671 lines
1.9 MiB
Plaintext
671 lines
1.9 MiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"from pandas import DataFrame, Series\n",
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"from numpy import nan\n",
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"import pathlib\n",
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"import matplotlib.pyplot as plt\n",
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"plt.rcParams[\"figure.figsize\"] = (30,5)\n",
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"import seaborn as sns\n",
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"sns.set()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>TEST</th>\n",
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" <th>MAP</th>\n",
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" <th>50000</th>\n",
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" <th>100000</th>\n",
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" <th>150000</th>\n",
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" <th>200000</th>\n",
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" <th>250000</th>\n",
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" <th>300000</th>\n",
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" <th>350000</th>\n",
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" <th>400000</th>\n",
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" <th>...</th>\n",
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" <th>9000000</th>\n",
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" <th>10000000</th>\n",
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" <th>15000000</th>\n",
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" <th>20000000</th>\n",
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" <th>25000000</th>\n",
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" <th>30000000</th>\n",
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" <th>35000000</th>\n",
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" <th>40000000</th>\n",
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" <th>45000000</th>\n",
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" <th>50000000</th>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>Unnamed: 0</th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>int_delete</td>\n",
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" <td>absl::flat_hash_map</td>\n",
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" <td>9</td>\n",
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" <td>14</td>\n",
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" <td>11</td>\n",
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" <td>14</td>\n",
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" <td>11</td>\n",
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" <td>12</td>\n",
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" <td>13</td>\n",
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" <td>15</td>\n",
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" <td>...</td>\n",
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" <td>21</td>\n",
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" <td>21</td>\n",
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" <td>24</td>\n",
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" <td>28</td>\n",
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" <td>25</td>\n",
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" <td>25</td>\n",
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" <td>26</td>\n",
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" <td>25</td>\n",
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" <td>26</td>\n",
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" <td>26</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>int_delete</td>\n",
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" <td>absl::flat_hash_map</td>\n",
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" <td>9</td>\n",
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" <td>14</td>\n",
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" <td>11</td>\n",
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" <td>14</td>\n",
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" <td>11</td>\n",
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" <td>12</td>\n",
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" <td>13</td>\n",
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" <td>16</td>\n",
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" <td>...</td>\n",
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" <td>20</td>\n",
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" <td>23</td>\n",
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" <td>24</td>\n",
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" <td>23</td>\n",
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" <td>27</td>\n",
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" <td>26</td>\n",
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" <td>26</td>\n",
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" <td>26</td>\n",
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" <td>26</td>\n",
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" <td>26</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>int_delete</td>\n",
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" <td>absl::flat_hash_map</td>\n",
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" <td>9</td>\n",
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" <td>14</td>\n",
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" <td>11</td>\n",
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" <td>14</td>\n",
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" <td>11</td>\n",
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" <td>12</td>\n",
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" <td>13</td>\n",
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" <td>15</td>\n",
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" <td>...</td>\n",
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" <td>20</td>\n",
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" <td>21</td>\n",
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" <td>24</td>\n",
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" <td>24</td>\n",
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" <td>25</td>\n",
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" <td>26</td>\n",
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" <td>26</td>\n",
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" <td>30</td>\n",
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" <td>26</td>\n",
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" <td>27</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>int_delete</td>\n",
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" <td>absl::flat_hash_map</td>\n",
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" <td>9</td>\n",
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" <td>14</td>\n",
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" <td>11</td>\n",
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" <td>14</td>\n",
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" <td>11</td>\n",
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" <td>12</td>\n",
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" <td>13</td>\n",
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" <td>15</td>\n",
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" <td>...</td>\n",
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" <td>21</td>\n",
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" <td>21</td>\n",
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" <td>24</td>\n",
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" <td>24</td>\n",
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" <td>25</td>\n",
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" <td>25</td>\n",
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" <td>26</td>\n",
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" <td>29</td>\n",
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" <td>26</td>\n",
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" <td>26</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>int_delete</td>\n",
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" <td>absl::flat_hash_map</td>\n",
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" <td>9</td>\n",
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" <td>14</td>\n",
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" <td>11</td>\n",
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" <td>14</td>\n",
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" <td>11</td>\n",
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" <td>12</td>\n",
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" <td>13</td>\n",
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" <td>15</td>\n",
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" <td>...</td>\n",
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" <td>20</td>\n",
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" <td>20</td>\n",
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" <td>24</td>\n",
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" <td>24</td>\n",
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" <td>25</td>\n",
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" <td>26</td>\n",
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" <td>26</td>\n",
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" <td>26</td>\n",
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" <td>26</td>\n",
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" <td>27</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"<p>5 rows × 33 columns</p>\n",
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"</div>"
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],
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"text/plain": [
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" TEST MAP 50000 100000 150000 200000 \\\n",
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"Unnamed: 0 \n",
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"0 int_delete absl::flat_hash_map 9 14 11 14 \n",
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"1 int_delete absl::flat_hash_map 9 14 11 14 \n",
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"2 int_delete absl::flat_hash_map 9 14 11 14 \n",
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"3 int_delete absl::flat_hash_map 9 14 11 14 \n",
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"4 int_delete absl::flat_hash_map 9 14 11 14 \n",
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"\n",
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" 250000 300000 350000 400000 ... 9000000 10000000 15000000 \\\n",
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"Unnamed: 0 ... \n",
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"0 11 12 13 15 ... 21 21 24 \n",
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"1 11 12 13 16 ... 20 23 24 \n",
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"2 11 12 13 15 ... 20 21 24 \n",
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"3 11 12 13 15 ... 21 21 24 \n",
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"4 11 12 13 15 ... 20 20 24 \n",
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"\n",
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" 20000000 25000000 30000000 35000000 40000000 45000000 \\\n",
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"Unnamed: 0 \n",
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"0 28 25 25 26 25 26 \n",
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"1 23 27 26 26 26 26 \n",
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"2 24 25 26 26 30 26 \n",
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"3 24 25 25 26 29 26 \n",
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"4 24 25 26 26 26 26 \n",
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"\n",
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" 50000000 \n",
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"Unnamed: 0 \n",
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"0 26 \n",
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"1 26 \n",
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"2 27 \n",
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"3 26 \n",
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"4 27 \n",
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"\n",
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"[5 rows x 33 columns]"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"cols = [\n",
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"\"TEST\",\"MAP\",\n",
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"50000, 100000, 150000, 200000, 250000, 300000, 350000, 400000, 500000,\n",
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"600000, 700000, 800000, 900000, 1000000,\n",
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"2000000, 3000000, 4000000, 5000000, 6000000, 7000000, 8000000, 9000000, 10000000,\n",
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"15000000, 20000000, 25000000, 30000000, 35000000, 40000000, 45000000, 50000000\n",
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"]\n",
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"if not pathlib.Path(\"./sorted.csv\").is_file():\n",
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" data = pd.read_csv(\"results.csv\", quotechar=\"'\", header=None)\n",
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" data.columns= cols\n",
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" data = data.sort_values(by=['TEST', 'MAP'], ignore_index=True)\n",
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" data.to_csv(\"sorted.csv\")\n",
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"\n",
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"else:\n",
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" data = pd.read_csv(\"sorted.csv\")\n",
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" data.set_index(\"Unnamed: 0\", inplace=True)\n",
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"data.head()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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"def remove_with_iqr(data):\n",
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" stats = data.describe()\n",
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" IQR = stats[\"75%\"] - stats[\"25%\"]\n",
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" min_cutoff = stats[\"25%\"] - 1.5 * IQR\n",
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" max_cutoff = stats[\"75%\"] + 1.5 * IQR\n",
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" lower_max = data <= max_cutoff\n",
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" higher_min = data >= min_cutoff\n",
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" data = data * lower_max * higher_min\n",
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" data = data.replace(0, nan)\n",
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" return data\n",
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" \n",
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"def remove_with_zscore(data, cutoff=3.5):\n",
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" stats = data.describe()\n",
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" if not stats[\"std\"]:\n",
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" return data\n",
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|
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" z = abs((data - stats[\"mean\"]) / stats[\"std\"])\n",
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" cut = z <= cutoff\n",
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" data = data * cut\n",
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" data = data.replace(0, nan)\n",
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" return data \n",
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"\n",
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"def remove_with_modified_z_score(data, treshold=3.5):\n",
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" stats = data.describe()\n",
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" median_absolute_deviation = abs(data - data.median()).median()\n",
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" if not median_absolute_deviation:\n",
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" return data\n",
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" modified_z_scores = abs(0.6745 * (data - data.median()) / median_absolute_deviation)\n",
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" cutoff = modified_z_scores <= treshold\n",
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" data = data * cutoff\n",
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" data = data.replace(0, nan)\n",
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" return data\n",
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"\n",
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"def max_val(hmap, test):\n",
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" return groups_mean.loc[test, hmap].max()\n",
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"\n",
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"def sort_maps(test):\n",
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" maps = list(groups_mean.loc[test].index)\n",
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" new = [(max_val(i, test), i) for i in maps]\n",
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" new.sort()\n",
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" new = [i[1] for i in new]\n",
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" return new\n",
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"\n",
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"def plot_test(test, include_error=True):\n",
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|
|
" sizes = [50000, 100000, 150000, 200000, 250000, 300000, 350000, 400000, 500000,\n",
|
|||
|
|
" 600000, 700000, 800000, 900000, 1000000,\n",
|
|||
|
|
" 2000000, 3000000, 4000000, 5000000, 6000000, 7000000, 8000000, 9000000, 10000000,\n",
|
|||
|
|
" 15000000, 20000000, 25000000, 30000000, 35000000, 40000000, 45000000, 50000000]\n",
|
|||
|
|
" maps = sort_maps(test)\n",
|
|||
|
|
" count = 16\n",
|
|||
|
|
" repeats = [0, 5, 11]\n",
|
|||
|
|
" while count > -1:\n",
|
|||
|
|
" if not count and count not in repeats:\n",
|
|||
|
|
" break\n",
|
|||
|
|
" mp = maps[count]\n",
|
|||
|
|
" if include_error:\n",
|
|||
|
|
" plt.errorbar(sizes,groups_mean.loc[test, mp], yerr=groups_std.loc[test, mp], label=mp)\n",
|
|||
|
|
" else:\n",
|
|||
|
|
" sns.lineplot(x=sizes, y=groups_mean.loc[test, mp], label=mp)\n",
|
|||
|
|
" if count in repeats:\n",
|
|||
|
|
" plt.xscale(\"log\")\n",
|
|||
|
|
" plt.ylabel(\"{} time (ns)\".format(test))\n",
|
|||
|
|
" plt.legend()\n",
|
|||
|
|
" plt.title(test)\n",
|
|||
|
|
" plt.show()\n",
|
|||
|
|
" repeats.pop(repeats.index(count))\n",
|
|||
|
|
" else:\n",
|
|||
|
|
" count -=1"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 9,
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"iqr_data = data.copy(True)\n",
|
|||
|
|
"# modz_data = data.copy(True)\n",
|
|||
|
|
"# z_data = data.copy(True)"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 10,
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": [
|
|||
|
|
"for col in range(2,33):\n",
|
|||
|
|
" for row in range(8 * 17):\n",
|
|||
|
|
" start = row * 30\n",
|
|||
|
|
" end = (row + 1 ) * 30\n",
|
|||
|
|
" temp = data.iloc[start : end,col]\n",
|
|||
|
|
" iqr_data.iloc[start : end,col] = remove_with_iqr(temp)\n",
|
|||
|
|
"# modz_data.iloc[start : end,col] = remove_with_modified_z_score(temp)\n",
|
|||
|
|
"# z_data.iloc[start : end,col] = remove_with_zscore(temp)"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 11,
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "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
|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 2160x360 with 1 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "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
|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 2160x360 with 1 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "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
|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 2160x360 with 1 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"tester = iqr_data # use removed outliers data\n",
|
|||
|
|
"groups_modz = tester.groupby([\"TEST\", \"MAP\"])\n",
|
|||
|
|
"groups_mean = groups_modz.mean()\n",
|
|||
|
|
"groups_std = groups_modz.std()\n",
|
|||
|
|
"groups_std.columns = [int(i) for i in groups_std.columns]\n",
|
|||
|
|
"groups_mean.columns = groups_std.columns\n",
|
|||
|
|
"plot_test(\"int_insert\")"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 12,
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "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
|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 2160x360 with 1 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "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
|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 2160x360 with 1 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "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
|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 2160x360 with 1 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"tester = data # use original data\n",
|
|||
|
|
"groups_modz = tester.groupby([\"TEST\", \"MAP\"])\n",
|
|||
|
|
"groups_mean = groups_modz.mean()\n",
|
|||
|
|
"groups_std = groups_modz.std()\n",
|
|||
|
|
"groups_std.columns = [int(i) for i in groups_std.columns]\n",
|
|||
|
|
"groups_mean.columns = groups_std.columns\n",
|
|||
|
|
"plot_test(\"int_insert\")"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 15,
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
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|
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"text/plain": [
|
|||
|
|
"<Figure size 2160x360 with 1 Axes>"
|
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|
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]
|
|||
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|
},
|
|||
|
|
"metadata": {},
|
|||
|
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"output_type": "display_data"
|
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},
|
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{
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"data": {
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"image/png": "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
|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 2160x360 with 1 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
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"data": {
|
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|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAABsIAAAFGCAYAAADQAooIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+j8jraAAAgAElEQVR4nOzdd3hUZfr/8feZmWTSSIAkEEIJhCogNRQxAcUOgiyyqKjoItWNqLuAUhQQASm6iqyKVEVYlx/6RURAxMYCUhNEkWaAUEJCaOnJZGbO749A6D2N8Hldl1dmzjznfu5zkjC7c+d+HsM0TRMRERERERERERERERGRUsZS3AmIiIiIiIiIiIiIiIiIFAYVwkRERERERERERERERKRUUiFMRERERERERERERERESiUVwkRERERERERERERERKRUUiFMRERERERERERERERESiUVwkRERERERERERERERKRUUiFMRERERERERERERERESiUVwkRERERERIrAb7/9xsCBAy87ZurUqaxcufKKsR555BFSU1MLKrUbzkdERERERKSkUiFMRERERESkCNx+++1MmTLlsmPWr1+P0+m8YqyvvvoKf3//gkrthvMREREREREpqWzFnYCIiIiIiMitYP369YwZM4aGDRvi5+fHzp07SUxMpG7dukyYMIFFixbx+++/M3HiRKxWK/fdd98lY9WtW5dffvmFn376ie+++w6LxUJ8fDxeXl5MmDCBmjVrsmLFCj788EMMw8BqtTJkyBBatGhBWloaY8eOZdeuXeTm5nLHHXcwZMgQbDYbDRs25J577mHHjh106tTpqvMREREREREpqdQRJiIiIiIiUsR+//13Zs6cydKlSzl06BDLly/nySefpGHDhgwZMuSaik4bN27ktddeY8mSJTRu3JiPP/4YgIkTJzJy5Ei+/PJLXnzxRdavXw/AuHHjaNCgAV9++SWLFi3ixIkTzJ49G4Dc3Fzuvvtuvv32W6Kjo68rHxERERERkZJEHWEiIiIiIiJFLCoqCk9PTwDq1KlDSkrKdcdq0KABISEhANSvX5/vvvsOgI4dOxIdHU27du2488476dOnDwA//fQTv/32GwsXLgQgOzv7nHgRERHXnYuIiIiIiEhJo0KYiIiIiIhIEfPy8sp/bBgGpmkWeKyXX36ZRx99lDVr1vDll18ya9YsFi5ciNvt5r333qNmzZoApKamYhhGfgwfH5/rzkVERERERKSk0dKIIiIiIiIiJYTVasXpdN5wHKfTSfv27cnKyuKJJ55g5MiR7Ny5E4fDQWRkJHPmzME0TRwOBwMGDOCzzz4r1HxERERERESKizrCRERERERESoj27dvzzjvvkJuby1/+8pfrjmOz2Rg2bBiDBg3CZrNhGAbjxo3D09OT4cOHM3bsWDp16kRubi5t2rShd+/ehZqPiIiIiIhIcTHMG1mDQ0RERERERERERERERKSEUkeYiIiIiIhICTNjxgy+/vrri7723HPP0blz5yLOSERERERE5OakjjAREREREREREREREREplSzFnYCIiIiIiIiIiIiIiIhIYVAhTEREREREREREREREREqlUrNH2IkTGbjdWuVRpCQIDPTj2LH04k5DRERECone60VEREo/vd+LiMjNwmIxKFfO95Kvl5pCmNttqhAmUoLo91FERKR003u9iIhI6af3exERKQ20NKKIiIiIiIiIiIiIiIiUSiqEiYiIiIiIiIiIiIiISKmkQpiIiIiIiIiIiIiIiIiUSqVmj7CLcbmcnDiRjNPpKO5UREoUm82TcuWCsVpL9T8BIiIiIiIiIiIiInKLK9Wfgp84kYyXlw++viEYhlHc6YiUCKZpkpGRyokTyQQFVSrudERERERERERERERECk2pXhrR6XTg6+uvIpjIWQzDwNfXX52SIiIiIiIiIiIiIlLqlepCGHBdRbAJ82KYMC+mELIRKRlUHBYRERERERERERGRW0GhF8LS09N5+OGHOXjwIAD//e9/efjhh+nUqRNDhw7F4cjrStm+fTtdu3blgQceYPjw4TidzsJOTUREREREREREREREREqxQi2E/frrrzzxxBPs27cPgL179zJz5kw+//xzFi9ejNvtZv78+QAMHjyY119/nW+//RbTNFmwYEFhplYiHD6cQLduna56/MyZ05g5c9plx+zcuYOuXTvy97/3YezYUSxd+vVlx48bN5rExMOXHRMd3ZeYmE1XnefFXOu1ioiIiIiIiIiIiIiI3KhCLYQtWLCAkSNHUqFCBQA8PT0ZOXIkfn5+GIZBnTp1SEhI4NChQ2RnZ9OkSRMAunbtyvLlywsztVJr7dr/8cADHfj3v6df1fiYmE2YplnIWYmIiIiIiIiIiIiIiBQ9W2EGHzt27DnPK1euTOXKlQE4fvw48+bNY/z48Rw5coTg4OD8ccHBwSQlJV3TXIGBfhccO3LEgs2WV+tbvTWBVVsSrirW/iNpAEycf3X7hLVtEkpko9DLjnE6nUycOJ49e/7k+PHj1KpVmwEDonE4HIwcOZT4+H1UrlyF4cNH4u/vz5Qp/2LDhnVYLBbatr2L3r37YbHk7etks1kYO/YNoqLa0bZtOz7++EOCgoIJCQnh//5vIQBeXnYMw8BiMbDZLHz44VQ2bdpAamoqQUHBvPnmW3zzzWKOHk1m8OAXmTZtJgEBZS+au2EYLF26mKlT3yU9PY2XXx5EVFQ74uL+5O23J5KVlcmJE8fp2bMXXbt2Y+PG9Uyd+h6GYVCmjD9jxozDarWQk5PDqFHD2LMnjjJlyjBx4juXnBOgS5eO3H//g2zYsA6r1UqvXn2YP38uBw4cYODAl7n33vsvmcP06R+RmHiYffv2kpJyki5dHuWpp565qu/nrcJisRAcXKbQ4hdmbBERESl+eq8XEREp/fR+LyJSPIZ+sBqA8c9HFnMmpUOhFsIuJSkpid69e/Poo4/SqlUrNm/ejGEY+a+bpnnO86tx7Fg6bve5nU1utxun0w2Ay2VyrY1PVzve5TLz57mULVu2YLXa+Oij2bjdbgYO7M/q1as5ceI4Xbt2p3Hjpvz73+8xY8Y0unfvwdq1a/jsswVkZ2czbtxoMjKy8q/P6XTzyisj8h/36tUvf55HHukKwDPP9Gbs2FG43Sb79sWzb99ePvxwFhaLhTFjXmfp0m/o0eMZvvxyIZMmvYevr/8lr8E0TXx8fJk16zPWrPkfM2dO5447oli06P/o2bMXEREtOXToIM8+24POnbsya9YMBg0aym23NWDevE/444/tVK1ajZMnT9C9ew/q12/IiBFDWL58OY8+2v2y961s2fLMmDGXceNG88kns5ky5SN+++1Xpkx5m7vuuveSObjdJjt2bOfDD2fhdrt57rmnaNq0BXXr1ru6b+otwO12k5ycViixg4PLFFpsERERKX56rxcRESn99H4vIlJ8ch0uAP07fJUsFuOizVKnFXkhLC4ujt69e/P000/Tq1cvAEJCQkhOTs4fc/To0fzlFAvKnbdX4s7bK13V2Anz8jrBXnmyWYHN36RJM/z9A/jiiwXs37+PgwcPkJWVSbVqYTRu3BSABx7owNixI3n++Rex2+0MGNCLNm2iGDDgBex2+3XPXaVKVaKjX+brrxexf38827b9RuXKVa4pRlTUXQDUqBFOSspJAKKjX2L9+l+YO3c2cXF/kpWVCUBkZFuGDRtMVFQ7oqLa0aJFaw4fTiAoKJj69RueilMzP87ltG7dBoCKFUMICgrGZrMRElKJtLS0y+YAcO+9D+Dj45Of0+bNG1UIExERERERERERERG5hRTqHmHnS09P57nnnuPFF1/ML4JB3pKJdrudzZs3A/DVV1/Rtm3bokyt0K1e/TNvvPEaXl5edOjQmcaNmxISUgmr1Zo/xjTd2Gw2bDYbH388h969B5CSkkL//n9j//746557x47tvPxyNKbp5u6776Ft27uueV+w03kahpF/7uuvv8qqVT9SvXoN+vZ9Pn/sY489yfvvT6NKlap88MEUPvlk5jkxzlzvlXPw8PC4IIe
|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 2160x360 with 1 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"tests = data[\"TEST\"].unique()\n",
|
|||
|
|
"plot_test(tests[1])\n"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 16,
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "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
|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 2160x360 with 1 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "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
|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 2160x360 with 1 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "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
|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 2160x360 with 1 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"plot_test(tests[2])"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 41,
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
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|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 2160x360 with 1 Axes>"
|
|||
|
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]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
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},
|
|||
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{
|
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|
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"data": {
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"image/png": "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
|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 2160x360 with 1 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "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
|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 2160x360 with 1 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"plot_test(tests[3])"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": 42,
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "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
|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 2160x360 with 1 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
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|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 2160x360 with 1 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"data": {
|
|||
|
|
"image/png": "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
|
|||
|
|
"text/plain": [
|
|||
|
|
"<Figure size 2160x360 with 1 Axes>"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
"metadata": {},
|
|||
|
|
"output_type": "display_data"
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"source": [
|
|||
|
|
"plot_test(tests[4])"
|
|||
|
|
]
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": null,
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": []
|
|||
|
|
},
|
|||
|
|
{
|
|||
|
|
"cell_type": "code",
|
|||
|
|
"execution_count": null,
|
|||
|
|
"metadata": {},
|
|||
|
|
"outputs": [],
|
|||
|
|
"source": []
|
|||
|
|
}
|
|||
|
|
],
|
|||
|
|
"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"
|
|||
|
|
}
|
|||
|
|
},
|
|||
|
|
"nbformat": 4,
|
|||
|
|
"nbformat_minor": 4
|
|||
|
|
}
|