{ "cells": [ { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import statsmodels.api as sm\n", "import statsmodels.formula.api as smf\n", "import numpy as np" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "data = pd.read_csv(\"r2vals.csv\").sort_values(\"r2 \")" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", " | r2 | \n", "
---|---|
count | \n", "133.000000 | \n", "
mean | \n", "0.677843 | \n", "
std | \n", "0.229390 | \n", "
min | \n", "0.135144 | \n", "
25% | \n", "0.474227 | \n", "
50% | \n", "0.734562 | \n", "
75% | \n", "0.878335 | \n", "
max | \n", "0.968964 | \n", "
\n", " | test | \n", "map | \n", "size | \n", "time | \n", "
---|---|---|---|---|
0 | \n", "int_delete | \n", "absl::flat_hash_map | \n", "1.0 | \n", "2.516393 | \n", "
1 | \n", "int_delete | \n", "absl::flat_hash_map | \n", "100001.0 | \n", "11.352983 | \n", "
2 | \n", "int_delete | \n", "absl::flat_hash_map | \n", "200001.0 | \n", "12.227014 | \n", "
3 | \n", "int_delete | \n", "absl::flat_hash_map | \n", "300001.0 | \n", "12.806459 | \n", "
4 | \n", "int_delete | \n", "absl::flat_hash_map | \n", "400001.0 | \n", "13.254607 | \n", "
... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "
495 | \n", "string_succ_lookup | \n", "tsl::sparse_map | \n", "49500001.0 | \n", "267.156427 | \n", "
496 | \n", "string_succ_lookup | \n", "tsl::sparse_map | \n", "49600001.0 | \n", "267.172009 | \n", "
497 | \n", "string_succ_lookup | \n", "tsl::sparse_map | \n", "49700001.0 | \n", "267.187371 | \n", "
498 | \n", "string_succ_lookup | \n", "tsl::sparse_map | \n", "49800001.0 | \n", "267.202512 | \n", "
499 | \n", "string_succ_lookup | \n", "tsl::sparse_map | \n", "49900001.0 | \n", "267.217433 | \n", "
68000 rows × 4 columns
\n", "