55,421,27,6500,2700,500,1000,76,76,14.3,53,8377,51 +Bloomsburg Univ. of Pennsylvania,No,6773,3028,1025,15,55,5847,946,7844,2948,500,1680,66,68,18,19,7041,75 +Bluefield College,Yes,377,358,181,15,30,653,129,7150,4350,450,1500,61,67,17.8,3,6259,53 +Bluffton College,Yes,692,514,209,20,50,760,81,9900,3990,400,900,76,71,13.3,19,9073,58 +Boston University,Yes,20192,13007,3810,45,80,14971,3113,18420,6810,475,1025,80,81,11.9,16,16836,72 +Bowdoin College,Yes,3356,1019,418,76,100,1490,8,19030,5885,1495,875,93,96,11.2,52,20447,96 +Bowling Green State University,No,9251,7333,3076,14,45,13699,1213,7452,3352,600,1700,81,89,21.1,14,6918,67 +Bradford College,Yes,443,330,151,5,36,453,42,14080,6270,500,900,57,80,10.2,21,15387,46 +Bradley University,Yes,3767,3414,1061,30,58,4531,643,10870,4440,2000,1522,75,81,14.4,21,7671,85 +Brandeis University,Yes,4186,2743,740,48,77,2819,62,19380,6750,410,1000,90,97,9.8,24,17150,84 +Brenau University,Yes,367,274,158,12,41,917,479,9592,5879,500,700,71,80,13.7,12,5935,49 +Brewton-Parker College,Yes,1436,1228,1202,10,26,1320,822,4371,2370,500,2000,62,62,12.6,10,4900,18 +Briar Cliff College,Yes,392,351,155,16,44,738,430,10260,3597,600,1500,39,66,13.1,26,8355,58 +Bridgewater College,Yes,838,673,292,22,53,881,55,10265,4725,560,875,68,73,13.2,24,8655,82 +Brigham Young University at Provo,Yes,7365,5402,4615,48,82,27378,1253,2340,3580,860,1220,76,76,20.5,40,7916,33 +Brown University,Yes,12586,3239,1462,87,95,5643,349,19528,5926,720,1100,99,100,7.6,39,20440,97 +Bryn Mawr College,Yes,1465,810,313,71,95,1088,16,18165,6750,500,1200,100,100,12.3,49,17449,89 +Bucknell University,Yes,6548,3813,862,49,85,3316,31,18550,4750,800,1200,95,97,14.2,36,13675,93 +Buena Vista College,Yes,860,688,285,32,70,1928,442,13306,3797,450,950,62,69,8.8,10,6333,78 +Butler University,Yes,2362,2037,700,40,68,2607,148,13130,4650,500,1600,77,81,10.9,29,9511,83 +Cabrini College,Yes,599,494,224,8,28,1035,446,10518,6250,300,300,59,76,16.5,36,7117,71 +Caldwell College,Yes,1011,604,213,17,42,693,868,8900,4600,425,1000,87,96,13.9,25,7922,55 +California Lutheran University,Yes,563,247,247,23,52,1427,432,12950,5300,612,576,72,74,12.4,17,8985,60 +California Polytechnic-San Luis,No,7811,3817,1650,47,73,12911,1404,7380,4877,612,2091,72,81,19.8,13,8453,59 +California State University at Fresno,No,4540,3294,1483,5,60,13494,1254,7706,4368,600,1926,90,90,21.2,8,7268,61 +Calvin College,Yes,1784,1512,913,29,56,3401,136,10230,3710,400,1210,75,81,14.8,41,7786,81 +Campbell University,Yes,2087,1339,657,20,54,3191,1204,7550,2790,600,500,77,77,21.8,34,3739,63 +Campbellsville College,Yes,848,587,298,25,55,935,184,6060,3070,600,1300,62,66,17.7,13,5391,49 +Canisius College,Yes,2853,2193,753,16,34,2978,434,10750,5340,400,1130,90,92,14.6,26,7972,64 +Capital University,Yes,1747,1382,449,34,66,1662,960,13050,4000,500,800,64,69,12.1,27,9557,83 +Capitol College,Yes,100,90,35,10,52,282,331,8400,2812,300,2134,10,50,12.1,24,7976,52 +Carleton College,Yes,2694,1579,489,75,93,1870,12,19292,3957,550,550,81,93,10.4,60,17960,91 +Carnegie Mellon University,Yes,8728,5201,1191,60,89,4265,291,17900,5690,450,1250,86,93,9.2,31,24386,74 +Carroll College,Yes,1160,991,352,19,55,1357,737,12200,3880,480,930,74,81,17.8,25,7666,79 +Carson-Newman College,Yes,1096,951,464,27,62,1776,239,8150,3150,400,500,61,62,13.6,16,6716,67 +Carthage College,Yes,1616,1427,434,20,43,1405,580,13125,3775,500,1300,74,89,15.9,22,7364,62 +Case Western Reserve University,Yes,3877,3156,713,71,93,3051,513,15700,4730,525,1460,95,95,2.9,29,19733,67 +Castleton State College,No,1257,940,363,9,22,1547,294,7656,4690,400,700,89,91,14.7,8,6318,79 +Catawba College,Yes,1083,880,291,13,34,915,80,9270,4100,600,1860,75,82,13.5,27,8425,55 +Catholic University of America,Yes,1754,1465,505,24,49,2159,211,13712,6408,526,1100,90,96,9.3,18,12751,75 +Cazenovia College,Yes,3847,3433,527,9,35,1010,12,9384,4840,600,500,22,47,14.3,20,7697,118 +Cedar Crest College,Yes,776,607,198,25,58,791,764,14340,5285,500,1000,58,83,11.7,39,10961,74 +Cedarville College,Yes,1307,1090,616,25,55,2196,82,7344,4410,570,1000,50,52,15.3,34,6897,64 +Centenary College,Yes,369,312,90,12,46,396,526,11400,5400,500,760,41,85,9.5,20,9583,24 +Centenary College of Louisiana,Yes,495,434,210,35,55,775,44,8950,3490,600,1900,86,92,11.3,25,9685,66 +Center for Creative Studies,Yes,601,396,203,1,20,525,323,11230,6643,2340,620,8,58,6.8,4,13025,47 +Central College,Yes,1283,1113,401,31,65,1355,40,10938,3660,650,600,76,90,13.5,29,8444,67 +Central Connecticut State University,No,4158,2532,902,6,24,6394,3881,5962,4444,500,985,69,73,16.7,4,4900,49 +Central Missouri State University,No,4681,4101,1436,10,35,8094,1596,4620,3288,300,2250,69,80,19.7,4,5501,50 +Central Washington University,No,2785,2011,1007,8,65,6507,898,7242,3603,654,1416,67,89,18.1,0,6413,51 +Central Wesleyan College,Yes,174,146,88,8,29,1047,33,8300,3080,600,600,62,62,15.2,18,3365,58 +Centre College,Yes,1013,888,288,55,82,943,7,11850,4270,600,900,95,99,11.4,60,13118,74 +Chapman University,Yes,959,771,351,23,48,1662,209,16624,5895,600,1100,72,80,12.8,6,12692,47 +Chatham College,Yes,212,197,91,28,56,471,148,13500,5230,400,850,95,98,9.3,37,16095,52 +Chestnut Hill College,Yes,342,254,126,25,64,518,232,10335,5015,700,850,71,71,8.3,29,7729,73 +Christendom College,Yes,81,72,51,33,71,139,3,8730,3600,400,800,92,92,9.3,17,10922,58 +Christian Brothers University,Yes,880,520,224,16,42,1068,364,9300,3260,600,900,81,81,11.1,24,8129,63 +Christopher Newport University,No,883,766,428,3,37,2910,1749,7860,4750,525,1889,80,82,21.2,16,4639,48 +Claflin College,Yes,1196,697,499,21,47,959,13,4412,2460,500,1000,69,69,16.9,31,7083,21 +Claremont McKenna College,Yes,1860,767,227,71,93,887,1,17000,6010,500,850,99,99,9.6,52,18443,87 +Clark University,Yes,2887,2059,457,30,61,1928,296,17500,4200,500,950,94,95,10.5,35,11951,79 +Clarke College,Yes,460,340,167,14,45,604,350,10740,3676,350,900,67,71,11,27,7963,74 +Clarkson University,Yes,2174,1953,557,35,68,2332,53,15960,5580,700,1300,95,95,15.8,32,11659,77 +Clemson University,No,8065,5257,2301,37,65,11755,770,8116,3610,800,1618,82,88,18,17,7597,73 +Clinch Valley Coll. of the Univ. of Virginia,No,689,561,250,15,30,1125,422,7168,3689,600,1900,67,67,18.1,9,4417,46 +Coe College,Yes,1006,742,275,29,60,1127,205,13925,4390,500,2200,73,86,12.7,32,10141,67 +Coker College,Yes,604,452,295,15,47,690,222,9888,4502,400,1000,64,77,12.1,39,8741,75 +Colby College,Yes,2848,1319,456,58,84,1720,35,18930,5590,500,1000,83,94,10.2,41,15954,91 +Colgate University,Yes,4856,2492,727,46,75,2649,25,19510,5565,500,750,95,98,10.5,45,15494,93 +College Misericordia,Yes,1432,888,317,29,58,1121,493,10860,5760,550,900,56,62,12.9,23,8604,96 +College of Charleston,No,4772,3140,1265,22,55,6851,1200,6120,3460,666,2316,73,78,17.2,18,4776,51 +College of Mount St. Joseph,Yes,798,620,238,14,41,1165,1232,9800,4430,400,1150,46,46,11.1,35,6889,100 +College of Mount St. Vincent,Yes,946,648,177,23,46,707,432,11790,5770,500,1000,75,77,11.9,35,10015,83 +College of Notre Dame,Yes,344,264,97,11,42,500,331,12600,5520,630,2250,77,80,10.4,7,9773,43 +College of Notre Dame of Maryland,Yes,457,356,177,35,61,667,1983,11180,5620,600,700,64,64,11.5,32,7477,75 +College of Saint Benedict,Yes,938,864,511,29,62,1715,103,12247,4221,500,600,70,88,13.1,26,8847,72 +College of Saint Catherine,Yes,511,411,186,23,51,1692,562,12224,4440,450,1000,63,87,11.5,32,7315,77 +College of Saint Elizabeth,Yes,444,359,122,34,53,493,968,10900,5250,380,1000,68,70,11.4,23,9447,78 +College of Saint Rose,Yes,983,664,249,23,57,1698,894,9990,5666,800,1500,66,71,14.3,28,6084,64 +College of Santa Fe,Yes,546,447,189,16,42,873,683,11138,4138,600,1200,40,74,14,7,8820,80 +College of St. Joseph,Yes,141,118,55,12,21,201,173,8300,4850,450,1300,53,53,9.5,19,6936,76 +College of St. Scholastica,Yes,672,596,278,29,60,1350,275,11844,3696,450,1146,54,76,11.6,33,8996,72 +College of the Holy Cross,Yes,2994,1691,659,70,95,2675,22,18000,6300,400,900,92,96,11.3,55,12138,95 +College of William and Mary,No,7117,3106,1217,68,88,5186,134,11720,4298,600,800,89,92,12.1,31,9534,93 +College of Wooster,Yes,2100,1883,553,29,65,1704,1,16240,4690,500,500,84,96,11.1,43,14140,69 +Colorado College,Yes,3207,1577,490,56,87,1892,7,17142,4190,450,1200,85,97,11.3,51,14664,84 +Colorado State University,No,9478,6312,2194,29,65,15646,1829,8412,4180,470,1800,87,89,19.2,10,7850,59 +Columbia College MO,Yes,314,158,132,10,28,690,5346,8294,3700,400,900,87,87,15.3,2,5015,37 +Columbia College,Yes,737,614,242,21,67,968,237,10425,3975,500,1500,61,77,14.7,34,8693,76 +Columbia University,Yes,6756,1930,871,78,96,3376,55,18624,6664,550,300,97,98,5.9,21,30639,99 +Concordia College at St. Paul,Yes,281,266,139,13,29,1049,181,10500,3750,450,950,69,75,12.8,18,6955,45 +Concordia Lutheran College,Yes,232,216,106,16,34,534,172,6900,3800,450,1825,67,76,12.1,9,6875,42 +Concordia University CA,Yes,688,497,144,30,75,641,101,10800,4440,570,1515,55,60,13.1,13,8415,55 +Concordia University,Yes,528,403,186,22,56,1168,145,9216,4191,400,1000,56,64,12.1,13,7309,75 +Connecticut College,Yes,3035,1546,438,42,93,1630,232,18740,6300,600,500,86,95,10.7,40,14773,91 +Converse College,Yes,440,407,149,35,70,643,80,12050,3700,500,900,63,76,10.2,31,10965,75 +Cornell College,Yes,1538,1329,383,33,68,1140,10,15248,4323,550,800,71,76,12.2,31,10340,64 +Creighton University,Yes,2967,2836,876,30,60,3450,644,10628,4372,650,2055,85,90,6.5,32,22906,85 +Culver-Stockton College,Yes,1576,1110,274,24,55,992,112,8000,3700,400,500,51,52,14.1,28,5807,51 +Cumberland College,Yes,995,789,398,26,47,1306,122,6230,3526,400,600,42,44,13,4,8189,63 +D'Youville College,Yes,866,619,157,18,47,1074,336,8920,4310,680,1320,68,68,14.6,42,6898,46 +Dana College,Yes,504,482,185,10,36,550,84,9130,3322,450,1450,46,51,12.6,25,8686,54 +Daniel Webster College,Yes,585,508,153,12,30,460,536,12292,4934,500,500,61,61,22.2,10,8643,72 +Dartmouth College,Yes,8587,2273,1087,87,99,3918,32,19545,6070,550,1100,95,99,4.7,49,29619,98 +Davidson College,Yes,2373,956,452,77,96,1601,6,17295,5070,600,1011,95,97,12,46,17581,94 +Defiance College,Yes,571,461,174,10,26,645,283,10850,3670,400,1159,58,60,12.8,19,7505,56 +Delta State University,No,967,945,459,15,48,2806,538,4528,1880,500,1200,49,63,17.1,16,5113,58 +Denison University,Yes,2762,2279,533,32,60,1835,14,16900,4720,500,600,88,97,11.6,45,12423,81 +DePauw University,Yes,1994,1656,495,50,80,1983,36,14300,5020,550,950,78,94,11.1,31,11525,82 +Dickinson College,Yes,3014,2539,487,31,68,1889,62,18700,5000,595,1250,87,94,11.2,39,13861,87 +Dickinson State University,No,434,412,319,10,30,1376,237,4486,2146,600,2000,50,64,16.5,28,4525,46 +Dillard University,Yes,1998,1376,651,41,88,1539,45,6700,3650,500,2307,52,52,14.1,12,7566,61 +Doane College,Yes,793,709,244,20,47,1022,411,9570,3000,400,1000,67,72,15.1,42,6852,60 +Dominican College of Blauvelt,Yes,360,329,108,4,19,756,863,8310,5500,600,1800,43,43,12.7,5,5480,54 +Dordt College,Yes,604,562,328,25,50,1048,56,9800,2650,450,2800,61,60,12.5,17,7325,87 +Dowling College,Yes,1011,829,410,9,33,1059,2458,9000,3100,450,1413,77,78,12.4,7,11178,42 +Drake University,Yes,2799,2573,839,34,65,3322,726,13420,4770,560,1675,88,93,15,24,9473,77 +Drew University,Yes,2153,1580,321,56,84,1192,87,18432,5616,520,660,93,97,10.2,28,14907,83 +Drury College,Yes,700,650,314,33,66,1065,48,8730,3523,500,750,82,92,13.2,35,9303,67 +Duke University,Yes,13789,3893,1583,90,98,6188,53,18590,5950,625,1162,95,96,5,44,27206,97 +Earlham College,Yes,1358,1006,274,35,63,1028,13,15036,4056,600,600,90,94,10.6,46,14634,78 +East Carolina University,No,9274,6362,2435,14,44,13171,1687,7248,3240,500,1700,74,78,13.2,18,9002,58 +East Tennessee State University,No,3330,2730,1303,15,36,6706,2640,5800,3000,600,2200,73,75,14,9,9825,42 +East Texas Baptist University,Yes,379,341,265,10,36,1050,151,4950,2780,530,1500,62,62,15.7,7,5619,38 +Eastern College,Yes,458,369,165,16,42,1057,355,11190,4800,450,1230,60,60,13.6,22,8135,54 +Eastern Connecticut State University,No,2172,1493,564,14,50,2766,1531,5962,4316,650,500,71,76,16.9,14,5719,50 +Eastern Illinois University,No,5597,4253,1565,12,38,9161,845,5710,3066,120,1730,62,71,16.2,5,5682,76 +Eastern Mennonite College,Yes,486,440,227,19,48,903,59,9650,3800,600,1300,46,65,11.4,29,10188,82 +Eastern Nazarene College,Yes,516,409,200,17,40,1238,30,8770,3500,450,700,58,58,17.3,17,6430,70 +Eckerd College,Yes,1422,1109,366,33,65,1363,23,15360,4080,600,1000,82,89,12.8,26,15003,59 +Elizabethtown College,Yes,2417,1843,426,36,70,1476,299,14190,4400,500,750,65,68,12.8,25,9815,81 +Elmira College,Yes,1457,1045,345,27,50,1109,502,14990,4980,450,550,77,98,21.5,21,7502,64 +Elms College,Yes,245,208,125,23,46,544,436,11800,4765,450,1700,71,71,11.3,21,8952,86 +Elon College,Yes,3624,2786,858,11,39,2933,334,9100,3883,490,1777,70,74,18.9,34,6329,63 +Embry Riddle Aeronautical University,Yes,3151,2584,958,14,40,4772,856,7800,3750,570,3020,37,43,16.5,4,12878,44 +Emory & Henry College,Yes,765,646,226,30,60,809,32,8578,4408,700,1600,79,88,13.9,51,8061,82 +Emory University,Yes,8506,4168,1236,76,97,5544,192,17600,6000,600,870,97,98,5,28,28457,96 +Emporia State University,No,1256,1256,853,43,79,3957,588,5401,3144,450,1888,72,75,19.3,4,5527,50 +Erskine College,Yes,659,557,167,47,74,532,35,10485,3840,475,1246,76,80,13.5,47,7527,67 +Eureka College,Yes,560,454,113,36,56,484,16,10955,3450,330,670,62,87,10.6,31,9552,53 +Evergreen State College,No,1801,1101,438,14,50,3065,363,6297,4600,600,1323,75,78,18.1,14,8355,68 +Fairfield University,Yes,4784,3346,781,30,66,2984,1037,15000,6200,700,1100,86,90,15.1,30,11220,94 +Fayetteville State University,No,1455,1064,452,1,16,2632,617,6806,2550,350,766,75,75,15.1,10,6972,24 +Ferrum College,Yes,1339,1107,336,12,36,1051,82,9400,4200,500,1600,53,58,12.5,9,7967,22 +Flagler College,Yes,1415,714,338,18,52,1345,44,5120,3200,500,2140,52,60,18.1,9,3930,69 +Florida Institute of Technology,Yes,1947,1580,523,39,74,1863,233,13900,4140,750,1500,90,90,10.6,7,8923,57 +Florida International University,No,3306,2079,1071,42,89,10208,9310,6597,2494,800,3028,81,96,13.9,20,6722,66 +Florida Southern College,Yes,1381,1040,374,20,44,1506,970,8025,4865,400,650,65,74,17.4,10,6339,68 +Florida State University,No,11651,8683,3023,50,90,18906,3242,6680,4060,600,1020,80,89,23.1,15,7250,58 +Fontbonne College,Yes,291,245,126,16,49,981,337,8390,4100,350,1500,45,55,21.5,24,4607,62 +Fordham University,Yes,4200,2874,942,30,55,4740,1646,14235,6965,600,1735,86,97,14.4,14,10864,80 +Fort Lewis College,No,3440,2823,1123,16,35,3793,486,6198,3320,500,2500,89,97,19.1,6,4362,46 +Francis Marion University,No,1801,1655,819,13,38,3224,436,5840,3138,400,2430,76,76,19.1,8,5039,43 +Franciscan University of Steubenville,Yes,553,452,228,22,49,1301,242,9650,4400,600,1000,57,69,14.9,8,6336,83 +Franklin College,Yes,804,632,281,29,72,840,68,10390,4040,525,1345,54,78,12.5,37,11751,60 +Franklin Pierce College,Yes,5187,4471,446,3,14,1818,1197,13320,4630,500,800,50,56,17.6,16,6418,51 +Freed-Hardeman University,Yes,895,548,314,20,54,1174,50,5500,3340,600,1600,68,76,16.1,13,6078,62 +Fresno Pacific College,Yes,346,274,146,51,87,704,63,9900,3670,630,1818,59,59,10.5,14,8095,54 +Furman University,Yes,2161,1951,685,56,82,2371,175,13440,4048,600,1250,92,95,13.5,28,12940,82 +Gannon University,Yes,2464,1908,678,24,57,2693,691,10970,4280,500,1380,47,51,13.3,18,7711,65 +Gardner Webb University,Yes,1110,930,332,18,36,1603,374,8180,4270,500,500,65,58,15.2,12,5664,29 +Geneva College,Yes,668,534,237,19,39,1306,258,9476,4820,500,1100,67,67,20.1,26,6786,74 +George Fox College,Yes,809,726,294,27,52,1271,43,12500,4130,400,1050,53,53,13.5,22,7136,52 +George Mason University,No,5653,4326,1727,17,29,9528,3822,10800,4840,580,1050,93,96,19.3,7,6751,46 +George Washington University,Yes,7875,5062,1492,38,71,5471,1470,17450,6328,700,950,92,93,7.6,15,14745,72 +Georgetown College,Yes,727,693,286,30,55,1063,48,8100,3950,550,550,73,76,13.3,28,7508,55 +Georgetown University,Yes,11115,2881,1390,71,93,5881,406,18300,7131,670,1700,91,92,7.2,27,19635,95 +Georgia Institute of Technology,No,7837,4527,2276,89,99,8528,654,6489,4438,795,1164,92,92,19.3,33,11271,70 +Georgia State University,No,3793,2341,1238,9,24,7732,9054,6744,2655,720,3450,87,89,19,10,7762,34 +Georgian Court College,Yes,348,281,127,12,52,1095,785,9150,3950,500,800,56,59,12.2,27,7348,76 +Gettysburg College,Yes,3596,2466,575,42,78,1944,46,19964,4328,500,500,94,95,12.1,32,14720,83 +Goldey Beacom College,Yes,633,468,284,10,27,823,963,6120,2985,531,1830,25,25,27.6,4,6081,36 +Gonzaga University,Yes,1886,1524,526,31,67,2523,296,13000,4450,600,2400,78,90,14.7,32,9553,69 +Gordon College,Yes,674,565,282,25,54,1151,39,12200,4070,400,1200,73,82,14.2,32,9226,66 +Goshen College,Yes,440,396,221,26,51,910,166,9420,3730,600,1230,51,56,9.9,46,10270,72 +Goucher College,Yes,1151,813,248,40,64,850,80,15588,6174,500,1200,78,90,9.2,34,16623,77 +Grace College and Seminary,Yes,548,428,167,18,46,618,113,8958,3670,300,1000,53,59,15.3,26,9798,64 +Graceland College,Yes,555,414,242,14,41,996,2281,9100,3100,550,880,51,61,23.6,24,5609,47 +Grand Valley State University,No,5165,3887,1561,20,60,8234,2619,6108,3800,500,1000,64,66,20.6,9,5063,57 +Green Mountain College,Yes,780,628,198,7,20,545,42,11750,2700,400,850,77,83,14,24,6475,76 +Greensboro College,Yes,608,494,176,10,31,649,314,8330,3770,550,1300,64,80,13,31,7949,39 +Greenville College,Yes,510,387,194,20,46,771,53,10310,4530,400,800,57,61,14.3,16,8222,60 +Grinnell College,Yes,2039,1389,432,56,91,1333,30,15688,4618,400,400,88,92,9.5,54,18979,83 +Grove City College,Yes,2491,1110,573,57,88,2213,35,5224,3048,525,350,65,65,18.4,18,4957,100 +Guilford College,Yes,1202,1054,326,18,44,1410,299,13404,5160,450,1050,78,86,15.6,30,9114,65 +Gustavus Adolphus College,Yes,1709,1385,634,36,72,2281,50,14125,3600,400,700,79,89,12.5,58,9907,80 +Gwynedd Mercy College,Yes,380,237,104,30,56,716,1108,11000,5550,500,500,36,41,7.8,22,7483,96 +Hamilton College,Yes,3140,1783,454,40,82,1646,24,19700,5050,300,800,91,96,9.6,60,17761,91 +Hamline University,Yes,1006,825,328,34,73,1362,102,13252,4194,450,550,89,93,13,33,10296,65 +Hampden - Sydney College,Yes,817,644,307,20,40,945,1,13218,4773,660,600,95,97,13.3,53,12263,69 +Hampton University,Yes,7178,3755,1433,25,63,4623,740,7161,3518,600,2000,60,64,14,9,6791,70 +Hanover College,Yes,1006,837,317,33,65,1024,15,8200,3485,500,1200,84,84,10.6,26,9248,64 +Hardin-Simmons University,Yes,467,424,350,16,40,1365,334,6300,2980,700,2140,75,79,13.7,10,7054,38 +Harding University,Yes,1721,1068,806,35,75,3128,213,5504,3528,700,910,71,77,17.7,37,6466,73 +Hartwick College,Yes,2083,1725,430,22,49,1464,67,17480,4780,500,700,75,87,12.3,32,11625,73 +Harvard University,Yes,13865,2165,1606,90,100,6862,320,18485,6410,500,1920,97,97,9.9,52,37219,100 +Harvey Mudd College,Yes,1377,572,178,95,100,654,5,17230,6690,700,900,100,100,8.2,46,21569,100 +Hastings College,Yes,817,708,262,22,52,935,37,9376,3272,500,1902,57,63,13,17,7335,52 +Hendrix College,Yes,823,721,274,52,87,954,6,8800,3195,500,1200,82,99,13.1,26,8588,63 +Hillsdale College,Yes,920,745,347,35,66,1133,42,11090,4700,400,750,80,80,12,31,12639,79 +Hiram College,Yes,922,729,244,37,66,1000,275,14067,4560,400,1000,75,95,10.6,34,12165,79 +Hobart and William Smith Colleges,Yes,2688,2081,500,25,53,1792,5,19029,5841,600,600,99,99,12.1,37,13040,79 +Hofstra University,Yes,7428,5860,1349,25,63,6534,1350,11600,5920,1000,1000,81,90,13.9,10,10093,60 +Hollins College,Yes,602,498,215,26,58,795,74,13470,5515,500,850,78,91,11.1,48,13957,72 +Hood College,Yes,699,565,176,36,64,710,399,13960,6040,450,690,82,88,14.4,34,12434,72 +Hope College,Yes,1712,1483,624,37,69,2505,208,12275,4341,465,1100,72,81,12.5,40,9284,72 +Houghton College,Yes,949,786,302,30,70,1210,26,9990,3550,500,1500,85,90,15,24,8187,67 +Huntingdon College,Yes,608,520,127,26,47,538,126,8080,3920,500,1100,63,72,11.4,9,7703,44 +Huntington College,Yes,450,430,125,20,46,488,43,9950,3920,300,1300,76,76,11.8,25,9466,47 +Huron University,Yes,600,197,124,3,9,392,69,7260,3090,600,1840,31,35,12.9,4,9249,21 +Husson College,Yes,723,652,361,10,30,951,706,7800,4000,350,1500,36,44,22,4,4923,84 +Illinois Benedictine College,Yes,607,558,269,22,47,1222,519,10500,4348,650,1500,81,91,11.6,29,8324,75 +Illinois College,Yes,894,787,262,28,63,909,28,8050,3850,600,1000,75,75,15.6,30,7348,52 +Illinois Institute of Technology,Yes,1756,1360,478,42,77,1911,626,14550,4620,500,700,80,88,12.3,26,12851,56 +Illinois State University,No,8681,6695,2408,10,35,15701,1823,7799,3403,537,2605,77,84,21,16,5569,54 +Illinois Wesleyan University,Yes,3050,1342,471,55,86,1818,23,14360,4090,400,650,77,92,12.9,34,9605,83 +Immaculata College,Yes,268,253,103,16,44,494,1305,10000,5364,500,1000,56,64,11.2,33,7305,69 +Incarnate Word College,Yes,1163,927,386,16,49,1685,556,8840,4689,750,2775,67,69,11.4,21,6095,95 +Indiana State University,No,5659,4761,3147,10,31,8596,1949,6892,3706,600,2500,72,76,16.6,8,6996,40 +Indiana University at Bloomington,No,16587,13243,5873,25,72,24763,2717,9766,3990,600,2000,77,88,21.3,24,8686,68 +Indiana Wesleyan University,Yes,735,423,366,20,48,2448,707,9210,3782,700,1000,49,51,39.8,15,6562,34 +Iona College,Yes,4892,3530,913,13,33,3906,1446,10690,6790,570,1150,66,83,16,14,8107,66 +Iowa State University,No,8427,7424,3441,26,59,18676,1715,7550,3224,640,2055,81,88,19.2,22,8420,65 +Ithaca College,Yes,7259,5526,1368,23,52,5612,166,14424,6192,634,1000,58,79,11.5,25,9812,75 +James Madison University,No,11223,5285,2082,32,72,9652,742,7994,4544,500,732,77,81,17.9,29,5212,98 +Jamestown College,Yes,472,410,262,14,41,9950,71,7620,3050,400,400,51,53,17,21,3186,54 +Jersey City State College,No,2957,1423,691,10,30,3817,1394,3946,4800,400,1500,63,67,14.9,10,8367,26 +John Brown University,Yes,605,405,284,24,53,961,99,6398,3672,400,1350,68,68,13.3,19,8118,75 +John Carroll University,Yes,2421,2109,820,27,57,3168,392,11700,5550,600,450,89,90,14.5,28,7738,89 +Johns Hopkins University,Yes,8474,3446,911,75,94,3566,1569,18800,6740,500,1040,96,97,3.3,38,56233,90 +Johnson State College,No,833,669,279,3,13,1224,345,7656,4690,500,624,80,91,14.4,15,6564,36 +Judson College,Yes,313,228,137,10,30,552,67,9414,4554,500,1700,34,55,10.6,30,7840,56 +Juniata College,Yes,1005,859,298,36,55,1075,43,14850,4460,450,420,97,97,12.7,37,12067,80 +Kansas State University,No,5880,4075,2833,25,55,14914,2246,6995,3120,600,2000,76,86,18.5,22,6122,54 +Kansas Wesleyan University,Yes,589,575,148,16,40,474,258,8400,3250,500,1400,63,55,12.4,14,6535,68 +Keene State College,No,3121,2446,822,5,19,3480,776,7870,4157,500,1150,73,73,16.1,13,6195,61 +Kentucky Wesleyan College,Yes,584,497,175,20,49,662,121,8000,4150,500,1300,57,65,11.3,32,7058,62 +Kenyon College,Yes,2212,1538,408,44,75,1445,1,19240,3690,750,480,95,95,11.1,46,14067,88 +Keuka College,Yes,461,381,174,10,43,738,55,9600,4550,600,750,55,94,13.3,43,7863,51 +King's College,Yes,1456,1053,381,20,45,500,541,10910,5160,400,1795,66,72,15.6,37,7649,87 +King College,Yes,355,300,142,34,65,509,44,8664,3350,600,3000,65,68,10.7,25,8954,65 +Knox College,Yes,1040,845,286,48,77,967,24,15747,4062,400,800,88,95,12.7,33,13224,79 +La Roche College,Yes,361,321,185,10,41,650,819,8842,4782,600,1100,57,73,14.2,14,7022,52 +La Salle University,Yes,2929,1834,622,20,56,2738,1662,12600,5610,450,3160,90,90,15.1,9,9084,84 +Lafayette College,Yes,4010,2402,572,36,59,2018,226,18730,5740,600,1000,93,96,10.5,38,15365,92 +LaGrange College,Yes,544,399,177,15,35,600,363,6987,3585,750,1500,77,83,12.5,12,9067,75 +Lake Forest College,Yes,979,638,271,31,70,968,20,16880,3970,920,1320,91,94,10.7,19,15687,77 +Lakeland College,Yes,497,452,231,24,47,887,1957,9400,4005,500,1000,49,65,17.2,25,4054,57 +Lamar University,No,2336,1725,1043,10,27,5438,4058,4752,3040,508,1463,48,82,18.4,12,5879,26 +Lambuth University,Yes,831,538,224,15,35,840,325,5170,3430,600,1590,61,61,16.1,10,5531,60 +Lander University,No,1166,1009,510,9,33,2074,341,4938,2987,528,1702,67,77,17,11,6119,51 +Lawrence University,Yes,1243,947,324,50,77,1129,74,17163,3891,525,975,76,92,10.1,57,13965,77 +Le Moyne College,Yes,1470,1199,425,21,76,1820,558,11040,4840,400,900,89,92,13.3,28,8118,94 +Lebanon Valley College,Yes,1386,1060,320,28,56,965,502,13850,4755,400,1125,84,84,12.3,30,8196,85 +Lehigh University,Yes,6397,4304,1092,40,84,4298,132,18700,5580,750,1130,96,99,12.5,43,14665,91 +Lenoir-Rhyne College,Yes,979,743,259,25,46,1188,166,10100,4000,400,1000,88,92,12,20,8539,66 +Lesley College,Yes,244,198,82,12,33,1134,336,11700,5300,550,805,71,88,27.8,18,8694,58 +LeTourneau University,Yes,477,417,204,29,54,1532,77,8840,4240,600,1400,58,70,20.8,23,6863,56 +Lewis and Clark College,Yes,2774,2092,482,35,64,1763,59,15800,4790,450,950,97,98,12.3,21,12999,69 +Lewis University,Yes,1154,1050,395,12,31,2192,1423,10560,4520,500,1200,36,48,14.3,10,7701,61 +Lincoln Memorial University,Yes,787,562,363,21,55,925,605,5950,2890,600,1300,67,72,14.6,35,5177,53 +Lincoln University,No,1660,1091,326,15,41,1196,33,4818,3400,350,1400,71,72,12.6,8,10912,45 +Lindenwood College,Yes,810,484,356,6,33,2155,191,9200,4800,1000,4200,65,85,24.1,9,3480,100 +Linfield College,Yes,1561,1188,458,48,72,1548,840,13380,4210,500,900,89,91,17.8,34,8747,81 +Livingstone College,Yes,900,473,217,22,47,621,11,4400,3400,800,900,53,93,10.4,16,9268,92 +Lock Haven University of Pennsylvania,No,3570,2215,651,17,41,3390,325,7352,3620,225,500,47,55,16.1,14,6374,63 +Longwood College,No,2747,1870,724,12,47,2874,118,7920,3962,550,2200,74,80,18.4,23,5553,62 +Loras College,Yes,1641,1283,527,20,39,1663,170,11200,4000,500,1200,61,62,14.2,24,7578,70 +Louisiana College,Yes,2013,1053,212,33,61,912,158,5150,3036,500,1655,64,74,10.5,11,7547,59 +Louisiana State University at Baton Rouge,No,5996,4993,3079,29,57,16269,3757,5925,2980,600,2242,83,87,15.9,11,6741,37 +Louisiana Tech University,No,2397,2144,1525,22,45,6720,1822,3957,2325,618,1656,66,77,20,13,4546,45 +Loyola College,Yes,4076,3137,738,25,54,3010,184,12990,6300,600,900,86,88,14.7,27,9448,80 +Loyola Marymount University,Yes,3768,2662,753,42,64,3558,436,13592,5916,545,1328,84,88,14.2,10,11677,84 +Loyola University,Yes,1891,1698,719,24,80,2740,761,11100,5870,600,750,77,88,11.7,14,9456,53 +Loyola University Chicago,Yes,3579,2959,868,25,55,5244,3417,11500,5330,700,2000,94,95,6.2,15,13009,65 +Luther College,Yes,1549,1392,587,38,72,2269,85,13240,3560,600,400,73,85,13.8,38,8949,77 +Lycoming College,Yes,1286,1005,363,16,37,1363,74,13900,4300,500,900,75,81,14,32,8024,72 +Lynchburg College,Yes,1756,1500,366,3,21,1524,280,12450,5400,450,870,62,66,12.4,24,8832,70 +Lyndon State College,No,535,502,223,6,20,959,150,7320,4640,500,600,48,65,12.6,15,7114,51 +Macalester College,Yes,2939,1496,452,56,86,1723,113,15909,4772,500,700,85,91,11.9,37,14213,77 +MacMurray College,Yes,740,558,177,12,29,628,63,9620,3750,550,950,49,55,10.8,33,10642,59 +Malone College,Yes,874,758,428,21,46,1605,246,9858,3700,450,1200,42,45,17.6,16,4796,55 +Manchester College,Yes,1004,802,239,23,63,909,51,10440,3850,525,1450,63,72,11.8,20,7940,64 +Manhattan College,Yes,2432,1730,563,20,63,2578,254,12370,6800,500,1800,92,92,13.6,25,10062,79 +Manhattanville College,Yes,962,750,212,21,54,830,150,14700,6550,450,400,97,97,11.3,24,11291,70 +Mankato State University,No,3073,2672,1547,9,29,9649,1792,4300,2643,450,1660,57,68,19,11,5801,68 +Marian College of Fond du Lac,Yes,824,670,337,15,41,1160,653,9400,3400,500,1100,37,37,8.4,21,5352,59 +Marietta College,Yes,1611,960,342,27,60,1089,210,13850,3920,470,810,80,97,13.2,30,10223,96 +Marist College,Yes,4731,3171,830,12,31,3557,658,10700,5925,550,1200,74,81,17.6,34,8408,69 +Marquette University,Yes,5152,4600,1685,36,71,7016,804,11610,4760,600,1950,86,94,13.5,25,9982,77 +Marshall University,Yes,4226,3666,2007,14,60,7703,2339,5094,4010,700,1560,77,86,16.6,10,6203,50 +Mary Baldwin College,Yes,499,441,199,26,52,846,377,11200,7400,600,1300,66,79,6.8,50,10819,90 +Mary Washington College,No,4350,2178,756,39,78,2997,736,6490,4942,650,2102,75,80,17.6,30,5358,84 +Marymount College Tarrytown,Yes,478,327,117,9,34,731,370,11510,6450,575,1075,71,93,10.3,30,10502,77 +Marymount Manhattan College,Yes,695,535,239,21,30,988,785,10200,7000,350,1100,63,76,11.7,20,10622,68 +Marymount University,Yes,941,772,214,10,30,1247,776,11390,5280,500,750,77,82,10.6,17,8575,55 +Maryville College,Yes,1464,888,176,26,52,624,128,11200,4208,500,1642,80,90,11.1,43,8317,51 +Maryville University,Yes,549,397,169,26,51,1343,1751,9250,4550,425,1350,52,58,13.1,13,5925,61 +Marywood College,Yes,1107,859,323,13,51,1452,402,11040,4500,600,700,65,76,11.8,30,9034,66 +Massachusetts Institute of Technology,Yes,6411,2140,1078,96,99,4481,28,20100,5975,725,1600,99,99,10.1,35,33541,94 +Mayville State University,No,233,233,153,5,12,658,58,4486,2516,600,1900,68,68,15.7,11,6971,51 +McKendree College,Yes,1002,555,119,16,43,836,684,7680,3740,500,800,70,74,17.7,21,6652,52 +McMurry University,Yes,578,411,187,25,50,880,477,6930,3452,400,1525,57,64,11,11,6383,32 +McPherson College,Yes,420,293,93,11,32,336,80,7950,3750,600,2740,54,54,9.8,45,9754,48 +Mercer University,Yes,2286,1668,564,37,70,2943,1260,11985,4081,400,1500,93,95,9.2,15,8995,91 +Mercyhurst College,Yes,1557,1074,397,15,40,1805,433,9813,4050,425,1000,45,63,16.7,29,7307,78 +Meredith College,Yes,857,772,376,25,58,1721,470,6720,3250,450,1520,77,82,13.9,33,6881,82 +Merrimack College,Yes,1981,1541,514,18,36,1927,1084,12500,6200,375,1000,73,75,16.8,22,8707,80 +Mesa State College,No,1584,1456,891,6,18,3471,911,5016,3798,540,2256,48,48,28.8,12,3871,59 +Messiah College,Yes,1742,1382,607,30,64,2258,53,10300,5080,475,1200,68,75,14.1,30,7762,89 +Miami University at Oxford,No,9239,7788,3290,35,39,13606,807,8856,3960,500,1382,81,89,17.6,20,7846,85 +Michigan State University,No,18114,15096,6180,23,57,26640,4120,10658,3734,504,600,93,95,14,9,10520,71 +Michigan Technological University,No,2618,2288,1032,42,77,5524,414,8127,3978,900,1200,82,82,17,25,7473,65 +MidAmerica Nazarene College,Yes,331,331,225,15,36,1100,166,6840,3720,1100,4913,33,33,15.4,20,5524,49 +Millersville University of Penn.,No,6011,3075,960,22,60,5146,1532,7844,3830,450,1258,72,74,16.8,20,7832,71 +Milligan College,Yes,610,461,189,26,52,685,49,8200,3300,550,1000,63,69,12,16,8128,64 +Millikin University,Yes,1444,1261,456,29,62,1788,95,11910,4378,450,965,60,77,11.4,25,8149,75 +Millsaps College,Yes,905,834,319,32,61,1073,179,11320,4402,550,1350,82,89,12.7,38,11218,58 +Milwaukee School of Engineering,Yes,1217,1088,496,36,69,1773,884,11505,3255,1000,2075,35,46,16.7,23,7140,67 +Mississippi College,Yes,594,385,307,36,57,1695,721,5580,2830,600,700,77,79,16.5,18,6170,61 +Mississippi State University,No,4255,3277,1609,18,57,10094,1621,9866,3084,480,1479,77,77,15.9,20,6223,53 +Mississippi University for Women,No,480,405,380,19,46,1673,1014,4386,2217,600,1500,49,54,15.8,8,5704,63 +Missouri Southern State College,No,1576,1326,913,13,50,3689,2200,3840,2852,200,400,52,54,20.3,9,4172,100 +Missouri Valley College,Yes,1310,983,316,5,35,1057,175,8550,5050,400,900,35,67,17.4,16,4333,27 +Monmouth College IL,Yes,601,503,204,28,57,671,11,13000,4100,400,460,91,91,11.6,43,11087,56 +Monmouth College,Yes,2707,1881,478,14,34,1893,847,12480,5290,530,1740,70,85,14.2,15,9492,54 +Montana College of Mineral Sci. & Tech.,No,572,544,320,45,72,1470,416,6073,3400,550,1400,71,71,16.4,31,6112,74 +Montana State University,No,3500,2836,1779,15,42,8730,993,5552,3710,550,2300,75,83,17.6,8,6324,37 +Montclair State University,No,5220,2128,865,19,53,6411,3186,3648,4834,700,950,82,87,21.5,9,6717,58 +Montreat-Anderson College,Yes,263,223,103,10,24,316,20,8438,3372,500,2958,42,50,11.1,4,11989,15 +Moorhead State University,No,2442,2164,1189,12,37,5983,1075,4426,2664,600,1000,76,81,18.1,19,4795,60 +Moravian College,Yes,1232,955,303,23,58,1241,485,14990,4730,550,1250,86,92,15.2,28,9566,74 +Morehouse College,Yes,3708,1678,722,41,66,2852,153,7050,5490,250,600,71,74,17.8,10,8122,83 +Morningside College,Yes,586,533,239,16,36,950,228,10520,3678,500,1000,48,68,13,32,8111,56 +Morris College,Yes,882,730,330,2,13,926,12,4515,2550,850,2100,53,60,18.6,34,6990,60 +Mount Holyoke College,Yes,1800,1314,526,47,79,1891,40,19300,5700,750,750,79,91,9,51,18359,84 +Mount Marty College,Yes,279,276,126,17,37,600,435,6844,2980,500,500,45,55,11.7,38,5073,44 +Mount Mary College,Yes,235,217,121,12,32,931,487,8950,3119,550,1125,51,51,10.7,26,7016,78 +Mount Mercy College,Yes,368,317,159,20,49,806,542,10500,3555,500,2285,44,50,11.3,30,6695,64 +Mount Saint Clare College,Yes,325,284,95,16,33,364,88,9900,3650,500,1200,32,37,13.6,43,6525,21 +Mount Saint Mary's College,Yes,1321,1159,328,15,36,1243,79,12850,6200,550,900,77,82,12.8,36,8536,80 +Mount Saint Mary College,Yes,1170,695,238,14,48,1170,429,7470,4600,250,1400,74,75,15.3,23,6898,88 +Mount St. Mary's College,Yes,657,537,113,37,90,1039,466,12474,5678,630,1278,53,71,11.9,19,10613,72 +Mount Union College,Yes,1310,1086,458,26,61,1365,144,12250,3530,400,1150,85,87,16.7,35,7215,81 +Mount Vernon Nazarene College,Yes,510,485,334,18,36,1114,94,7400,3346,600,600,57,57,19.8,7,6869,58 +Muhlenberg College,Yes,2519,1836,462,30,61,1656,352,16975,4565,600,850,76,86,12.8,39,10888,83 +Murray State University,No,2225,1910,1190,29,55,5968,955,4738,3110,700,940,72,76,20.2,27,5972,52 +Muskingum College,Yes,1109,922,375,24,46,1115,70,13240,3914,600,800,73,85,13.4,27,9333,73 +National-Louis University,Yes,513,347,279,23,48,2508,505,9090,4500,650,500,62,65,18.3,2,7905,71 +Nazareth College of Rochester,Yes,947,798,266,36,68,1274,471,10850,5150,550,800,77,93,13.6,24,8797,61 +New Jersey Institute of Technology,No,1879,1216,483,27,62,3311,1646,8832,5376,700,1850,92,98,13.5,19,12529,72 +New Mexico Institute of Mining and Tech.,No,787,601,233,40,73,1017,411,5376,3214,600,1100,99,100,13.7,11,9241,34 +New York University,Yes,13594,7244,2505,70,86,12408,2814,17748,7262,450,1000,87,98,7.8,16,21227,71 +Newberry College,Yes,872,722,154,14,36,601,36,10194,2600,500,1500,57,63,11.4,32,5788,83 +Niagara University,Yes,2220,1796,467,65,99,1919,334,10320,4762,450,650,68,100,14.2,20,7788,65 +North Adams State College,No,1563,1005,240,1,19,1380,136,5542,4330,500,1000,65,71,14.2,17,6562,57 +North Carolina A. & T. State University,No,4809,3089,1429,12,33,6162,871,6806,1780,600,1651,72,72,16.7,9,7090,44 +North Carolina State University at Raleigh,No,10634,7064,3176,39,78,16505,5481,8400,6540,600,1300,92,98,17.5,21,9670,62 +North Carolina Wesleyan College,Yes,812,689,195,7,24,646,84,8242,4230,600,1295,77,77,12.7,11,10090,52 +North Central College,Yes,1127,884,308,30,64,1310,766,11718,7398,450,1800,73,87,16.4,33,8871,76 +North Dakota State University,No,2968,2297,1610,13,47,7368,1128,5834,2744,600,2000,79,83,17,24,6310,42 +North Park College,Yes,465,361,176,19,39,879,156,12580,4345,400,970,76,79,13.1,24,10889,74 +Northeast Missouri State University,No,6040,4577,1620,36,72,5640,266,4856,3416,400,1100,69,72,15.7,13,6601,76 +Northeastern University,Yes,11901,8492,2517,16,42,11160,10221,13380,7425,600,1750,73,82,12.9,17,9563,46 +Northern Arizona University,No,5891,4931,1973,23,48,11249,2682,6746,3728,620,2342,78,83,21.7,7,6157,41 +Northern Illinois University,No,10706,7219,2397,12,37,14826,1979,7799,3296,470,1750,73,78,17.3,11,6086,56 +Northwest Missouri State University,No,2729,2535,1257,8,29,4787,472,3735,3136,250,1630,62,65,21.7,23,5284,54 +Northwest Nazarene College,Yes,616,514,385,29,52,1115,60,9840,2820,450,822,59,59,14.8,20,6261,58 +Northwestern College,Yes,860,811,366,22,56,1040,52,9900,3075,300,1800,68,68,14.9,34,6357,68 +Northwestern University,Yes,12289,5200,1902,85,98,7450,45,16404,5520,759,1585,96,100,6.8,25,26385,92 +Norwich University,Yes,1743,1625,626,8,29,1862,382,14134,5270,500,800,71,74,13.1,22,9209,63 +Notre Dame College,Yes,379,324,107,15,37,500,311,9990,4900,400,600,44,47,12.1,26,4948,33 +Oakland University,No,3041,2581,1173,16,56,6441,3982,9114,4030,400,650,88,90,19.7,13,6637,53 +Oberlin College,Yes,4778,2767,678,50,89,2587,120,19670,5820,575,1119,77,96,10.1,47,16593,83 +Occidental College,Yes,2324,1319,370,52,81,1686,35,16560,5140,558,1152,91,93,10.5,30,16196,79 +Oglethorpe University,Yes,792,649,186,56,87,769,377,12900,4340,600,4110,91,95,13.1,27,8568,67 +Ohio Northern University,Yes,2936,2342,669,35,62,2502,66,15990,4080,600,825,73,78,14.5,31,9979,83 +Ohio University,No,11023,8298,3183,21,54,14861,1310,7629,4095,550,2300,79,87,20.4,13,8811,64 +Ohio Wesleyan University,Yes,2190,1700,458,36,65,1780,48,16732,5650,550,550,93,93,12.1,32,12011,75 +Oklahoma Baptist University,Yes,758,681,484,35,59,1707,705,5390,3140,515,1290,63,71,15.1,18,5511,50 +Oklahoma Christian University,Yes,776,765,351,22,44,1419,228,6400,3150,500,1900,58,64,16.2,8,6578,45 +Oklahoma State University,No,4522,3913,2181,29,57,12830,1658,5336,3344,800,3100,84,92,15.3,14,6433,48 +Otterbein College,Yes,1496,1205,428,26,57,1648,936,12888,4440,420,840,62,68,13.9,30,8802,87 +Ouachita Baptist University,Yes,910,773,450,31,73,1310,61,6530,2800,500,1500,63,67,13.3,10,6413,65 +Our Lady of the Lake University,Yes,2308,1336,295,22,46,1202,942,8530,3644,616,1576,56,64,14.9,25,7114,37 +Pace University,Yes,8256,3750,1522,37,70,5809,4379,11000,5160,660,1115,90,95,13.8,10,10059,62 +Pacific Lutheran University,Yes,1603,1392,504,31,68,2580,302,13312,4488,600,1516,78,78,11,23,9431,83 +Pacific Union College,Yes,940,668,385,20,48,1316,139,11925,3825,630,1926,48,87,12.3,12,9157,69 +Pacific University,Yes,943,849,288,41,71,1041,35,14210,3994,450,1100,76,76,10.9,22,11216,42 +Pembroke State University,No,944,774,440,14,34,2174,529,6360,2760,550,1498,77,77,15,5,6443,48 +Pennsylvania State Univ. Main Campus,No,19315,10344,3450,48,93,28938,2025,10645,4060,512,2394,77,96,18.1,19,8992,63 +Pepperdine University,Yes,3821,2037,680,86,96,2488,625,18200,6770,500,700,95,98,11.6,13,16185,66 +Peru State College,No,701,501,458,10,40,959,457,2580,2624,500,900,48,100,20.1,24,4870,44 +Pfeiffer College,Yes,838,651,159,11,25,654,162,8640,3700,400,1915,62,62,12.2,13,7634,48 +Philadelphia Coll. of Textiles and Sci.,Yes,1538,1259,468,19,42,1664,1042,11690,5062,600,1664,48,80,12.9,15,8028,68 +Phillips University,Yes,692,576,174,19,50,597,83,10500,3860,600,940,58,64,11.6,19,8990,39 +Piedmont College,Yes,663,562,127,20,40,641,63,5640,3620,600,750,89,89,13.2,17,7309,31 +Pikeville College,Yes,404,400,169,28,48,797,100,6000,3000,500,500,48,57,13.4,14,5557,61 +Pitzer College,Yes,1133,630,220,37,73,750,30,17688,5900,650,850,100,100,10.4,11,14820,73 +Point Loma Nazarene College,Yes,809,687,428,20,43,1889,217,10178,4190,800,750,71,71,16.1,19,7895,54 +Point Park College,Yes,875,744,207,7,38,1173,1402,9700,4830,400,1200,45,90,14.5,10,7652,66 +Polytechnic University,Yes,1132,847,302,58,89,1379,214,16200,4200,436,2486,90,90,10.4,14,14329,62 +Prairie View A. and M. University,No,2405,2234,1061,10,22,4564,448,4290,3500,598,1582,55,93,19.4,1,5967,35 +Presbyterian College,Yes,1082,832,302,34,63,1133,30,11859,3635,554,1429,80,85,13.4,42,8354,85 +Princeton University,Yes,13218,2042,1153,90,98,4540,146,19900,5910,675,1575,91,96,8.4,54,28320,99 +Providence College,Yes,5139,3346,973,20,55,3717,1358,14400,6200,450,1100,66,74,18.4,35,8135,96 +Purdue University at West Lafayette,No,21804,18744,5874,29,60,26213,4065,9556,3990,570,1060,86,86,18.2,15,8604,67 +Queens College,Yes,516,392,154,32,62,630,549,11020,4970,610,1900,73,75,14,36,9315,58 +Quincy University,Yes,1025,707,297,22,66,1070,72,10100,4140,450,1080,69,71,16.3,32,6880,80 +Quinnipiac College,Yes,3712,2153,806,17,45,2677,714,12030,6140,1000,500,63,73,12,33,8847,86 +Radford University,No,5702,4894,1742,15,37,8077,472,6684,4110,500,900,73,83,19.6,9,4519,62 +Ramapo College of New Jersey,No,2088,957,362,6,29,2745,1938,4449,4860,600,1655,74,95,17.8,8,7333,47 +Randolph-Macon College,Yes,1771,1325,306,21,46,1071,27,13840,3735,400,900,77,80,10.7,38,11080,74 +Randolph-Macon Woman's College,Yes,696,616,169,35,66,653,56,13970,6110,370,920,88,97,9.2,24,16358,68 +Reed College,Yes,1966,1436,327,47,80,1199,61,19960,5490,500,450,90,90,11.8,37,15886,68 +Regis College,Yes,427,385,143,18,38,581,533,12700,5800,450,700,81,85,10.3,37,11758,84 +Rensselaer Polytechnic Institute,Yes,4996,4165,936,53,82,4291,16,17475,5976,1230,1100,94,98,15.4,21,15605,70 +Rhodes College,Yes,2302,1831,391,58,82,1345,59,15200,4768,550,1500,90,96,10.8,47,13388,77 +Rider University,Yes,3586,2424,730,16,31,2748,1309,13250,5420,700,3100,84,92,12.3,23,11299,70 +Ripon College,Yes,587,501,211,28,52,735,28,15200,4100,350,650,87,90,9.4,49,12472,64 +Rivier College,Yes,484,386,141,6,28,590,1196,9870,4860,600,1100,59,59,12.2,19,6744,81 +Roanoke College,Yes,2227,1790,437,27,54,1460,239,13425,4425,450,1200,85,89,13,26,9405,72 +Rockhurst College,Yes,935,858,345,22,50,1127,754,9490,4100,500,1500,60,79,10.7,21,7519,79 +Rocky Mountain College,Yes,560,392,270,11,31,743,118,8734,3362,600,625,56,78,11.3,27,6422,68 +Roger Williams University,Yes,3304,2804,679,10,20,2111,1489,12520,6050,500,730,44,54,16.4,8,7957,61 +Rollins College,Yes,1777,1151,382,31,55,1668,1052,16425,5220,955,750,81,85,13.3,23,11561,90 +Rosary College,Yes,434,321,141,28,53,624,269,10950,4600,550,950,79,82,12.9,30,9264,81 +Rowan College of New Jersey,No,3820,1431,695,21,70,5303,3942,4356,4830,800,800,76,81,22.1,6,7252,51 +Rutgers at New Brunswick,No,48094,26330,4520,36,79,21401,3712,7410,4748,690,2009,90,95,19.5,19,10474,77 +Rutgers State University at Camden,No,3366,1752,232,27,79,2585,1300,7411,4748,690,2009,90,95,18.6,12,10134,57 +Rutgers State University at Newark,No,5785,2690,499,26,62,4005,1886,7410,4748,690,2009,90,95,17.4,16,11878,58 +Sacred Heart University,Yes,2307,1896,509,19,51,1707,1889,11070,5780,400,600,71,73,14.8,16,7120,82 +Saint Ambrose University,Yes,897,718,276,12,48,1345,390,10450,4020,500,1500,56,56,14.1,16,7444,70 +Saint Anselm College,Yes,2095,1553,514,15,40,1873,94,12950,5400,450,1120,70,82,14.5,29,6719,97 +Saint Cloud State University,No,3971,3306,1921,10,34,11493,2206,4259,2625,350,1884,70,75,18.9,10,4629,58 +Saint Francis College IN,Yes,213,166,85,13,36,513,247,8670,3820,450,1000,43,78,12.5,4,7440,48 +Saint Francis College,Yes,1046,824,284,21,45,1223,451,10880,5050,400,1235,64,64,19.3,24,7344,69 +Saint John's University,Yes,933,800,444,18,45,1691,72,12247,4081,500,600,76,85,12,38,9853,70 +Saint Joseph's College IN,Yes,920,684,225,24,42,815,222,11200,4250,600,950,55,60,14.8,19,7360,67 +Saint Joseph's College,Yes,833,682,217,12,33,716,2196,9985,5180,500,800,53,89,27.2,8,4322,85 +Saint Joseph's University,Yes,2519,2003,776,39,71,2473,1314,12750,6350,350,1690,84,90,17.4,13,8243,83 +Saint Joseph College,Yes,292,241,96,20,52,543,712,12200,4600,650,950,87,90,11.2,32,8680,76 +Saint Louis University,Yes,3294,2855,956,44,67,4576,1140,11690,4730,800,6800,84,94,4.6,19,18367,67 +Saint Mary's College,Yes,888,734,393,26,60,1433,27,12730,4514,500,1525,74,95,9.9,31,11165,98 +Saint Mary's College of Minnesota,Yes,876,802,367,14,35,1263,118,10800,3600,400,820,68,74,18.8,19,5081,78 +Saint Mary-of-the-Woods College,Yes,150,130,88,23,50,341,768,10300,4130,500,1700,44,58,10.2,37,9678,75 +Saint Michael's College,Yes,1910,1380,463,16,64,1715,106,13030,5860,500,750,79,88,14.5,34,10190,84 +Saint Olaf College,Yes,2248,1673,745,38,73,2888,105,14350,3750,550,550,82,88,10,31,12502,83 +Saint Peter's College,Yes,1606,1413,530,23,38,1921,1154,9408,5520,500,450,78,78,12.1,22,7669,53 +Saint Vincent College,Yes,700,595,278,19,35,1035,182,10850,3936,500,900,62,64,12.3,31,8534,88 +Saint Xavier University,Yes,785,647,295,15,65,1670,726,10860,4624,600,794,87,100,13.7,15,8953,55 +Salem-Teikyo University,Yes,489,384,120,23,52,700,45,10575,3952,400,620,46,24,13,9,8946,98 +Salem College,Yes,335,284,132,28,69,534,216,10475,6300,500,2000,68,68,11.2,46,9599,60 +Salisbury State University,No,4216,2290,736,20,52,4296,1027,5130,4690,600,1450,73,75,17.9,18,5125,56 +Samford University,Yes,1680,1395,691,34,76,2959,402,8236,3700,569,1650,74,75,14.7,17,9533,61 +San Diego State University,No,9402,7020,2151,20,70,16407,5550,8384,5110,612,2400,87,93,19.5,7,7930,41 +Santa Clara University,Yes,4019,2779,888,40,73,3891,128,13584,5928,630,1278,88,92,13.9,19,10872,100 +Sarah Lawrence College,Yes,1380,768,263,57,82,1000,105,19300,6694,600,700,89,93,6.1,18,14779,83 +Savannah Coll. of Art and Design,Yes,1109,688,386,20,65,1897,208,8325,5000,1200,1600,14,98,16.1,26,6874,55 +Schreiner College,Yes,584,413,131,19,51,521,99,8955,5900,500,1488,51,56,11.8,23,8545,52 +Scripps College,Yes,855,632,139,60,83,569,7,17238,7350,600,800,95,100,8.2,41,18372,73 +Seattle Pacific University,Yes,1183,1016,411,42,82,1922,704,12669,4875,600,1250,83,85,16.8,20,10368,66 +Seattle University,Yes,2115,1540,494,28,72,2993,347,12825,4375,500,1500,85,85,12.2,16,10175,89 +Seton Hall University,Yes,4576,3565,1000,16,36,4384,1530,12000,6484,650,1000,81,84,14.4,15,10080,64 +Seton Hill College,Yes,936,794,197,24,56,752,210,11240,4180,350,2000,71,71,11.2,37,10065,71 +Shippensburg University of Penn.,No,5818,3281,1116,14,53,5268,300,7844,3504,450,1700,80,83,18.8,13,6719,72 +Shorter College,Yes,540,445,165,23,70,1115,111,7210,3600,500,2000,62,65,13.2,18,7356,58 +Siena College,Yes,2961,1932,628,24,68,2669,616,10800,5100,575,1090,71,82,14.1,42,8189,100 +Siena Heights College,Yes,464,419,183,10,31,686,287,9240,3880,475,1090,29,49,7.2,17,9431,47 +Simmons College,Yes,1003,782,295,23,53,1144,160,16160,6950,500,1200,74,81,8.9,33,14086,79 +Simpson College,Yes,1016,872,300,27,57,1116,602,11250,4980,550,1400,66,73,15.8,36,7411,70 +Sioux Falls College,Yes,437,400,211,13,35,614,271,8990,3064,500,1700,73,73,14.8,7,7881,48 +Skidmore College,Yes,4293,2728,591,25,62,2322,263,18710,5970,500,700,87,92,12.7,29,14837,81 +Smith College,Yes,2925,1598,632,51,88,2479,95,18820,6390,500,1050,85,97,10.3,44,21199,90 +South Dakota State University,No,2807,2589,1701,13,37,7000,1103,3811,2190,500,1970,62,65,15,29,5084,67 +Southeast Missouri State University,No,2281,1870,1408,18,43,6553,1246,4680,3540,200,2150,75,76,17.1,8,5916,45 +Southeastern Oklahoma State Univ.,No,818,700,447,20,50,2962,651,3738,2619,450,1022,55,59,19.6,9,4444,53 +Southern California College,Yes,385,340,193,18,38,784,127,9520,4124,630,1818,63,65,18.6,11,8219,43 +Southern Illinois University at Edwardsville,No,2540,2195,994,13,40,6063,2550,5472,3598,221,2216,76,81,16.5,8,7498,43 +Southern Methodist University,Yes,4301,3455,1166,41,69,4892,387,12772,5078,576,1802,74,88,13.5,17,12726,72 +Southwest Baptist University,Yes,1093,1093,642,12,32,1770,967,7070,2500,400,1000,52,54,15.9,13,4718,71 +Southwest Missouri State University,No,6118,5254,3204,15,37,13131,3374,4740,2590,500,1360,70,75,19.9,11,4632,56 +Southwest State University,No,1047,938,511,13,33,2091,546,4285,2750,600,1800,58,75,16.5,31,6591,51 +Southwestern Adventist College,Yes,321,318,172,11,27,620,280,7536,3736,430,1651,44,77,13,12,5309,36 +Southwestern College,Yes,213,155,75,28,66,504,147,7200,3532,550,1500,56,56,11.8,12,7818,52 +Southwestern University,Yes,1244,912,352,44,77,1177,43,11850,4675,600,1050,83,89,11.3,35,12995,67 +Spalding University,Yes,283,201,97,10,45,589,263,8400,2800,600,900,50,56,10.6,40,6860,89 +Spelman College,Yes,3713,1237,443,47,83,1971,107,7000,5565,660,2400,73,80,12.5,18,9988,65 +Spring Arbor College,Yes,372,362,181,15,32,1501,353,8600,3550,385,665,48,48,15.4,9,10938,49 +St. Bonaventure University,Yes,1489,1313,375,13,45,1688,131,10456,4927,500,1050,91,91,17.7,32,9828,78 +St. John's College,Yes,323,278,122,31,51,393,4,16150,5450,275,800,63,72,7.2,26,15622,64 +St. John Fisher College,Yes,1368,1064,354,19,51,1687,677,10570,5600,400,800,86,81,14.5,29,7908,66 +St. Lawrence University,Yes,2753,1820,505,31,56,1801,45,18720,5730,650,825,90,94,11.5,38,14980,85 +St. Martin's College,Yes,191,165,63,5,25,494,574,11550,4270,300,500,43,77,14.5,8,9209,40 +St. Mary's College of California,Yes,2643,1611,465,36,80,2615,248,13332,6354,630,1584,88,89,16.1,17,9619,78 +St. Mary's College of Maryland,No,1340,695,285,42,73,1315,209,6800,4730,675,1250,84,89,11.6,23,10357,63 +St. Mary's University of San Antonio,Yes,1243,1020,414,33,60,2149,418,8678,3858,700,1736,82,83,16.2,7,7651,72 +St. Norbert College,Yes,1334,1243,568,30,56,1946,95,12140,4450,425,1100,74,78,15.1,36,8595,88 +St. Paul's College,Yes,651,581,243,8,17,617,34,5000,3650,600,600,45,45,14,8,8426,45 +St. Thomas Aquinas College,Yes,861,609,215,10,27,1117,815,8650,5700,500,1750,69,73,16.1,13,6534,67 +Stephens College,Yes,450,405,194,17,34,614,388,13900,5200,450,2150,46,63,10.9,17,9995,59 +Stetson University,Yes,1557,1227,489,37,69,1964,81,12315,4565,600,1365,85,90,12.5,24,10307,73 +Stevens Institute of Technology,Yes,1768,1249,380,51,93,1263,11,16900,5680,450,750,89,89,19,33,12837,79 +Stockton College of New Jersey,No,4019,1579,710,23,65,4365,765,3040,4351,711,1125,78,92,19.5,7,5599,64 +Stonehill College,Yes,3646,2300,585,25,69,2022,926,12170,6172,480,800,79,79,13,30,7495,97 +SUNY at Albany,No,13528,9198,1843,16,61,10168,1231,6550,4355,700,1560,93,96,17.4,16,9075,74 +SUNY at Binghamton,No,14463,6166,1757,60,94,8544,671,6550,4598,700,1000,83,100,18,15,8055,80 +SUNY at Buffalo,No,15039,9649,3087,36,100,13963,3124,6550,4731,708,957,90,97,13.6,15,11177,56 +SUNY at Stony Brook,No,12512,6969,1724,27,66,9744,1351,6550,4712,600,1200,91,96,10.5,7,13705,57 +SUNY College at Brockport,No,7294,3564,904,7,34,5758,1363,6550,4460,500,705,79,83,19,14,6632,49 +SUNY College at Oswego,No,8000,4556,1464,17,70,6943,869,6550,4810,500,1500,69,85,22,21,5280,63 +SUNY College at Buffalo,No,5318,3515,1025,8,29,7626,2091,6550,4040,550,1230,71,78,18.7,12,7511,42 +SUNY College at Cortland,No,7888,3519,1036,6,40,5011,346,6550,4680,630,1274,82,85,17.8,17,5563,53 +SUNY College at Fredonia,No,4877,2798,814,13,48,4123,298,6550,4420,620,1481,82,90,16.3,10,6442,66 +SUNY College at Geneseo,No,8598,4562,1143,56,93,5060,146,6550,4170,600,650,79,84,19.1,25,5716,76 +SUNY College at New Paltz,No,8399,3609,656,19,53,4658,1478,6550,4240,550,1500,85,93,15.3,8,6608,53 +SUNY College at Plattsburgh,No,5549,3583,853,9,40,5004,475,6550,4176,600,1380,80,90,17.9,16,6174,65 +SUNY College at Potsdam,No,3150,2289,650,16,51,3598,234,6840,4660,500,1000,71,75,15.1,17,6436,59 +SUNY College at Purchase,No,2119,1264,390,5,33,2478,1441,6550,4760,1125,1362,80,100,14.9,8,8170,46 +Susquehanna University,Yes,2096,1512,465,27,59,1442,166,16130,4710,400,800,83,86,13.9,37,10554,90 +Sweet Briar College,Yes,462,402,146,36,68,527,41,14500,6000,500,600,91,99,6.5,48,18953,61 +Syracuse University,Yes,10477,7260,2442,28,67,10142,117,15150,6870,635,960,73,84,11.3,13,14231,67 +Tabor College,Yes,257,183,109,19,41,396,38,7850,3410,400,1500,55,70,10,15,7233,53 +Talladega College,Yes,4414,1500,335,30,60,908,119,5666,2964,1000,1400,56,58,15.5,7,5970,46 +Taylor University,Yes,1769,1092,437,41,80,1757,81,10965,4000,450,1250,60,61,14.2,32,8294,98 +Tennessee Wesleyan College,Yes,232,182,99,7,29,402,237,7070,3640,400,3158,59,65,8.9,16,6286,36 +Texas A&M Univ. at College Station,No,14474,10519,6392,49,85,31643,2798,5130,3412,600,2144,89,91,23.1,29,8471,69 +Texas A&M University at Galveston,No,529,481,243,22,47,1206,134,4860,3122,600,650,103,88,17.4,16,6415,43 +Texas Christian University,Yes,4095,3079,1195,33,64,5064,660,8490,3320,650,2400,81,93,14.8,23,9158,64 +Texas Lutheran College,Yes,497,423,215,27,57,895,429,7850,3410,490,1700,54,58,13.8,24,7002,50 +Texas Southern University,No,4345,3245,2604,15,85,5584,3101,7860,3360,600,1700,65,75,18.2,21,3605,10 +Texas Wesleyan University,Yes,592,501,279,19,44,1204,392,6400,3484,600,1800,80,83,14.5,10,7936,43 +The Citadel,No,1500,1242,611,12,36,2024,292,7070,2439,400,779,95,94,17.1,17,7744,84 +Thiel College,Yes,1154,951,253,15,31,791,140,11172,4958,700,1350,68,76,11.6,16,9186,60 +Tiffin University,Yes,845,734,254,5,21,662,351,7600,3800,600,1200,59,74,19,40,5096,39 +Transylvania University,Yes,759,729,244,57,81,867,51,10900,4450,500,1000,81,91,12.1,41,10219,70 +Trenton State College,No,5042,2312,944,55,94,5167,902,5391,5411,700,1000,81,87,14.4,6,8504,81 +Tri-State University,Yes,1262,1102,276,14,40,978,98,9456,4350,468,1323,53,53,12.8,24,7603,65 +Trinity College CT,Yes,3058,1798,478,46,84,1737,244,18810,5690,500,680,91,96,10.4,48,18034,91 +Trinity College DC,Yes,247,189,100,19,49,309,639,11412,6430,500,900,89,93,8.3,37,11806,96 +Trinity College VT,Yes,222,185,91,16,41,484,541,11010,5208,550,500,58,78,10.4,26,9586,78 +Trinity University,Yes,2425,1818,601,62,93,2110,95,12240,5150,500,490,94,96,9.6,20,14703,93 +Tulane University,Yes,7033,5125,1223,47,75,4941,1534,19040,5950,350,800,98,98,9.1,21,16920,74 +Tusculum College,Yes,626,372,145,12,34,983,40,7700,3400,450,800,70,70,21.9,28,4933,52 +Tuskegee University,Yes,2267,1827,611,20,59,2825,144,6735,3395,600,1425,70,74,12.2,7,10872,65 +Union College KY,Yes,484,384,177,9,45,634,78,7800,2950,500,600,60,88,14.1,9,6864,64 +Union College NY,Yes,3495,1712,528,49,84,1915,123,18732,6204,450,1024,94,96,11.5,49,15411,88 +Univ. of Wisconsin at OshKosh,No,4800,2900,1515,14,48,7764,1472,6874,2394,518,1890,73,78,19.2,14,5901,56 +University of Alabama at Birmingham,No,1797,1260,938,24,35,6960,4698,4440,5175,750,2200,96,96,6.7,16,16352,33 +University of Arkansas at Fayetteville,No,3235,3108,2133,25,65,9978,1530,5028,3300,500,2000,73,89,14.8,10,6820,39 +University of California at Berkeley,No,19873,8252,3215,95,100,19532,2061,11648,6246,636,1933,93,97,15.8,10,13919,78 +University of California at Irvine,No,15698,10775,2478,85,100,12677,864,12024,5302,790,1818,96,96,16.1,11,15934,66 +University of Central Florida,No,6986,2959,1918,25,60,12330,7152,6618,4234,700,1600,80,98,22.2,9,6742,46 +University of Charleston,Yes,682,535,204,22,43,771,611,9500,3540,400,750,26,58,2.5,10,7683,57 +University of Chicago,Yes,6348,2999,922,68,94,3340,39,18930,6380,500,1254,99,99,5.3,36,36854,90 +University of Cincinnati,No,6855,5553,2408,26,57,11036,2011,8907,4697,556,1851,89,95,10.8,6,13889,54 +University of Connecticut at Storrs,No,9735,7187,2064,23,63,12478,1660,11656,5072,700,2300,89,95,16,16,10178,71 +University of Dallas,Yes,681,588,246,44,74,1058,73,10760,6230,500,1200,85,93,13.4,26,8731,63 +University of Dayton,Yes,6361,5293,1507,26,51,5889,665,11380,4220,500,900,81,85,14.8,25,8894,93 +University of Delaware,Yes,14446,10516,3252,22,57,14130,4522,10220,4230,530,1300,82,87,18.3,15,10650,75 +University of Denver,Yes,2974,2001,580,29,60,2666,554,15192,4695,400,1350,84,91,15.9,21,11762,67 +University of Detroit Mercy,Yes,927,731,415,24,50,2149,2217,11130,3996,600,2166,72,79,13.5,14,10891,51 +University of Dubuque,Yes,576,558,137,11,39,662,131,10430,3620,400,1500,85,98,16.5,18,8767,45 +University of Evansville,Yes,2096,1626,694,35,67,2551,407,11800,4340,700,960,60,81,15.8,26,7780,77 +University of Florida,No,12445,8836,3623,54,85,24470,3286,7090,4180,630,1530,88,97,13.4,20,14737,66 +University of Georgia,No,11220,7871,3320,43,79,19553,2748,5697,3600,525,1755,88,95,14.7,22,7881,63 +University of Hartford,Yes,5081,4040,1194,11,26,3768,1415,14220,6000,500,1440,61,76,10.7,9,10625,66 +University of Hawaii at Manoa,No,3580,2603,1627,36,69,11028,2411,4460,3038,687,1281,85,87,11.8,6,12833,54 +University of Illinois - Urbana,No,14939,11652,5705,52,88,25422,911,7560,4574,500,1982,87,90,17.4,13,8559,81 +University of Illinois at Chicago,No,8384,5727,2710,22,50,13518,2916,7230,5088,630,3228,82,84,10,6,13883,34 +University of Indianapolis,Yes,1487,1276,388,26,51,1417,1646,11120,4080,525,1405,55,56,11.1,23,6735,69 +University of Kansas,No,8579,5561,3681,25,50,17880,1673,6994,3384,700,2681,88,94,13.7,17,9657,57 +University of La Verne,Yes,1597,969,226,16,38,1431,1522,13540,5050,630,2298,66,68,14.1,23,10139,47 +University of Louisville,No,4777,3057,1823,16,33,9844,6198,6540,3600,530,2440,84,92,11.1,24,10207,31 +University of Maine at Farmington,No,1208,803,438,20,48,1906,344,6810,3970,450,1647,67,75,15.9,26,5712,59 +University of Maine at Machias,No,441,369,172,17,45,633,317,6600,3680,600,400,46,46,15.1,4,5935,64 +University of Maine at Presque Isle,No,461,381,235,10,40,974,503,6600,3630,400,1675,67,67,15.2,11,6408,35 +University of Maryland at Baltimore County,No,4269,2594,985,27,57,6476,2592,8594,4408,494,2768,82,88,18.4,6,7618,55 +University of Maryland at College Park,No,14292,10315,3409,22,53,19340,3991,8723,5146,550,1550,89,92,18.1,12,9021,63 +University of Massachusetts at Amherst,No,14438,12414,3816,12,39,16282,1940,8566,3897,500,1400,88,92,16.7,15,10276,68 +University of Massachusetts at Dartmouth,No,3347,2597,1006,10,37,4664,1630,6919,4500,500,1250,74,90,15,20,7462,56 +University of Miami,Yes,7122,5386,1643,42,69,7760,876,16500,6526,630,1985,82,94,5.9,17,17500,59 +University of Michigan at Ann Arbor,No,19152,12940,4893,66,92,22045,1339,15732,4659,476,1600,90,98,11.5,26,14847,87 +University of Minnesota at Duluth,No,4192,3126,1656,15,45,5887,1254,8828,3474,753,2610,79,91,19,11,6393,53 +University of Minnesota at Morris,No,1458,874,588,56,86,1846,154,9843,3180,600,1500,74,78,14.6,16,6716,51 +University of Minnesota Twin Cities,No,11054,6397,3524,26,55,16502,21836,8949,3744,714,2910,88,90,12.2,37,16122,45 +University of Mississippi,No,3844,3383,1669,26,47,7524,804,4916,3810,600,550,81,86,20.3,14,6971,53 +University of Missouri at Columbia,No,6574,4637,2940,32,62,14782,1583,9057,3485,600,1983,87,87,12.7,15,10145,58 +University of Missouri at Rolla,No,1877,1826,823,49,77,3926,561,9057,3600,700,1435,88,88,14.4,23,9699,49 +University of Missouri at Saint Louis,No,1618,1141,479,18,54,4793,4552,7246,3964,500,4288,71,73,13.4,15,6433,48 +University of Mobile,Yes,452,331,269,17,54,1417,301,6150,3680,550,1200,59,63,16.6,4,5412,52 +University of Montevallo,No,1351,892,570,18,78,2385,331,4440,3030,300,600,72,72,18.9,8,5883,51 +University of Nebraska at Lincoln,No,6277,6003,3526,33,63,16454,3171,5595,3145,500,2070,86,92,15.1,48,6813,53 +University of New England,Yes,1209,750,265,19,54,820,159,11450,5045,900,2500,72,75,11.4,13,9718,64 +University of New Hampshire,No,9750,7640,2529,24,62,10358,1338,11180,3862,650,2450,89,87,17.5,16,7855,75 +University of North Carolina at Asheville,No,1757,979,394,32,74,2033,1078,5972,3420,600,750,77,83,13,11,7011,37 +University of North Carolina at Chapel Hill,No,14596,5985,3331,75,92,14609,1100,8400,4200,550,1200,88,93,8.9,23,15893,83 +University of North Carolina at Charlotte,No,5803,4441,1730,19,62,10099,3255,7248,3109,600,1900,79,91,16.8,7,6227,62 +University of North Carolina at Greensboro,No,5191,4134,1500,15,44,7532,1847,8677,3505,600,1300,75,94,15.5,17,7392,53 +University of North Carolina at Wilmington,No,6071,3856,1449,15,67,6635,1145,7558,3680,500,1500,82,85,19.1,15,6005,55 +University of North Dakota,No,2777,2249,1652,20,54,8334,1435,5634,2703,450,1200,97,97,15.9,16,9424,49 +University of North Florida,No,1800,1253,560,44,85,3876,3588,6634,4360,600,2604,82,85,17.8,14,6104,47 +University of North Texas,No,4418,2737,2049,23,51,14047,5134,4104,3579,450,1700,86,94,22.6,6,5657,35 +University of Northern Colorado,No,5530,4007,1697,12,37,8463,1498,7731,4128,540,2286,75,75,21.5,8,6309,40 +University of Northern Iowa,No,4144,3379,1853,18,52,10135,1448,6197,2930,595,2380,78,82,16.3,26,6333,77 +University of Notre Dame,Yes,7700,3700,1906,79,96,7671,30,16850,4400,600,1350,96,92,13.1,46,13936,97 +University of Oklahoma,No,4743,3970,2233,32,63,13436,2582,5173,3526,765,3176,86,90,11.5,11,10244,44 +University of Oregon,No,8631,6732,2546,25,61,11669,1605,10602,3660,570,1530,79,87,19.7,13,8020,54 +University of Pennsylvania,Yes,12394,5232,2464,85,100,9205,531,17020,7270,500,1544,95,96,6.3,38,25765,93 +University of Pittsburgh-Main Campus,No,8586,6383,2503,25,59,13138,4289,10786,4560,400,900,93,93,7.8,10,13789,66 +University of Portland,Yes,1758,1485,419,27,58,2041,174,12040,4100,600,1100,92,96,13.2,17,9060,72 +University of Puget Sound,Yes,4044,2826,688,51,83,2738,138,16230,4500,630,1800,79,86,15,17,11217,63 +University of Rhode Island,No,9643,7751,1968,12,40,8894,2456,10330,5558,500,1250,84,89,16.6,7,9158,63 +University of Richmond,Yes,5892,2718,756,46,72,2854,594,14500,3285,700,1125,75,89,11.7,32,11984,100 +University of Rochester,Yes,8766,5498,1243,56,75,5071,438,17840,6582,500,882,93,99,5.9,23,26037,80 +University of San Diego,Yes,3934,2735,886,40,70,3698,217,13600,5940,630,1820,93,96,15.6,13,10813,66 +University of San Francisco,Yes,2306,1721,538,23,48,4309,549,13226,6452,750,2450,86,86,13.6,8,10074,62 +University of Sci. and Arts of Oklahoma,No,285,280,208,21,43,1140,473,3687,1920,600,1800,67,77,23.6,3,3864,43 +University of Scranton,Yes,4471,2942,910,29,60,3674,493,11584,5986,650,800,83,83,14.1,41,9131,92 +University of South Carolina at Aiken,No,848,560,377,14,24,1855,1412,5800,3066,500,1500,62,62,14.8,3,5035,48 +University of South Carolina at Columbia,No,7693,5815,2328,30,66,12594,3661,8074,3522,495,2941,84,88,16.9,18,8246,63 +University of South Florida,No,7589,4676,1876,29,63,14770,10962,6760,3776,500,2180,84,89,17,7,11020,47 +University of Southern California,Yes,12229,8498,2477,45,71,13259,1429,17230,6482,600,2210,90,94,11.4,10,17007,68 +University of Southern Colorado,No,1401,1239,605,10,34,3716,675,7100,4380,540,2948,63,88,19.4,0,5389,36 +University of Southern Indiana,No,2379,2133,1292,8,25,4283,2973,4973,3192,500,1425,56,65,22,21,4078,38 +University of Southern Mississippi,No,2850,2044,1046,20,50,9260,1387,4652,2470,500,500,78,99,18.7,23,5917,45 +University of St. Thomas MN,Yes,2057,1807,828,26,53,4106,982,11712,4037,500,800,80,80,13.8,13,8546,89 +University of St. Thomas TX,Yes,374,280,185,45,77,995,408,8550,4050,500,1344,75,75,12.6,17,7237,62 +University of Tennessee at Knoxville,No,7473,5372,3013,27,53,15749,3237,5764,3262,750,3300,86,92,16.5,22,8612,53 +University of Texas at Arlington,No,3281,2559,1448,19,43,10975,8431,4422,2780,500,2850,73,73,21,4,4696,29 +University of Texas at Austin,No,14752,9572,5329,48,85,30017,5189,5130,3309,650,3140,91,99,19.7,11,7837,65 +University of Texas at San Antonio,No,4217,3100,1686,17,46,9375,5457,4104,5376,452,1200,94,100,25.3,3,4329,50 +University of the Arts,Yes,974,704,290,5,22,1145,39,12520,3860,1300,700,16,59,7.5,9,11641,57 +University of the Pacific,Yes,2459,1997,582,36,66,2664,299,16320,5326,646,1171,87,94,11.2,14,13706,65 +University of the South,Yes,1445,966,326,46,83,1129,24,15350,4080,450,810,89,93,10.3,52,18784,82 +University of Tulsa,Yes,1712,1557,696,41,68,2936,433,11750,4160,1200,2350,94,96,11.5,10,11743,47 +University of Utah,No,5095,4491,2400,27,53,13894,8374,6857,3975,858,3093,89,93,12.8,9,9275,37 +University of Vermont,No,7663,6008,1735,18,51,7353,1674,15516,4928,500,990,87,90,9.9,10,12646,79 +University of Virginia,No,15849,5384,2678,74,95,11278,114,12212,3792,500,1000,90,92,9.5,22,13597,95 +University of Washington,No,12749,7025,3343,40,81,20356,4582,8199,4218,708,2172,96,94,9,10,16527,65 +University of West Florida,No,1558,1254,472,20,57,3754,2477,6172,3994,541,1387,83,87,23.4,12,8488,53 +University of Wisconsin-Stout,No,2593,1966,1030,9,32,6038,579,6704,2592,376,1750,78,78,21,17,6254,65 +University of Wisconsin-Superior,No,910,910,342,14,53,1434,417,7032,2780,550,1960,75,81,15.2,15,6490,36 +University of Wisconsin-Whitewater,No,4400,3719,1472,12,38,7804,1552,6950,2500,300,1200,90,95,23.1,16,5559,67 +University of Wisconsin at Green Bay,No,2409,1939,759,17,50,3819,1347,6900,2800,475,1200,81,89,22.2,1,5968,46 +University of Wisconsin at Madison,No,14901,10932,4631,36,80,23945,2200,9096,4290,535,1545,93,96,11.5,20,11006,72 +University of Wisconsin at Milwaukee,No,5244,3782,1930,12,37,11561,7443,8786,2964,570,1980,79,87,15.9,8,8094,38 +University of Wyoming,No,2029,1516,1073,23,46,7535,1488,5988,3422,600,1500,91,94,15.1,13,8745,45 +Upper Iowa University,Yes,663,452,192,10,35,1481,1160,8840,3060,500,1000,69,75,17.4,19,3733,78 +Ursinus College,Yes,1399,1026,308,44,77,1131,17,14900,5160,500,800,82,85,11.6,40,12082,79 +Ursuline College,Yes,325,260,86,21,47,699,717,9600,4202,450,750,39,69,10.5,15,7164,68 +Valley City State University,No,368,344,212,5,27,863,189,4286,2570,600,2000,39,41,14.9,25,4958,40 +Valparaiso University,Yes,2075,1727,520,49,81,2501,198,11800,3260,500,800,87,89,14.2,23,9681,95 +Vanderbilt University,Yes,7791,4690,1499,71,92,5500,90,17865,6525,630,952,93,98,5.8,26,23850,83 +Vassar College,Yes,3550,1877,653,53,87,2164,77,18920,5950,600,800,90,98,9.7,39,17089,90 +Villanova University,Yes,7759,5588,1477,30,68,6362,1292,15925,6507,400,300,89,90,13.4,24,10458,96 +Virginia Commonwealth University,No,4963,3497,1567,18,45,10262,5065,10217,4182,500,3630,81,87,8.7,11,11183,45 +Virginia State University,No,2996,2440,704,2,30,3006,338,5587,4845,500,600,61,63,16,11,5733,31 +Virginia Tech,No,15712,11719,4277,29,53,18511,604,10260,3176,740,2200,85,89,13.8,20,8944,73 +Virginia Union University,Yes,1847,1610,453,19,59,1298,67,7384,3494,500,1763,51,67,13.7,8,6757,30 +Virginia Wesleyan College,Yes,1470,900,287,20,49,1130,417,10900,5100,500,550,70,81,15.7,14,7804,68 +Viterbo College,Yes,647,518,271,17,43,1014,387,9140,3365,500,2245,51,65,10.7,31,8050,73 +Voorhees College,Yes,1465,1006,188,10,30,703,20,4450,2522,500,1200,43,43,22.9,3,5861,58 +Wabash College,Yes,800,623,256,41,76,801,5,12925,4195,500,635,78,85,9.9,55,14904,72 +Wagner College,Yes,1416,1015,417,10,44,1324,117,13500,5800,585,1700,67,78,13.2,23,9006,75 +Wake Forest University,Yes,5661,2392,903,75,88,3499,172,13850,4360,500,1250,95,97,4.3,37,41766,89 +Walsh University,Yes,1092,890,477,27,92,847,497,8670,4180,500,1450,42,58,11.3,33,5738,68 +Warren Wilson College,Yes,440,311,112,25,49,466,7,10000,3052,400,1100,65,75,11.4,20,9430,63 +Wartburg College,Yes,1231,1074,345,34,66,1295,105,11600,3610,400,850,66,91,12.4,37,7735,67 +Washington and Jefferson College,Yes,1305,1100,334,42,64,1098,151,16260,4005,300,500,91,91,12.1,40,10162,86 +Washington and Lee University,Yes,3315,1096,425,68,93,1584,3,13750,4619,680,1115,81,96,9.6,45,15736,90 +Washington College,Yes,1209,942,214,31,60,822,46,15276,5318,500,300,79,86,11.2,37,10830,65 +Washington State University,No,6540,5839,2440,31,70,14445,1344,8200,4210,800,2719,84,87,16.9,30,10912,56 +Washington University,Yes,7654,5259,1254,62,93,4879,1274,18350,5775,768,1512,91,98,3.9,31,45702,90 +Wayne State College,No,1373,1373,724,6,21,2754,474,2700,2660,540,1660,60,68,20.3,29,4550,52 +Waynesburg College,Yes,1190,978,324,12,30,1280,61,8840,3620,500,1200,57,58,16.2,26,6563,63 +Webber College,Yes,280,143,79,5,27,327,110,5590,2900,650,1952,53,63,15.1,4,4839,90 +Webster University,Yes,665,462,226,17,44,1739,1550,9160,4340,500,500,68,68,20.6,14,6951,48 +Wellesley College,Yes,2895,1249,579,80,96,2195,156,18345,5995,500,700,94,98,10.6,51,21409,91 +Wells College,Yes,318,240,130,40,85,416,19,14900,5550,600,500,93,98,8.3,42,13935,69 +Wentworth Institute of Technology,Yes,1480,1257,452,6,25,2961,572,9850,6050,850,920,10,68,15.4,8,17858,64 +Wesley College,Yes,980,807,350,10,25,872,448,9890,4674,500,1350,52,57,14.4,15,6243,84 +Wesleyan University,Yes,4772,1973,712,60,86,2714,27,19130,5600,1400,1400,90,94,12.1,39,16262,92 +West Chester University of Penn.,No,6502,3539,1372,11,51,7484,1904,7844,4108,400,2000,76,79,15.3,16,6773,52 +West Liberty State College,No,1164,1062,478,12,25,2138,227,4470,2890,600,1210,33,33,16.3,10,4249,60 +West Virginia Wesleyan College,Yes,1566,1400,483,28,55,1509,170,14200,3775,450,1100,58,81,16.4,42,8080,67 +Western Carolina University,No,3224,2519,1057,11,31,5000,706,6390,2380,110,1622,67,78,14.6,9,6554,55 +Western Maryland College,Yes,1205,984,278,31,50,1071,98,14510,5340,500,1400,84,91,12.5,39,10026,60 +Western Michigan University,No,9167,7191,2738,24,53,15739,4278,6940,4100,500,1700,80,84,24.7,11,5983,55 +Western New England College,Yes,1650,1471,409,7,21,1803,1116,8994,5500,498,2065,74,97,15.4,15,8409,59 +Western State College of Colorado,No,2702,1623,604,7,24,2315,146,5918,3755,500,2050,76,79,19.4,4,4599,52 +Western Washington University,No,5548,3563,1549,30,71,8909,506,8124,4144,639,2385,83,89,22.7,10,7203,61 +Westfield State College,No,3100,2150,825,3,20,3234,941,5542,3788,500,1300,75,79,15.7,20,4222,65 +Westminster College MO,Yes,662,553,184,20,43,665,37,10720,4050,600,1650,66,70,12.5,20,7925,62 +Westminster College,Yes,996,866,377,29,58,1411,72,12065,3615,430,685,62,78,12.5,41,8596,80 +Westminster College of Salt Lake City,Yes,917,720,213,21,60,979,743,8820,4050,600,2025,68,83,10.5,34,7170,50 +Westmont College,No,950,713,351,42,72,1276,9,14320,5304,490,1410,77,77,14.9,17,8837,87 +Wheaton College IL,Yes,1432,920,548,56,84,2200,56,11480,4200,530,1400,81,83,12.7,40,11916,85 +Westminster College PA,Yes,1738,1373,417,21,55,1335,30,18460,5970,700,850,92,96,13.2,41,22704,71 +Wheeling Jesuit College,Yes,903,755,213,15,49,971,305,10500,4545,600,600,66,71,14.1,27,7494,72 +Whitman College,Yes,1861,998,359,45,77,1220,46,16670,4900,750,800,80,83,10.5,51,13198,72 +Whittier College,Yes,1681,1069,344,35,63,1235,30,16249,5699,500,1998,84,92,13.6,29,11778,52 +Whitworth College,Yes,1121,926,372,43,70,1270,160,12660,4500,678,2424,80,80,16.9,20,8328,80 +Widener University,Yes,2139,1492,502,24,64,2186,2171,12350,5370,500,1350,88,86,12.6,19,9603,63 +Wilkes University,Yes,1631,1431,434,15,36,1803,603,11150,5130,550,1260,78,92,13.3,24,8543,67 +Willamette University,Yes,1658,1327,395,49,80,1595,159,14800,4620,400,790,91,94,13.3,37,10779,68 +William Jewell College,Yes,663,547,315,32,67,1279,75,10060,2970,500,2600,74,80,11.2,19,7885,59 +William Woods University,Yes,469,435,227,17,39,851,120,10535,4365,550,3700,39,66,12.9,16,7438,52 +Williams College,Yes,4186,1245,526,81,96,1988,29,19629,5790,500,1200,94,99,9,64,22014,99 +Wilson College,Yes,167,130,46,16,50,199,676,11428,5084,450,475,67,76,8.3,43,10291,67 +Wingate College,Yes,1239,1017,383,10,34,1207,157,7820,3400,550,1550,69,81,13.9,8,7264,91 +Winona State University,No,3325,2047,1301,20,45,5800,872,4200,2700,300,1200,53,60,20.2,18,5318,58 +Winthrop University,No,2320,1805,769,24,61,3395,670,6400,3392,580,2150,71,80,12.8,26,6729,59 +Wisconsin Lutheran College,Yes,152,128,75,17,41,282,22,9100,3700,500,1400,48,48,8.5,26,8960,50 +Wittenberg University,Yes,1979,1739,575,42,68,1980,144,15948,4404,400,800,82,95,12.8,29,10414,78 +Wofford College,Yes,1501,935,273,51,83,1059,34,12680,4150,605,1440,91,92,15.3,42,7875,75 +Worcester Polytechnic Institute,Yes,2768,2314,682,49,86,2802,86,15884,5370,530,730,92,94,15.2,34,10774,82 +Worcester State College,No,2197,1515,543,4,26,3089,2029,6797,3900,500,1200,60,60,21,14,4469,40 +Xavier University,Yes,1959,1805,695,24,47,2849,1107,11520,4960,600,1250,73,75,13.3,31,9189,83 +Xavier University of Louisiana,Yes,2097,1915,695,34,61,2793,166,6900,4200,617,781,67,75,14.4,20,8323,49 +Yale University,Yes,10705,2453,1317,95,99,5217,83,19840,6510,630,2115,96,96,5.8,49,40386,99 +York College of Pennsylvania,Yes,2989,1855,691,28,63,2988,1726,4990,3560,500,1250,75,75,18.1,28,4509,99 diff --git a/datasets/Credit.csv b/datasets/Credit.csv new file mode 100644 index 0000000..997197e --- /dev/null +++ b/datasets/Credit.csv @@ -0,0 +1,401 @@ +,Income,Limit,Rating,Cards,Age,Education,Gender,Student,Married,Ethnicity,Balance +1,14.891,3606,283,2,34,11,Male,No,Yes,Caucasian,333 +2,106.025,6645,483,3,82,15,Female,Yes,Yes,Asian,903 +3,104.593,7075,514,4,71,11,Male,No,No,Asian,580 +4,148.924,9504,681,3,36,11,Female,No,No,Asian,964 +5,55.882,4897,357,2,68,16,Male,No,Yes,Caucasian,331 +6,80.18,8047,569,4,77,10,Male,No,No,Caucasian,1151 +7,20.996,3388,259,2,37,12,Female,No,No,African American,203 +8,71.408,7114,512,2,87,9,Male,No,No,Asian,872 +9,15.125,3300,266,5,66,13,Female,No,No,Caucasian,279 +10,71.061,6819,491,3,41,19,Female,Yes,Yes,African American,1350 +11,63.095,8117,589,4,30,14,Male,No,Yes,Caucasian,1407 +12,15.045,1311,138,3,64,16,Male,No,No,Caucasian,0 +13,80.616,5308,394,1,57,7,Female,No,Yes,Asian,204 +14,43.682,6922,511,1,49,9,Male,No,Yes,Caucasian,1081 +15,19.144,3291,269,2,75,13,Female,No,No,African American,148 +16,20.089,2525,200,3,57,15,Female,No,Yes,African American,0 +17,53.598,3714,286,3,73,17,Female,No,Yes,African American,0 +18,36.496,4378,339,3,69,15,Female,No,Yes,Asian,368 +19,49.57,6384,448,1,28,9,Female,No,Yes,Asian,891 +20,42.079,6626,479,2,44,9,Male,No,No,Asian,1048 +21,17.7,2860,235,4,63,16,Female,No,No,Asian,89 +22,37.348,6378,458,1,72,17,Female,No,No,Caucasian,968 +23,20.103,2631,213,3,61,10,Male,No,Yes,African American,0 +24,64.027,5179,398,5,48,8,Male,No,Yes,African American,411 +25,10.742,1757,156,3,57,15,Female,No,No,Caucasian,0 +26,14.09,4323,326,5,25,16,Female,No,Yes,African American,671 +27,42.471,3625,289,6,44,12,Female,Yes,No,Caucasian,654 +28,32.793,4534,333,2,44,16,Male,No,No,African American,467 +29,186.634,13414,949,2,41,14,Female,No,Yes,African American,1809 +30,26.813,5611,411,4,55,16,Female,No,No,Caucasian,915 +31,34.142,5666,413,4,47,5,Female,No,Yes,Caucasian,863 +32,28.941,2733,210,5,43,16,Male,No,Yes,Asian,0 +33,134.181,7838,563,2,48,13,Female,No,No,Caucasian,526 +34,31.367,1829,162,4,30,10,Male,No,Yes,Caucasian,0 +35,20.15,2646,199,2,25,14,Female,No,Yes,Asian,0 +36,23.35,2558,220,3,49,12,Female,Yes,No,Caucasian,419 +37,62.413,6457,455,2,71,11,Female,No,Yes,Caucasian,762 +38,30.007,6481,462,2,69,9,Female,No,Yes,Caucasian,1093 +39,11.795,3899,300,4,25,10,Female,No,No,Caucasian,531 +40,13.647,3461,264,4,47,14,Male,No,Yes,Caucasian,344 +41,34.95,3327,253,3,54,14,Female,No,No,African American,50 +42,113.659,7659,538,2,66,15,Male,Yes,Yes,African American,1155 +43,44.158,4763,351,2,66,13,Female,No,Yes,Asian,385 +44,36.929,6257,445,1,24,14,Female,No,Yes,Asian,976 +45,31.861,6375,469,3,25,16,Female,No,Yes,Caucasian,1120 +46,77.38,7569,564,3,50,12,Female,No,Yes,Caucasian,997 +47,19.531,5043,376,2,64,16,Female,Yes,Yes,Asian,1241 +48,44.646,4431,320,2,49,15,Male,Yes,Yes,Caucasian,797 +49,44.522,2252,205,6,72,15,Male,No,Yes,Asian,0 +50,43.479,4569,354,4,49,13,Male,Yes,Yes,African American,902 +51,36.362,5183,376,3,49,15,Male,No,Yes,African American,654 +52,39.705,3969,301,2,27,20,Male,No,Yes,African American,211 +53,44.205,5441,394,1,32,12,Male,No,Yes,Caucasian,607 +54,16.304,5466,413,4,66,10,Male,No,Yes,Asian,957 +55,15.333,1499,138,2,47,9,Female,No,Yes,Asian,0 +56,32.916,1786,154,2,60,8,Female,No,Yes,Asian,0 +57,57.1,4742,372,7,79,18,Female,No,Yes,Asian,379 +58,76.273,4779,367,4,65,14,Female,No,Yes,Caucasian,133 +59,10.354,3480,281,2,70,17,Male,No,Yes,Caucasian,333 +60,51.872,5294,390,4,81,17,Female,No,No,Caucasian,531 +61,35.51,5198,364,2,35,20,Female,No,No,Asian,631 +62,21.238,3089,254,3,59,10,Female,No,No,Caucasian,108 +63,30.682,1671,160,2,77,7,Female,No,No,Caucasian,0 +64,14.132,2998,251,4,75,17,Male,No,No,Caucasian,133 +65,32.164,2937,223,2,79,15,Female,No,Yes,African American,0 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+257,25.936,1774,135,2,71,14,Female,No,No,Asian,0 +258,15.629,2493,186,1,60,14,Male,No,Yes,Asian,0 +259,41.4,2561,215,2,36,14,Male,No,Yes,Caucasian,0 +260,33.657,6196,450,6,55,9,Female,No,No,Caucasian,1092 +261,67.937,5184,383,4,63,12,Male,No,Yes,Asian,345 +262,180.379,9310,665,3,67,8,Female,Yes,Yes,Asian,1050 +263,10.588,4049,296,1,66,13,Female,No,Yes,Caucasian,465 +264,29.725,3536,270,2,52,15,Female,No,No,African American,133 +265,27.999,5107,380,1,55,10,Male,No,Yes,Caucasian,651 +266,40.885,5013,379,3,46,13,Female,No,Yes,African American,549 +267,88.83,4952,360,4,86,16,Female,No,Yes,Caucasian,15 +268,29.638,5833,433,3,29,15,Female,No,Yes,Asian,942 +269,25.988,1349,142,4,82,12,Male,No,No,Caucasian,0 +270,39.055,5565,410,4,48,18,Female,No,Yes,Caucasian,772 +271,15.866,3085,217,1,39,13,Male,No,No,Caucasian,136 +272,44.978,4866,347,1,30,10,Female,No,No,Caucasian,436 +273,30.413,3690,299,2,25,15,Female,Yes,No,Asian,728 +274,16.751,4706,353,6,48,14,Male,Yes,No,Asian,1255 +275,30.55,5869,439,5,81,9,Female,No,No,African American,967 +276,163.329,8732,636,3,50,14,Male,No,Yes,Caucasian,529 +277,23.106,3476,257,2,50,15,Female,No,No,Caucasian,209 +278,41.532,5000,353,2,50,12,Male,No,Yes,Caucasian,531 +279,128.04,6982,518,2,78,11,Female,No,Yes,Caucasian,250 +280,54.319,3063,248,3,59,8,Female,Yes,No,Caucasian,269 +281,53.401,5319,377,3,35,12,Female,No,No,African American,541 +282,36.142,1852,183,3,33,13,Female,No,No,African American,0 +283,63.534,8100,581,2,50,17,Female,No,Yes,Caucasian,1298 +284,49.927,6396,485,3,75,17,Female,No,Yes,Caucasian,890 +285,14.711,2047,167,2,67,6,Male,No,Yes,Caucasian,0 +286,18.967,1626,156,2,41,11,Female,No,Yes,Asian,0 +287,18.036,1552,142,2,48,15,Female,No,No,Caucasian,0 +288,60.449,3098,272,4,69,8,Male,No,Yes,Caucasian,0 +289,16.711,5274,387,3,42,16,Female,No,Yes,Asian,863 +290,10.852,3907,296,2,30,9,Male,No,No,Caucasian,485 +291,26.37,3235,268,5,78,11,Male,No,Yes,Asian,159 +292,24.088,3665,287,4,56,13,Female,No,Yes,Caucasian,309 +293,51.532,5096,380,2,31,15,Male,No,Yes,Caucasian,481 +294,140.672,11200,817,7,46,9,Male,No,Yes,African American,1677 +295,42.915,2532,205,4,42,13,Male,No,Yes,Asian,0 +296,27.272,1389,149,5,67,10,Female,No,Yes,Caucasian,0 +297,65.896,5140,370,1,49,17,Female,No,Yes,Caucasian,293 +298,55.054,4381,321,3,74,17,Male,No,Yes,Asian,188 +299,20.791,2672,204,1,70,18,Female,No,No,African American,0 +300,24.919,5051,372,3,76,11,Female,No,Yes,African American,711 +301,21.786,4632,355,1,50,17,Male,No,Yes,Caucasian,580 +302,31.335,3526,289,3,38,7,Female,No,No,Caucasian,172 +303,59.855,4964,365,1,46,13,Female,No,Yes,Caucasian,295 +304,44.061,4970,352,1,79,11,Male,No,Yes,African American,414 +305,82.706,7506,536,2,64,13,Female,No,Yes,Asian,905 +306,24.46,1924,165,2,50,14,Female,No,Yes,Asian,0 +307,45.12,3762,287,3,80,8,Male,No,Yes,Caucasian,70 +308,75.406,3874,298,3,41,14,Female,No,Yes,Asian,0 +309,14.956,4640,332,2,33,6,Male,No,No,Asian,681 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+344,10.735,3746,280,2,44,17,Female,No,Yes,Caucasian,410 +345,48.218,5199,401,7,39,10,Male,No,Yes,Asian,633 +346,30.012,1511,137,2,33,17,Male,No,Yes,Caucasian,0 +347,21.551,5380,420,5,51,18,Male,No,Yes,Asian,907 +348,160.231,10748,754,2,69,17,Male,No,No,Caucasian,1192 +349,13.433,1134,112,3,70,14,Male,No,Yes,Caucasian,0 +350,48.577,5145,389,3,71,13,Female,No,Yes,Asian,503 +351,30.002,1561,155,4,70,13,Female,No,Yes,Caucasian,0 +352,61.62,5140,374,1,71,9,Male,No,Yes,Caucasian,302 +353,104.483,7140,507,2,41,14,Male,No,Yes,African American,583 +354,41.868,4716,342,2,47,18,Male,No,No,Caucasian,425 +355,12.068,3873,292,1,44,18,Female,No,Yes,Asian,413 +356,180.682,11966,832,2,58,8,Female,No,Yes,African American,1405 +357,34.48,6090,442,3,36,14,Male,No,No,Caucasian,962 +358,39.609,2539,188,1,40,14,Male,No,Yes,Asian,0 +359,30.111,4336,339,1,81,18,Male,No,Yes,Caucasian,347 +360,12.335,4471,344,3,79,12,Male,No,Yes,African American,611 +361,53.566,5891,434,4,82,10,Female,No,No,Caucasian,712 +362,53.217,4943,362,2,46,16,Female,No,Yes,Asian,382 +363,26.162,5101,382,3,62,19,Female,No,No,African American,710 +364,64.173,6127,433,1,80,10,Male,No,Yes,Caucasian,578 +365,128.669,9824,685,3,67,16,Male,No,Yes,Asian,1243 +366,113.772,6442,489,4,69,15,Male,Yes,Yes,Caucasian,790 +367,61.069,7871,564,3,56,14,Male,No,Yes,Caucasian,1264 +368,23.793,3615,263,2,70,14,Male,No,No,African American,216 +369,89,5759,440,3,37,6,Female,No,No,Caucasian,345 +370,71.682,8028,599,3,57,16,Male,No,Yes,Caucasian,1208 +371,35.61,6135,466,4,40,12,Male,No,No,Caucasian,992 +372,39.116,2150,173,4,75,15,Male,No,No,Caucasian,0 +373,19.782,3782,293,2,46,16,Female,Yes,No,Caucasian,840 +374,55.412,5354,383,2,37,16,Female,Yes,Yes,Caucasian,1003 +375,29.4,4840,368,3,76,18,Female,No,Yes,Caucasian,588 +376,20.974,5673,413,5,44,16,Female,No,Yes,Caucasian,1000 +377,87.625,7167,515,2,46,10,Female,No,No,African American,767 +378,28.144,1567,142,3,51,10,Male,No,Yes,Caucasian,0 +379,19.349,4941,366,1,33,19,Male,No,Yes,Caucasian,717 +380,53.308,2860,214,1,84,10,Male,No,Yes,Caucasian,0 +381,115.123,7760,538,3,83,14,Female,No,No,African American,661 +382,101.788,8029,574,2,84,11,Male,No,Yes,Caucasian,849 +383,24.824,5495,409,1,33,9,Male,Yes,No,Caucasian,1352 +384,14.292,3274,282,9,64,9,Male,No,Yes,Caucasian,382 +385,20.088,1870,180,3,76,16,Male,No,No,African American,0 +386,26.4,5640,398,3,58,15,Female,No,No,Asian,905 +387,19.253,3683,287,4,57,10,Male,No,No,African American,371 +388,16.529,1357,126,3,62,9,Male,No,No,Asian,0 +389,37.878,6827,482,2,80,13,Female,No,No,Caucasian,1129 +390,83.948,7100,503,2,44,18,Male,No,No,Caucasian,806 +391,135.118,10578,747,3,81,15,Female,No,Yes,Asian,1393 +392,73.327,6555,472,2,43,15,Female,No,No,Caucasian,721 +393,25.974,2308,196,2,24,10,Male,No,No,Asian,0 +394,17.316,1335,138,2,65,13,Male,No,No,African American,0 +395,49.794,5758,410,4,40,8,Male,No,No,Caucasian,734 +396,12.096,4100,307,3,32,13,Male,No,Yes,Caucasian,560 +397,13.364,3838,296,5,65,17,Male,No,No,African American,480 +398,57.872,4171,321,5,67,12,Female,No,Yes,Caucasian,138 +399,37.728,2525,192,1,44,13,Male,No,Yes,Caucasian,0 +400,18.701,5524,415,5,64,7,Female,No,No,Asian,966 diff --git a/datasets/Heart.csv b/datasets/Heart.csv new file mode 100644 index 0000000..deed37c --- /dev/null +++ b/datasets/Heart.csv @@ -0,0 +1,304 @@ +"","Age","Sex","ChestPain","RestBP","Chol","Fbs","RestECG","MaxHR","ExAng","Oldpeak","Slope","Ca","Thal","AHD" +"1",63,1,"typical",145,233,1,2,150,0,2.3,3,0,"fixed","No" +"2",67,1,"asymptomatic",160,286,0,2,108,1,1.5,2,3,"normal","Yes" +"3",67,1,"asymptomatic",120,229,0,2,129,1,2.6,2,2,"reversable","Yes" +"4",37,1,"nonanginal",130,250,0,0,187,0,3.5,3,0,"normal","No" +"5",41,0,"nontypical",130,204,0,2,172,0,1.4,1,0,"normal","No" +"6",56,1,"nontypical",120,236,0,0,178,0,0.8,1,0,"normal","No" +"7",62,0,"asymptomatic",140,268,0,2,160,0,3.6,3,2,"normal","Yes" +"8",57,0,"asymptomatic",120,354,0,0,163,1,0.6,1,0,"normal","No" +"9",63,1,"asymptomatic",130,254,0,2,147,0,1.4,2,1,"reversable","Yes" +"10",53,1,"asymptomatic",140,203,1,2,155,1,3.1,3,0,"reversable","Yes" +"11",57,1,"asymptomatic",140,192,0,0,148,0,0.4,2,0,"fixed","No" +"12",56,0,"nontypical",140,294,0,2,153,0,1.3,2,0,"normal","No" +"13",56,1,"nonanginal",130,256,1,2,142,1,0.6,2,1,"fixed","Yes" +"14",44,1,"nontypical",120,263,0,0,173,0,0,1,0,"reversable","No" +"15",52,1,"nonanginal",172,199,1,0,162,0,0.5,1,0,"reversable","No" +"16",57,1,"nonanginal",150,168,0,0,174,0,1.6,1,0,"normal","No" +"17",48,1,"nontypical",110,229,0,0,168,0,1,3,0,"reversable","Yes" +"18",54,1,"asymptomatic",140,239,0,0,160,0,1.2,1,0,"normal","No" +"19",48,0,"nonanginal",130,275,0,0,139,0,0.2,1,0,"normal","No" +"20",49,1,"nontypical",130,266,0,0,171,0,0.6,1,0,"normal","No" +"21",64,1,"typical",110,211,0,2,144,1,1.8,2,0,"normal","No" +"22",58,0,"typical",150,283,1,2,162,0,1,1,0,"normal","No" +"23",58,1,"nontypical",120,284,0,2,160,0,1.8,2,0,"normal","Yes" +"24",58,1,"nonanginal",132,224,0,2,173,0,3.2,1,2,"reversable","Yes" +"25",60,1,"asymptomatic",130,206,0,2,132,1,2.4,2,2,"reversable","Yes" +"26",50,0,"nonanginal",120,219,0,0,158,0,1.6,2,0,"normal","No" +"27",58,0,"nonanginal",120,340,0,0,172,0,0,1,0,"normal","No" +"28",66,0,"typical",150,226,0,0,114,0,2.6,3,0,"normal","No" +"29",43,1,"asymptomatic",150,247,0,0,171,0,1.5,1,0,"normal","No" +"30",40,1,"asymptomatic",110,167,0,2,114,1,2,2,0,"reversable","Yes" +"31",69,0,"typical",140,239,0,0,151,0,1.8,1,2,"normal","No" +"32",60,1,"asymptomatic",117,230,1,0,160,1,1.4,1,2,"reversable","Yes" +"33",64,1,"nonanginal",140,335,0,0,158,0,0,1,0,"normal","Yes" +"34",59,1,"asymptomatic",135,234,0,0,161,0,0.5,2,0,"reversable","No" +"35",44,1,"nonanginal",130,233,0,0,179,1,0.4,1,0,"normal","No" +"36",42,1,"asymptomatic",140,226,0,0,178,0,0,1,0,"normal","No" +"37",43,1,"asymptomatic",120,177,0,2,120,1,2.5,2,0,"reversable","Yes" +"38",57,1,"asymptomatic",150,276,0,2,112,1,0.6,2,1,"fixed","Yes" +"39",55,1,"asymptomatic",132,353,0,0,132,1,1.2,2,1,"reversable","Yes" +"40",61,1,"nonanginal",150,243,1,0,137,1,1,2,0,"normal","No" +"41",65,0,"asymptomatic",150,225,0,2,114,0,1,2,3,"reversable","Yes" +"42",40,1,"typical",140,199,0,0,178,1,1.4,1,0,"reversable","No" +"43",71,0,"nontypical",160,302,0,0,162,0,0.4,1,2,"normal","No" +"44",59,1,"nonanginal",150,212,1,0,157,0,1.6,1,0,"normal","No" +"45",61,0,"asymptomatic",130,330,0,2,169,0,0,1,0,"normal","Yes" +"46",58,1,"nonanginal",112,230,0,2,165,0,2.5,2,1,"reversable","Yes" +"47",51,1,"nonanginal",110,175,0,0,123,0,0.6,1,0,"normal","No" +"48",50,1,"asymptomatic",150,243,0,2,128,0,2.6,2,0,"reversable","Yes" +"49",65,0,"nonanginal",140,417,1,2,157,0,0.8,1,1,"normal","No" +"50",53,1,"nonanginal",130,197,1,2,152,0,1.2,3,0,"normal","No" +"51",41,0,"nontypical",105,198,0,0,168,0,0,1,1,"normal","No" +"52",65,1,"asymptomatic",120,177,0,0,140,0,0.4,1,0,"reversable","No" +"53",44,1,"asymptomatic",112,290,0,2,153,0,0,1,1,"normal","Yes" +"54",44,1,"nontypical",130,219,0,2,188,0,0,1,0,"normal","No" +"55",60,1,"asymptomatic",130,253,0,0,144,1,1.4,1,1,"reversable","Yes" +"56",54,1,"asymptomatic",124,266,0,2,109,1,2.2,2,1,"reversable","Yes" +"57",50,1,"nonanginal",140,233,0,0,163,0,0.6,2,1,"reversable","Yes" +"58",41,1,"asymptomatic",110,172,0,2,158,0,0,1,0,"reversable","Yes" +"59",54,1,"nonanginal",125,273,0,2,152,0,0.5,3,1,"normal","No" +"60",51,1,"typical",125,213,0,2,125,1,1.4,1,1,"normal","No" +"61",51,0,"asymptomatic",130,305,0,0,142,1,1.2,2,0,"reversable","Yes" +"62",46,0,"nonanginal",142,177,0,2,160,1,1.4,3,0,"normal","No" +"63",58,1,"asymptomatic",128,216,0,2,131,1,2.2,2,3,"reversable","Yes" +"64",54,0,"nonanginal",135,304,1,0,170,0,0,1,0,"normal","No" +"65",54,1,"asymptomatic",120,188,0,0,113,0,1.4,2,1,"reversable","Yes" +"66",60,1,"asymptomatic",145,282,0,2,142,1,2.8,2,2,"reversable","Yes" +"67",60,1,"nonanginal",140,185,0,2,155,0,3,2,0,"normal","Yes" +"68",54,1,"nonanginal",150,232,0,2,165,0,1.6,1,0,"reversable","No" +"69",59,1,"asymptomatic",170,326,0,2,140,1,3.4,3,0,"reversable","Yes" +"70",46,1,"nonanginal",150,231,0,0,147,0,3.6,2,0,"normal","Yes" +"71",65,0,"nonanginal",155,269,0,0,148,0,0.8,1,0,"normal","No" +"72",67,1,"asymptomatic",125,254,1,0,163,0,0.2,2,2,"reversable","Yes" +"73",62,1,"asymptomatic",120,267,0,0,99,1,1.8,2,2,"reversable","Yes" +"74",65,1,"asymptomatic",110,248,0,2,158,0,0.6,1,2,"fixed","Yes" +"75",44,1,"asymptomatic",110,197,0,2,177,0,0,1,1,"normal","Yes" +"76",65,0,"nonanginal",160,360,0,2,151,0,0.8,1,0,"normal","No" +"77",60,1,"asymptomatic",125,258,0,2,141,1,2.8,2,1,"reversable","Yes" +"78",51,0,"nonanginal",140,308,0,2,142,0,1.5,1,1,"normal","No" +"79",48,1,"nontypical",130,245,0,2,180,0,0.2,2,0,"normal","No" +"80",58,1,"asymptomatic",150,270,0,2,111,1,0.8,1,0,"reversable","Yes" +"81",45,1,"asymptomatic",104,208,0,2,148,1,3,2,0,"normal","No" +"82",53,0,"asymptomatic",130,264,0,2,143,0,0.4,2,0,"normal","No" +"83",39,1,"nonanginal",140,321,0,2,182,0,0,1,0,"normal","No" +"84",68,1,"nonanginal",180,274,1,2,150,1,1.6,2,0,"reversable","Yes" +"85",52,1,"nontypical",120,325,0,0,172,0,0.2,1,0,"normal","No" +"86",44,1,"nonanginal",140,235,0,2,180,0,0,1,0,"normal","No" +"87",47,1,"nonanginal",138,257,0,2,156,0,0,1,0,"normal","No" +"88",53,0,"nonanginal",128,216,0,2,115,0,0,1,0,NA,"No" +"89",53,0,"asymptomatic",138,234,0,2,160,0,0,1,0,"normal","No" +"90",51,0,"nonanginal",130,256,0,2,149,0,0.5,1,0,"normal","No" +"91",66,1,"asymptomatic",120,302,0,2,151,0,0.4,2,0,"normal","No" +"92",62,0,"asymptomatic",160,164,0,2,145,0,6.2,3,3,"reversable","Yes" +"93",62,1,"nonanginal",130,231,0,0,146,0,1.8,2,3,"reversable","No" +"94",44,0,"nonanginal",108,141,0,0,175,0,0.6,2,0,"normal","No" +"95",63,0,"nonanginal",135,252,0,2,172,0,0,1,0,"normal","No" +"96",52,1,"asymptomatic",128,255,0,0,161,1,0,1,1,"reversable","Yes" +"97",59,1,"asymptomatic",110,239,0,2,142,1,1.2,2,1,"reversable","Yes" +"98",60,0,"asymptomatic",150,258,0,2,157,0,2.6,2,2,"reversable","Yes" +"99",52,1,"nontypical",134,201,0,0,158,0,0.8,1,1,"normal","No" +"100",48,1,"asymptomatic",122,222,0,2,186,0,0,1,0,"normal","No" +"101",45,1,"asymptomatic",115,260,0,2,185,0,0,1,0,"normal","No" +"102",34,1,"typical",118,182,0,2,174,0,0,1,0,"normal","No" +"103",57,0,"asymptomatic",128,303,0,2,159,0,0,1,1,"normal","No" +"104",71,0,"nonanginal",110,265,1,2,130,0,0,1,1,"normal","No" +"105",49,1,"nonanginal",120,188,0,0,139,0,2,2,3,"reversable","Yes" +"106",54,1,"nontypical",108,309,0,0,156,0,0,1,0,"reversable","No" +"107",59,1,"asymptomatic",140,177,0,0,162,1,0,1,1,"reversable","Yes" +"108",57,1,"nonanginal",128,229,0,2,150,0,0.4,2,1,"reversable","Yes" +"109",61,1,"asymptomatic",120,260,0,0,140,1,3.6,2,1,"reversable","Yes" +"110",39,1,"asymptomatic",118,219,0,0,140,0,1.2,2,0,"reversable","Yes" +"111",61,0,"asymptomatic",145,307,0,2,146,1,1,2,0,"reversable","Yes" +"112",56,1,"asymptomatic",125,249,1,2,144,1,1.2,2,1,"normal","Yes" +"113",52,1,"typical",118,186,0,2,190,0,0,2,0,"fixed","No" +"114",43,0,"asymptomatic",132,341,1,2,136,1,3,2,0,"reversable","Yes" +"115",62,0,"nonanginal",130,263,0,0,97,0,1.2,2,1,"reversable","Yes" +"116",41,1,"nontypical",135,203,0,0,132,0,0,2,0,"fixed","No" +"117",58,1,"nonanginal",140,211,1,2,165,0,0,1,0,"normal","No" +"118",35,0,"asymptomatic",138,183,0,0,182,0,1.4,1,0,"normal","No" +"119",63,1,"asymptomatic",130,330,1,2,132,1,1.8,1,3,"reversable","Yes" +"120",65,1,"asymptomatic",135,254,0,2,127,0,2.8,2,1,"reversable","Yes" +"121",48,1,"asymptomatic",130,256,1,2,150,1,0,1,2,"reversable","Yes" +"122",63,0,"asymptomatic",150,407,0,2,154,0,4,2,3,"reversable","Yes" +"123",51,1,"nonanginal",100,222,0,0,143,1,1.2,2,0,"normal","No" +"124",55,1,"asymptomatic",140,217,0,0,111,1,5.6,3,0,"reversable","Yes" +"125",65,1,"typical",138,282,1,2,174,0,1.4,2,1,"normal","Yes" +"126",45,0,"nontypical",130,234,0,2,175,0,0.6,2,0,"normal","No" +"127",56,0,"asymptomatic",200,288,1,2,133,1,4,3,2,"reversable","Yes" +"128",54,1,"asymptomatic",110,239,0,0,126,1,2.8,2,1,"reversable","Yes" +"129",44,1,"nontypical",120,220,0,0,170,0,0,1,0,"normal","No" +"130",62,0,"asymptomatic",124,209,0,0,163,0,0,1,0,"normal","No" +"131",54,1,"nonanginal",120,258,0,2,147,0,0.4,2,0,"reversable","No" +"132",51,1,"nonanginal",94,227,0,0,154,1,0,1,1,"reversable","No" +"133",29,1,"nontypical",130,204,0,2,202,0,0,1,0,"normal","No" +"134",51,1,"asymptomatic",140,261,0,2,186,1,0,1,0,"normal","No" +"135",43,0,"nonanginal",122,213,0,0,165,0,0.2,2,0,"normal","No" +"136",55,0,"nontypical",135,250,0,2,161,0,1.4,2,0,"normal","No" +"137",70,1,"asymptomatic",145,174,0,0,125,1,2.6,3,0,"reversable","Yes" +"138",62,1,"nontypical",120,281,0,2,103,0,1.4,2,1,"reversable","Yes" +"139",35,1,"asymptomatic",120,198,0,0,130,1,1.6,2,0,"reversable","Yes" +"140",51,1,"nonanginal",125,245,1,2,166,0,2.4,2,0,"normal","No" +"141",59,1,"nontypical",140,221,0,0,164,1,0,1,0,"normal","No" +"142",59,1,"typical",170,288,0,2,159,0,0.2,2,0,"reversable","Yes" +"143",52,1,"nontypical",128,205,1,0,184,0,0,1,0,"normal","No" +"144",64,1,"nonanginal",125,309,0,0,131,1,1.8,2,0,"reversable","Yes" +"145",58,1,"nonanginal",105,240,0,2,154,1,0.6,2,0,"reversable","No" +"146",47,1,"nonanginal",108,243,0,0,152,0,0,1,0,"normal","Yes" +"147",57,1,"asymptomatic",165,289,1,2,124,0,1,2,3,"reversable","Yes" +"148",41,1,"nonanginal",112,250,0,0,179,0,0,1,0,"normal","No" +"149",45,1,"nontypical",128,308,0,2,170,0,0,1,0,"normal","No" +"150",60,0,"nonanginal",102,318,0,0,160,0,0,1,1,"normal","No" +"151",52,1,"typical",152,298,1,0,178,0,1.2,2,0,"reversable","No" +"152",42,0,"asymptomatic",102,265,0,2,122,0,0.6,2,0,"normal","No" +"153",67,0,"nonanginal",115,564,0,2,160,0,1.6,2,0,"reversable","No" +"154",55,1,"asymptomatic",160,289,0,2,145,1,0.8,2,1,"reversable","Yes" +"155",64,1,"asymptomatic",120,246,0,2,96,1,2.2,3,1,"normal","Yes" +"156",70,1,"asymptomatic",130,322,0,2,109,0,2.4,2,3,"normal","Yes" +"157",51,1,"asymptomatic",140,299,0,0,173,1,1.6,1,0,"reversable","Yes" +"158",58,1,"asymptomatic",125,300,0,2,171,0,0,1,2,"reversable","Yes" +"159",60,1,"asymptomatic",140,293,0,2,170,0,1.2,2,2,"reversable","Yes" +"160",68,1,"nonanginal",118,277,0,0,151,0,1,1,1,"reversable","No" +"161",46,1,"nontypical",101,197,1,0,156,0,0,1,0,"reversable","No" +"162",77,1,"asymptomatic",125,304,0,2,162,1,0,1,3,"normal","Yes" +"163",54,0,"nonanginal",110,214,0,0,158,0,1.6,2,0,"normal","No" +"164",58,0,"asymptomatic",100,248,0,2,122,0,1,2,0,"normal","No" +"165",48,1,"nonanginal",124,255,1,0,175,0,0,1,2,"normal","No" +"166",57,1,"asymptomatic",132,207,0,0,168,1,0,1,0,"reversable","No" +"167",52,1,"nonanginal",138,223,0,0,169,0,0,1,NA,"normal","No" +"168",54,0,"nontypical",132,288,1,2,159,1,0,1,1,"normal","No" +"169",35,1,"asymptomatic",126,282,0,2,156,1,0,1,0,"reversable","Yes" +"170",45,0,"nontypical",112,160,0,0,138,0,0,2,0,"normal","No" +"171",70,1,"nonanginal",160,269,0,0,112,1,2.9,2,1,"reversable","Yes" +"172",53,1,"asymptomatic",142,226,0,2,111,1,0,1,0,"reversable","No" +"173",59,0,"asymptomatic",174,249,0,0,143,1,0,2,0,"normal","Yes" +"174",62,0,"asymptomatic",140,394,0,2,157,0,1.2,2,0,"normal","No" +"175",64,1,"asymptomatic",145,212,0,2,132,0,2,2,2,"fixed","Yes" +"176",57,1,"asymptomatic",152,274,0,0,88,1,1.2,2,1,"reversable","Yes" +"177",52,1,"asymptomatic",108,233,1,0,147,0,0.1,1,3,"reversable","No" +"178",56,1,"asymptomatic",132,184,0,2,105,1,2.1,2,1,"fixed","Yes" +"179",43,1,"nonanginal",130,315,0,0,162,0,1.9,1,1,"normal","No" +"180",53,1,"nonanginal",130,246,1,2,173,0,0,1,3,"normal","No" +"181",48,1,"asymptomatic",124,274,0,2,166,0,0.5,2,0,"reversable","Yes" +"182",56,0,"asymptomatic",134,409,0,2,150,1,1.9,2,2,"reversable","Yes" +"183",42,1,"typical",148,244,0,2,178,0,0.8,1,2,"normal","No" +"184",59,1,"typical",178,270,0,2,145,0,4.2,3,0,"reversable","No" +"185",60,0,"asymptomatic",158,305,0,2,161,0,0,1,0,"normal","Yes" +"186",63,0,"nontypical",140,195,0,0,179,0,0,1,2,"normal","No" +"187",42,1,"nonanginal",120,240,1,0,194,0,0.8,3,0,"reversable","No" +"188",66,1,"nontypical",160,246,0,0,120,1,0,2,3,"fixed","Yes" +"189",54,1,"nontypical",192,283,0,2,195,0,0,1,1,"reversable","Yes" +"190",69,1,"nonanginal",140,254,0,2,146,0,2,2,3,"reversable","Yes" +"191",50,1,"nonanginal",129,196,0,0,163,0,0,1,0,"normal","No" +"192",51,1,"asymptomatic",140,298,0,0,122,1,4.2,2,3,"reversable","Yes" +"193",43,1,"asymptomatic",132,247,1,2,143,1,0.1,2,NA,"reversable","Yes" +"194",62,0,"asymptomatic",138,294,1,0,106,0,1.9,2,3,"normal","Yes" +"195",68,0,"nonanginal",120,211,0,2,115,0,1.5,2,0,"normal","No" +"196",67,1,"asymptomatic",100,299,0,2,125,1,0.9,2,2,"normal","Yes" +"197",69,1,"typical",160,234,1,2,131,0,0.1,2,1,"normal","No" +"198",45,0,"asymptomatic",138,236,0,2,152,1,0.2,2,0,"normal","No" +"199",50,0,"nontypical",120,244,0,0,162,0,1.1,1,0,"normal","No" +"200",59,1,"typical",160,273,0,2,125,0,0,1,0,"normal","Yes" +"201",50,0,"asymptomatic",110,254,0,2,159,0,0,1,0,"normal","No" +"202",64,0,"asymptomatic",180,325,0,0,154,1,0,1,0,"normal","No" +"203",57,1,"nonanginal",150,126,1,0,173,0,0.2,1,1,"reversable","No" +"204",64,0,"nonanginal",140,313,0,0,133,0,0.2,1,0,"reversable","No" +"205",43,1,"asymptomatic",110,211,0,0,161,0,0,1,0,"reversable","No" +"206",45,1,"asymptomatic",142,309,0,2,147,1,0,2,3,"reversable","Yes" +"207",58,1,"asymptomatic",128,259,0,2,130,1,3,2,2,"reversable","Yes" +"208",50,1,"asymptomatic",144,200,0,2,126,1,0.9,2,0,"reversable","Yes" +"209",55,1,"nontypical",130,262,0,0,155,0,0,1,0,"normal","No" +"210",62,0,"asymptomatic",150,244,0,0,154,1,1.4,2,0,"normal","Yes" +"211",37,0,"nonanginal",120,215,0,0,170,0,0,1,0,"normal","No" +"212",38,1,"typical",120,231,0,0,182,1,3.8,2,0,"reversable","Yes" +"213",41,1,"nonanginal",130,214,0,2,168,0,2,2,0,"normal","No" +"214",66,0,"asymptomatic",178,228,1,0,165,1,1,2,2,"reversable","Yes" +"215",52,1,"asymptomatic",112,230,0,0,160,0,0,1,1,"normal","Yes" +"216",56,1,"typical",120,193,0,2,162,0,1.9,2,0,"reversable","No" +"217",46,0,"nontypical",105,204,0,0,172,0,0,1,0,"normal","No" +"218",46,0,"asymptomatic",138,243,0,2,152,1,0,2,0,"normal","No" +"219",64,0,"asymptomatic",130,303,0,0,122,0,2,2,2,"normal","No" +"220",59,1,"asymptomatic",138,271,0,2,182,0,0,1,0,"normal","No" +"221",41,0,"nonanginal",112,268,0,2,172,1,0,1,0,"normal","No" +"222",54,0,"nonanginal",108,267,0,2,167,0,0,1,0,"normal","No" +"223",39,0,"nonanginal",94,199,0,0,179,0,0,1,0,"normal","No" +"224",53,1,"asymptomatic",123,282,0,0,95,1,2,2,2,"reversable","Yes" +"225",63,0,"asymptomatic",108,269,0,0,169,1,1.8,2,2,"normal","Yes" +"226",34,0,"nontypical",118,210,0,0,192,0,0.7,1,0,"normal","No" +"227",47,1,"asymptomatic",112,204,0,0,143,0,0.1,1,0,"normal","No" +"228",67,0,"nonanginal",152,277,0,0,172,0,0,1,1,"normal","No" +"229",54,1,"asymptomatic",110,206,0,2,108,1,0,2,1,"normal","Yes" +"230",66,1,"asymptomatic",112,212,0,2,132,1,0.1,1,1,"normal","Yes" +"231",52,0,"nonanginal",136,196,0,2,169,0,0.1,2,0,"normal","No" +"232",55,0,"asymptomatic",180,327,0,1,117,1,3.4,2,0,"normal","Yes" +"233",49,1,"nonanginal",118,149,0,2,126,0,0.8,1,3,"normal","Yes" +"234",74,0,"nontypical",120,269,0,2,121,1,0.2,1,1,"normal","No" +"235",54,0,"nonanginal",160,201,0,0,163,0,0,1,1,"normal","No" +"236",54,1,"asymptomatic",122,286,0,2,116,1,3.2,2,2,"normal","Yes" +"237",56,1,"asymptomatic",130,283,1,2,103,1,1.6,3,0,"reversable","Yes" +"238",46,1,"asymptomatic",120,249,0,2,144,0,0.8,1,0,"reversable","Yes" +"239",49,0,"nontypical",134,271,0,0,162,0,0,2,0,"normal","No" +"240",42,1,"nontypical",120,295,0,0,162,0,0,1,0,"normal","No" +"241",41,1,"nontypical",110,235,0,0,153,0,0,1,0,"normal","No" +"242",41,0,"nontypical",126,306,0,0,163,0,0,1,0,"normal","No" +"243",49,0,"asymptomatic",130,269,0,0,163,0,0,1,0,"normal","No" +"244",61,1,"typical",134,234,0,0,145,0,2.6,2,2,"normal","Yes" +"245",60,0,"nonanginal",120,178,1,0,96,0,0,1,0,"normal","No" +"246",67,1,"asymptomatic",120,237,0,0,71,0,1,2,0,"normal","Yes" +"247",58,1,"asymptomatic",100,234,0,0,156,0,0.1,1,1,"reversable","Yes" +"248",47,1,"asymptomatic",110,275,0,2,118,1,1,2,1,"normal","Yes" +"249",52,1,"asymptomatic",125,212,0,0,168,0,1,1,2,"reversable","Yes" +"250",62,1,"nontypical",128,208,1,2,140,0,0,1,0,"normal","No" +"251",57,1,"asymptomatic",110,201,0,0,126,1,1.5,2,0,"fixed","No" +"252",58,1,"asymptomatic",146,218,0,0,105,0,2,2,1,"reversable","Yes" +"253",64,1,"asymptomatic",128,263,0,0,105,1,0.2,2,1,"reversable","No" +"254",51,0,"nonanginal",120,295,0,2,157,0,0.6,1,0,"normal","No" +"255",43,1,"asymptomatic",115,303,0,0,181,0,1.2,2,0,"normal","No" +"256",42,0,"nonanginal",120,209,0,0,173,0,0,2,0,"normal","No" +"257",67,0,"asymptomatic",106,223,0,0,142,0,0.3,1,2,"normal","No" +"258",76,0,"nonanginal",140,197,0,1,116,0,1.1,2,0,"normal","No" +"259",70,1,"nontypical",156,245,0,2,143,0,0,1,0,"normal","No" +"260",57,1,"nontypical",124,261,0,0,141,0,0.3,1,0,"reversable","Yes" +"261",44,0,"nonanginal",118,242,0,0,149,0,0.3,2,1,"normal","No" +"262",58,0,"nontypical",136,319,1,2,152,0,0,1,2,"normal","Yes" +"263",60,0,"typical",150,240,0,0,171,0,0.9,1,0,"normal","No" +"264",44,1,"nonanginal",120,226,0,0,169,0,0,1,0,"normal","No" +"265",61,1,"asymptomatic",138,166,0,2,125,1,3.6,2,1,"normal","Yes" +"266",42,1,"asymptomatic",136,315,0,0,125,1,1.8,2,0,"fixed","Yes" +"267",52,1,"asymptomatic",128,204,1,0,156,1,1,2,0,NA,"Yes" +"268",59,1,"nonanginal",126,218,1,0,134,0,2.2,2,1,"fixed","Yes" +"269",40,1,"asymptomatic",152,223,0,0,181,0,0,1,0,"reversable","Yes" +"270",42,1,"nonanginal",130,180,0,0,150,0,0,1,0,"normal","No" +"271",61,1,"asymptomatic",140,207,0,2,138,1,1.9,1,1,"reversable","Yes" +"272",66,1,"asymptomatic",160,228,0,2,138,0,2.3,1,0,"fixed","No" +"273",46,1,"asymptomatic",140,311,0,0,120,1,1.8,2,2,"reversable","Yes" +"274",71,0,"asymptomatic",112,149,0,0,125,0,1.6,2,0,"normal","No" +"275",59,1,"typical",134,204,0,0,162,0,0.8,1,2,"normal","Yes" +"276",64,1,"typical",170,227,0,2,155,0,0.6,2,0,"reversable","No" +"277",66,0,"nonanginal",146,278,0,2,152,0,0,2,1,"normal","No" +"278",39,0,"nonanginal",138,220,0,0,152,0,0,2,0,"normal","No" +"279",57,1,"nontypical",154,232,0,2,164,0,0,1,1,"normal","Yes" +"280",58,0,"asymptomatic",130,197,0,0,131,0,0.6,2,0,"normal","No" +"281",57,1,"asymptomatic",110,335,0,0,143,1,3,2,1,"reversable","Yes" +"282",47,1,"nonanginal",130,253,0,0,179,0,0,1,0,"normal","No" +"283",55,0,"asymptomatic",128,205,0,1,130,1,2,2,1,"reversable","Yes" +"284",35,1,"nontypical",122,192,0,0,174,0,0,1,0,"normal","No" +"285",61,1,"asymptomatic",148,203,0,0,161,0,0,1,1,"reversable","Yes" +"286",58,1,"asymptomatic",114,318,0,1,140,0,4.4,3,3,"fixed","Yes" +"287",58,0,"asymptomatic",170,225,1,2,146,1,2.8,2,2,"fixed","Yes" +"288",58,1,"nontypical",125,220,0,0,144,0,0.4,2,NA,"reversable","No" +"289",56,1,"nontypical",130,221,0,2,163,0,0,1,0,"reversable","No" +"290",56,1,"nontypical",120,240,0,0,169,0,0,3,0,"normal","No" +"291",67,1,"nonanginal",152,212,0,2,150,0,0.8,2,0,"reversable","Yes" +"292",55,0,"nontypical",132,342,0,0,166,0,1.2,1,0,"normal","No" +"293",44,1,"asymptomatic",120,169,0,0,144,1,2.8,3,0,"fixed","Yes" +"294",63,1,"asymptomatic",140,187,0,2,144,1,4,1,2,"reversable","Yes" +"295",63,0,"asymptomatic",124,197,0,0,136,1,0,2,0,"normal","Yes" +"296",41,1,"nontypical",120,157,0,0,182,0,0,1,0,"normal","No" +"297",59,1,"asymptomatic",164,176,1,2,90,0,1,2,2,"fixed","Yes" +"298",57,0,"asymptomatic",140,241,0,0,123,1,0.2,2,0,"reversable","Yes" +"299",45,1,"typical",110,264,0,0,132,0,1.2,2,0,"reversable","Yes" +"300",68,1,"asymptomatic",144,193,1,0,141,0,3.4,2,2,"reversable","Yes" +"301",57,1,"asymptomatic",130,131,0,0,115,1,1.2,2,1,"reversable","Yes" +"302",57,0,"nontypical",130,236,0,2,174,0,0,2,1,"normal","Yes" +"303",38,1,"nonanginal",138,175,0,0,173,0,0,1,NA,"normal","No" diff --git a/datasets/Income1.csv b/datasets/Income1.csv new file mode 100644 index 0000000..4d46336 --- /dev/null +++ b/datasets/Income1.csv @@ -0,0 +1,31 @@ +"","Education","Income" +"1",10,26.6588387834389 +"2",10.4013377926421,27.3064353457772 +"3",10.8428093645485,22.1324101716143 +"4",11.2441471571906,21.1698405046065 +"5",11.6454849498328,15.1926335164307 +"6",12.0869565217391,26.3989510407284 +"7",12.4882943143813,17.435306578572 +"8",12.8896321070234,25.5078852305278 +"9",13.2909698996656,36.884594694235 +"10",13.7324414715719,39.666108747637 +"11",14.133779264214,34.3962805641312 +"12",14.5351170568562,41.4979935356871 +"13",14.9765886287625,44.9815748660704 +"14",15.3779264214047,47.039595257834 +"15",15.7792642140468,48.2525782901863 +"16",16.2207357859532,57.0342513373801 +"17",16.6220735785953,51.4909192102538 +"18",17.0234113712375,61.3366205527288 +"19",17.4648829431438,57.581988179306 +"20",17.866220735786,68.5537140185881 +"21",18.2675585284281,64.310925303692 +"22",18.7090301003344,68.9590086393083 +"23",19.1103678929766,74.6146392793647 +"24",19.5117056856187,71.8671953042483 +"25",19.9130434782609,76.098135379724 +"26",20.3545150501672,75.77521802986 +"27",20.7558528428094,72.4860553152424 +"28",21.1571906354515,77.3550205741877 +"29",21.5986622073579,72.1187904524136 +"30",22,80.2605705009016 diff --git a/datasets/Income2.csv b/datasets/Income2.csv new file mode 100644 index 0000000..d3ce0d8 --- /dev/null +++ b/datasets/Income2.csv @@ -0,0 +1,31 @@ +"","Education","Seniority","Income" +"1",21.5862068965517,113.103448275862,99.9171726114381 +"2",18.2758620689655,119.310344827586,92.579134855529 +"3",12.0689655172414,100.689655172414,34.6787271520874 +"4",17.0344827586207,187.586206896552,78.7028062353695 +"5",19.9310344827586,20,68.0099216471551 +"6",18.2758620689655,26.2068965517241,71.5044853814318 +"7",19.9310344827586,150.344827586207,87.9704669939115 +"8",21.1724137931034,82.0689655172414,79.8110298331255 +"9",20.3448275862069,88.2758620689655,90.00632710858 +"10",10,113.103448275862,45.6555294997364 +"11",13.7241379310345,51.0344827586207,31.9138079371295 +"12",18.6896551724138,144.137931034483,96.2829968022869 +"13",11.6551724137931,20,27.9825049000603 +"14",16.6206896551724,94.4827586206897,66.601792415137 +"15",10,187.586206896552,41.5319924201478 +"16",20.3448275862069,94.4827586206897,89.00070081522 +"17",14.1379310344828,20,28.8163007592387 +"18",16.6206896551724,44.8275862068966,57.6816942573605 +"19",16.6206896551724,175.172413793103,70.1050960424457 +"20",20.3448275862069,187.586206896552,98.8340115435447 +"21",18.2758620689655,100.689655172414,74.7046991976891 +"22",14.551724137931,137.931034482759,53.5321056283034 +"23",17.448275862069,94.4827586206897,72.0789236655191 +"24",10.4137931034483,32.4137931034483,18.5706650327685 +"25",21.5862068965517,20,78.8057842852386 +"26",11.2413793103448,44.8275862068966,21.388561306174 +"27",19.9310344827586,168.965517241379,90.8140351180409 +"28",11.6551724137931,57.2413793103448,22.6361626208955 +"29",12.0689655172414,32.4137931034483,17.613593041445 +"30",17.0344827586207,106.896551724138,74.6109601985289 diff --git a/islr-ch3.md b/islr-ch3.md new file mode 100644 index 0000000..4414fbd --- /dev/null +++ b/islr-ch3.md @@ -0,0 +1,139 @@ +# Linear regression + +Though it may seem somewhat dull compared to some of the more modern statistical learning approaches described in later chapters of this book, linear regression is still a useful and widely used statistical learning method. Moreover, it serves as a good jumping-off point for newer approaches: as we will see in later chapters, many fancy statistical learning approaches can be seen as generalizations or extensions of linear regression. Consequently, the importance of having a good understanding of linear regression before studying more complex learning methods cannot be overstated. + +## 3.1 Simple linear regression +is a very straightforward simple linear approach for predicting a quantitative response Y on the basis of a single predictor variable X. It assumes that there is approximately a linear relationship between X and Y +$$ +Y \approx \beta_0 + \beta_1 X +$$ +Which we can read as Y is approximately modeled as, or we are regressing Y onto x. +In this case with just 2 parameters, beta0 is the intercept and beta1 is the slope. + +### 3.1.1 Estimating coefficients +We can create observation pairs $(x_i, y_i)$, and then obtain coefficient estimates such that f(xi) approximates yi. There are different ways to measure *closeness*; The prevailing method is the least squares method. + +Let ŷi = β̂0 + β̂1 xi be the prediction for Y based on the ith value of X. +Then ei = yi − ŷ i represents the ith residual—this is the difference between the ith observed response value and the ith response value that is predicted by our linear model. We define the residual sum of squares (RSS) as follows: +$$ +RSS = e_1^2 + e_2^2 + \ldots + e_n^2 +$$ +Using some calculus, we can show that + +$$ +\hat{\beta}_1 = {\sum (x_i = \bar{x})(y_i - \bar{y})\over \sum (x_i - \bar{x})^2} \\ +\hat{\beta}_0 = \bar{y} - \beta_1 \bar{x} +$$ + +### 3.1.2 Assessing the acuracy +Recall that expected Y was f + irreducable error. This means that for our simple linear regression, +$\hat{Y} = \beta_0 + \beta_1 X + \epsilon$ + +The error term is a catch-all for what we miss with this simple model: the true relationship is probably not linear, there may be other variables that cause variation in Y , and there may be measurement error. We typically assume that the error term is independent of X. +The model defines the population regression line(the real model without error), which is the best linear approximation to the true relationship between X and Y. +in real applications, we have access to a set of observations from which we can compute the least squares line; however, the population regression line is unobserved. +Typically, the training data is sampled multiple times so we can compute multiple least square lines. This allows us to decrease bias, because each line will be higher or lower, meaning no systematic bias. Kinda like population mean and sample mean. +To go futher with our mean analogy, how do we compute how far the sample mean is from the actual mean? We do this with standard error + +$$SE(\hat{\mu})^2 = {\sigma^2 \over n}$$ + +similarly, +![](./ISLR/pics/ch3-1.png) +$\sigma^2$ is generally not known, but we can use an estimate called **residual standard error** which is calculated as follows: +$$RSE = \sqrt{RSS/(n-2)}$$ + +Standard errors can be used to compute **confidence intervals**. +For linear regression, the 95 % confidence interval for β1 +approximately takes the form +![](./ISLR/pics/ch3-2.png) +the factor of 2 in front of the SE(β̂1 ) term will vary slightly depending on the number of observations n in the linear regression. To be precise, rather than the number 2, it should contain the 97.5 % quantile of a t-distribution with n−2 degrees of freedom. +We can also use this for hypothesis testing. To test the null hypothesis, we need to determine whether β̂1 , our estimate for β1 , is sufficiently far from zero that we can be confident that β1 is non-zero. How far depends on SE(β̂1). small SE allows for small numbers, and in contrast, if SE is large, we need a large b1 to tell us that b1 = 0. +We're actually computing the t statistic, +$$ +t = {\hat{\beta_1} - 0\over SE(\beta_1)}$$ +which measures the number of standard deviations that β̂1 is away from 0. We can also compute the p-value. + +### 3.1.3 Assessing the accuracy of our model +Once we've rejected the null hypotheses, we would likely want to know to what extend our model fits the data. The quality of a linear regression fit is typically assessed using two related quantities: the residual standard error (RSE) and the $R^2$ Rstatistic. + +### RSE +Recall that because of the irreducable error, we won't be able to perfectly predict Y anyway. RSE is an estimate of the std of $\epsilon$. Roughly speaking, it is the average amount that the response +will deviate from the true regression line. It is computed using the formula +![](ISLR/pics/ch3-3.png) +In table 3.2, we have an RSE of 3.26. Another way to think about this is that even if the model were correct and the true values of the unknown coefficients β0 and β1 were known exactly, any prediction of sales on the basis of TV +advertising would still be off by about 3.260 units on average. +It depends on the context wether this is acceptable. In the advertising data set, the mean value of sales over all markets is approximately 1 units, and so the percentage error is +3.260/14 = 23 %. +The RSE is considered a measure of the lack of fit of the model to the data. As it increases, we know that predicted response will be further of from true response. + +### R^2 statistic +The RSE provides an absolute measure of lack of fit of the model to the data. But since it is measured in the units of Y , it is not always clear what constitutes a good RSE. The $R^2$ statistic provides an alternative measure of fit. It takes the form of a proportion—the proportion of variance explained—and so it always takes on a value between 0 and 1, and is independent of the scale of Y . + +![](ISLR/pics/ch3-4.png) + +TTS is the total variance in Y. TSS - RSS is the ammount of variability that can be explained with the regression. $R^2$ is the proportion of the variability of Y that can be explained with X. Higher is better. If it's low, regression did not explain much of the variability, and may be due the fact that the real world problem isnt linear at all or that the inherent error $\sigma^2$ is high. +The pro is that it's way more interpretable than RSE. How close to 1 is acceptable depends on the context. In physics, a number that's not extremely close to 1 might indicate a serious problem with the experiment, but in biology, sociology, etc, a value of 0.1 might be realistic. Also, correlation(r) is another good measure. In simple linear regression, $R^2 = r^2$ +Note that this is only for simple lin. regression. For multiple linear regression, we need $R^2$ + +## 3.2 Multiple regression +How can we extend our simple linear regression model to radio, tv and newspaper advertisments? +We could simply make 3 simple lin. regression models, but this would be kinda wrong. Not only are we then ignoring the effects of the other 2 predictors for each model, we also remove the way to predict sales when multiple predictors are tweaked. +The better thing to do is to extend our model to include multiple predictors, like so: + +$$ +Y = \beta_0 + \beta_1 X_1 + \ldots + \beta_p X_p +$$ + +Any Xj then represents the jth predictor, and $\beta_j$ the average effect of Xj on the response. + +### 3.2.1 Estimating the regression coefficients + +We use the same least squares method for this. that is: +$$ +RSS = \sum (y_i - \hat{y}_i)^2 = \sum (y_i - \beta_0 - \beta_1 X_1 - \ldots - \beta_p X_p)^2 +$$ +The formulla used to calculate the coefficients is out of the scope of this book. + +### 3.2.2 Some important Questions +#### Is There a Relationship Between the Response and Predictors? + +To answer this, we test the null hypothesis: +H0 : every $X_i$ is zero. +We do this with the **F-statistic** + +![](ISLR/pics/ch3-5.png) +![](ISLR/pics/ch3-6.png) +Hence, when there is no relationship between the response and predictors, +one would expect the F-statistic to take on a value close to 1, and a lot greater than 1 otherwise. + +The larger the number of datapoints n, the smaller F has to be to reject the null hypothesis. Every good software package provides a way to calculate the **p-value** associated with the F-statistic using this distribution. Based on this p-value, we can determine whether or not to reject H0 . + +Sometimes we only want to see wether a subset q of the coefficients is zero. We just create a model with only those subset of predictors, and do the same analysis as above, but this time, +![](ISLR/pics/ch3-7.png) + +**if p > n, we can't fit the linear regression model with least squares, so we don't use the F statistic, or most concepts discussed in this chapter. When p is large, some of the approaches discussed in the next section, such as *forward selection*, can be used. This *high-dimensional* setting will be discussed later.** + +### Do all the predictors help to explain Y , or is only a subset of the predictors useful? + +*Variable selection*, the practice of determining which predictors are associated with the response, in order to fit a single model involving only those predictors is extensively discussed in Ch6, but we'll go a bit in it here. + +![](ISLR/pics/ch3-8.png) +Unfortunately, we need to fit and test $2^p$ models, which might be very impractical, so we need an automated and efficient approach. +There are 3 classical approaches available: +* Forward selection. We start with a model with no predictors. We then test simple regression models for all p, selecting the one with the lowest RSS. We then test all models with 2 variables containing the previous one, again selecting the one with the lowest RSS. We keep this up untill some stopping rule says we stop (e.g. we only want 5 vars). +* Backward selection. We start with a model with all predictors, removing the predictor with the largest p-value(The one that's the least statistically significant) and refitting the model. We continue this untill some stopping condition is satisifed, such as when all predictors are below some p-value treshold. +* Mixed selection. Combination of the 2 mentioned already. We start with forward selection, adding statistically relevant variables. The p-values can change when new predictors are added, so we remove the variable when it's above some treshold. We continue to perform these forward and backward steps until all variables in the model have a sufficiently low p-value, and all variables outside the model would have a large p-value if added to the model. + +**Backward selection cannot be used if p > n, while forward selection can always be used. Forward selection is a greedy approach, and might include variables early that later become redundant. Mixed selection can remedy this.** + +### How well does the model fit the data? + + + +### Given a set of predictor values, what response value should we predict, and how accurate is our prediction? + + + + + + diff --git a/quickR/atest.R b/quickR/atest.R new file mode 100644 index 0000000..ae655d1 --- /dev/null +++ b/quickR/atest.R @@ -0,0 +1,5 @@ +library(ISLR) + +pairs(College[,1:10]) + +