mpg-plotting-a-diagonal-correlation-matrix.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting a diagonal correlation matrix\n",
    "* https://seaborn.pydata.org/examples/many_pairwise_correlations.html\n",
    "* [상관 분석 - 위키백과, 우리 모두의 백과사전](https://ko.wikipedia.org/wiki/%EC%83%81%EA%B4%80_%EB%B6%84%EC%84%9D)\n",
    "* [Correlation and dependence - Wikipedia](https://en.wikipedia.org/wiki/Correlation_and_dependence)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from string import ascii_letters\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "sns.set(style=\"white\")\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "      <th>E</th>\n",
       "      <th>F</th>\n",
       "      <th>G</th>\n",
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       "      <th>J</th>\n",
       "      <th>...</th>\n",
       "      <th>Q</th>\n",
       "      <th>R</th>\n",
       "      <th>S</th>\n",
       "      <th>T</th>\n",
       "      <th>U</th>\n",
       "      <th>V</th>\n",
       "      <th>W</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>Z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.318854</td>\n",
       "      <td>-1.602981</td>\n",
       "      <td>-1.535218</td>\n",
       "      <td>-0.570401</td>\n",
       "      <td>-0.216728</td>\n",
       "      <td>0.254874</td>\n",
       "      <td>-0.149450</td>\n",
       "      <td>2.010783</td>\n",
       "      <td>-0.096784</td>\n",
       "      <td>0.422202</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.951219</td>\n",
       "      <td>0.832973</td>\n",
       "      <td>-1.000208</td>\n",
       "      <td>0.343463</td>\n",
       "      <td>1.546030</td>\n",
       "      <td>0.690081</td>\n",
       "      <td>-2.045853</td>\n",
       "      <td>0.334467</td>\n",
       "      <td>-0.641459</td>\n",
       "      <td>-0.222497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-1.230374</td>\n",
       "      <td>0.205848</td>\n",
       "      <td>0.821371</td>\n",
       "      <td>-0.493780</td>\n",
       "      <td>-1.408794</td>\n",
       "      <td>-1.216324</td>\n",
       "      <td>1.734299</td>\n",
       "      <td>-0.206790</td>\n",
       "      <td>-0.733189</td>\n",
       "      <td>0.774163</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.148826</td>\n",
       "      <td>-0.606270</td>\n",
       "      <td>-1.185801</td>\n",
       "      <td>0.455504</td>\n",
       "      <td>-0.837645</td>\n",
       "      <td>-0.146961</td>\n",
       "      <td>-0.682350</td>\n",
       "      <td>1.487670</td>\n",
       "      <td>-1.094711</td>\n",
       "      <td>-1.654707</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          A         B         C         D         E         F         G  \\\n",
       "0 -0.318854 -1.602981 -1.535218 -0.570401 -0.216728  0.254874 -0.149450   \n",
       "1 -1.230374  0.205848  0.821371 -0.493780 -1.408794 -1.216324  1.734299   \n",
       "\n",
       "          H         I         J  ...         Q         R         S         T  \\\n",
       "0  2.010783 -0.096784  0.422202  ... -0.951219  0.832973 -1.000208  0.343463   \n",
       "1 -0.206790 -0.733189  0.774163  ... -0.148826 -0.606270 -1.185801  0.455504   \n",
       "\n",
       "          U         V         W         X         Y         Z  \n",
       "0  1.546030  0.690081 -2.045853  0.334467 -0.641459 -0.222497  \n",
       "1 -0.837645 -0.146961 -0.682350  1.487670 -1.094711 -1.654707  \n",
       "\n",
       "[2 rows x 26 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Generate a large random dataset\n",
    "rs = np.random.RandomState(33)\n",
    "d = pd.DataFrame(data=rs.normal(size=(100, 26)),\n",
    "                 columns=list(ascii_letters[26:]))\n",
    "d.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "      <th>E</th>\n",
       "      <th>F</th>\n",
       "      <th>G</th>\n",
       "      <th>H</th>\n",
       "      <th>I</th>\n",
       "      <th>J</th>\n",
       "      <th>...</th>\n",
       "      <th>Q</th>\n",
       "      <th>R</th>\n",
       "      <th>S</th>\n",
       "      <th>T</th>\n",
       "      <th>U</th>\n",
       "      <th>V</th>\n",
       "      <th>W</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>Z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.107401</td>\n",
       "      <td>-0.086468</td>\n",
       "      <td>0.000131</td>\n",
       "      <td>0.035047</td>\n",
       "      <td>0.004749</td>\n",
       "      <td>0.028226</td>\n",
       "      <td>0.000422</td>\n",
       "      <td>0.132100</td>\n",
       "      <td>0.057720</td>\n",
       "      <td>...</td>\n",
       "      <td>0.073645</td>\n",
       "      <td>-0.055396</td>\n",
       "      <td>-0.058241</td>\n",
       "      <td>-0.123823</td>\n",
       "      <td>0.096451</td>\n",
       "      <td>-0.015178</td>\n",
       "      <td>0.172725</td>\n",
       "      <td>0.003791</td>\n",
       "      <td>0.005531</td>\n",
       "      <td>-0.011534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>-0.107401</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.254632</td>\n",
       "      <td>0.061506</td>\n",
       "      <td>0.043581</td>\n",
       "      <td>-0.078019</td>\n",
       "      <td>0.069133</td>\n",
       "      <td>-0.211278</td>\n",
       "      <td>-0.011796</td>\n",
       "      <td>0.085277</td>\n",
       "      <td>...</td>\n",
       "      <td>0.031315</td>\n",
       "      <td>0.100451</td>\n",
       "      <td>-0.103068</td>\n",
       "      <td>0.011187</td>\n",
       "      <td>-0.008536</td>\n",
       "      <td>-0.030730</td>\n",
       "      <td>-0.022978</td>\n",
       "      <td>-0.050483</td>\n",
       "      <td>-0.014468</td>\n",
       "      <td>0.078737</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          A         B         C         D         E         F         G  \\\n",
       "A  1.000000 -0.107401 -0.086468  0.000131  0.035047  0.004749  0.028226   \n",
       "B -0.107401  1.000000  0.254632  0.061506  0.043581 -0.078019  0.069133   \n",
       "\n",
       "          H         I         J  ...         Q         R         S         T  \\\n",
       "A  0.000422  0.132100  0.057720  ...  0.073645 -0.055396 -0.058241 -0.123823   \n",
       "B -0.211278 -0.011796  0.085277  ...  0.031315  0.100451 -0.103068  0.011187   \n",
       "\n",
       "          U         V         W         X         Y         Z  \n",
       "A  0.096451 -0.015178  0.172725  0.003791  0.005531 -0.011534  \n",
       "B -0.008536 -0.030730 -0.022978 -0.050483 -0.014468  0.078737  \n",
       "\n",
       "[2 rows x 26 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Compute the correlation matrix\n",
    "corr = d.corr()\n",
    "corr.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ True,  True,  True, False, False, False, False, False, False,\n",
       "       False, False, False, False, False, False, False, False, False,\n",
       "       False, False, False, False, False, False, False, False])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Generate a mask for the upper triangle\n",
    "mask = np.zeros_like(corr, dtype=np.bool)\n",
    "mask[np.triu_indices_from(mask)] = True\n",
    "mask[:, 2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Generate a custom diverging colormap\n",
    "cmap = sns.diverging_palette(220, 10, as_cmap=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1262594e0>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Hyf95ZdBxnZCQkMDq1asBSE1NJS6u7C5up06dSE5Oxul0kp+fT3Z2NrGxsZXm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\nZpmCSucaMAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 792x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(11, 9))\n",
    "sns.heatmap(corr, mask=mask, cmap=cmap, center=0, vmax=.3, \n",
    "            annot=True, fmt=\".1f\",\n",
    "            square=True, linewidths=.5, cbar_kws={\"shrink\": .5})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1258eae80>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ngYeAtwBExHuBqZn56ZGE2lRJkqS2avU+VbXNzfcY5Ph3Bzl2zWDPHYxNlSRJ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\nJKkENlWSJEklsKmSJEkqwf8HyeQRDTXqIbkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 792x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Set up the matplotlib figure\n",
    "f, ax = plt.subplots(figsize=(11, 9))\n",
    "\n",
    "# Draw the heatmap with the mask and correct aspect ratio\n",
    "sns.heatmap(corr, mask=mask, cmap=cmap, vmax=.3, center=0,\n",
    "            square=True, linewidths=.5, cbar_kws={\"shrink\": .5})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mpg</th>\n",
       "      <th>cylinders</th>\n",
       "      <th>displacement</th>\n",
       "      <th>horsepower</th>\n",
       "      <th>weight</th>\n",
       "      <th>acceleration</th>\n",
       "      <th>model_year</th>\n",
       "      <th>origin</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>18.0</td>\n",
       "      <td>8</td>\n",
       "      <td>307.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>3504</td>\n",
       "      <td>12.0</td>\n",
       "      <td>70</td>\n",
       "      <td>usa</td>\n",
       "      <td>chevrolet chevelle malibu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>15.0</td>\n",
       "      <td>8</td>\n",
       "      <td>350.0</td>\n",
       "      <td>165.0</td>\n",
       "      <td>3693</td>\n",
       "      <td>11.5</td>\n",
       "      <td>70</td>\n",
       "      <td>usa</td>\n",
       "      <td>buick skylark 320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>18.0</td>\n",
       "      <td>8</td>\n",
       "      <td>318.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>3436</td>\n",
       "      <td>11.0</td>\n",
       "      <td>70</td>\n",
       "      <td>usa</td>\n",
       "      <td>plymouth satellite</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>16.0</td>\n",
       "      <td>8</td>\n",
       "      <td>304.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>3433</td>\n",
       "      <td>12.0</td>\n",
       "      <td>70</td>\n",
       "      <td>usa</td>\n",
       "      <td>amc rebel sst</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17.0</td>\n",
       "      <td>8</td>\n",
       "      <td>302.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>3449</td>\n",
       "      <td>10.5</td>\n",
       "      <td>70</td>\n",
       "      <td>usa</td>\n",
       "      <td>ford torino</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    mpg  cylinders  displacement  horsepower  weight  acceleration  \\\n",
       "0  18.0          8         307.0       130.0    3504          12.0   \n",
       "1  15.0          8         350.0       165.0    3693          11.5   \n",
       "2  18.0          8         318.0       150.0    3436          11.0   \n",
       "3  16.0          8         304.0       150.0    3433          12.0   \n",
       "4  17.0          8         302.0       140.0    3449          10.5   \n",
       "\n",
       "   model_year origin                       name  \n",
       "0          70    usa  chevrolet chevelle malibu  \n",
       "1          70    usa          buick skylark 320  \n",
       "2          70    usa         plymouth satellite  \n",
       "3          70    usa              amc rebel sst  \n",
       "4          70    usa                ford torino  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mpg = sns.load_dataset(\"mpg\")\n",
    "mpg.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mpg</th>\n",
       "      <th>cylinders</th>\n",
       "      <th>displacement</th>\n",
       "      <th>horsepower</th>\n",
       "      <th>weight</th>\n",
       "      <th>acceleration</th>\n",
       "      <th>model_year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mpg</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.775396</td>\n",
       "      <td>-0.804203</td>\n",
       "      <td>-0.778427</td>\n",
       "      <td>-0.831741</td>\n",
       "      <td>0.420289</td>\n",
       "      <td>0.579267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cylinders</th>\n",
       "      <td>-0.775396</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.950721</td>\n",
       "      <td>0.842983</td>\n",
       "      <td>0.896017</td>\n",
       "      <td>-0.505419</td>\n",
       "      <td>-0.348746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>displacement</th>\n",
       "      <td>-0.804203</td>\n",
       "      <td>0.950721</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.897257</td>\n",
       "      <td>0.932824</td>\n",
       "      <td>-0.543684</td>\n",
       "      <td>-0.370164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>horsepower</th>\n",
       "      <td>-0.778427</td>\n",
       "      <td>0.842983</td>\n",
       "      <td>0.897257</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.864538</td>\n",
       "      <td>-0.689196</td>\n",
       "      <td>-0.416361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>weight</th>\n",
       "      <td>-0.831741</td>\n",
       "      <td>0.896017</td>\n",
       "      <td>0.932824</td>\n",
       "      <td>0.864538</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.417457</td>\n",
       "      <td>-0.306564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>acceleration</th>\n",
       "      <td>0.420289</td>\n",
       "      <td>-0.505419</td>\n",
       "      <td>-0.543684</td>\n",
       "      <td>-0.689196</td>\n",
       "      <td>-0.417457</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.288137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>model_year</th>\n",
       "      <td>0.579267</td>\n",
       "      <td>-0.348746</td>\n",
       "      <td>-0.370164</td>\n",
       "      <td>-0.416361</td>\n",
       "      <td>-0.306564</td>\n",
       "      <td>0.288137</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   mpg  cylinders  displacement  horsepower    weight  \\\n",
       "mpg           1.000000  -0.775396     -0.804203   -0.778427 -0.831741   \n",
       "cylinders    -0.775396   1.000000      0.950721    0.842983  0.896017   \n",
       "displacement -0.804203   0.950721      1.000000    0.897257  0.932824   \n",
       "horsepower   -0.778427   0.842983      0.897257    1.000000  0.864538   \n",
       "weight       -0.831741   0.896017      0.932824    0.864538  1.000000   \n",
       "acceleration  0.420289  -0.505419     -0.543684   -0.689196 -0.417457   \n",
       "model_year    0.579267  -0.348746     -0.370164   -0.416361 -0.306564   \n",
       "\n",
       "              acceleration  model_year  \n",
       "mpg               0.420289    0.579267  \n",
       "cylinders        -0.505419   -0.348746  \n",
       "displacement     -0.543684   -0.370164  \n",
       "horsepower       -0.689196   -0.416361  \n",
       "weight           -0.417457   -0.306564  \n",
       "acceleration      1.000000    0.288137  \n",
       "model_year        0.288137    1.000000  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c = mpg.corr()\n",
    "c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ True,  True,  True, False, False, False, False])"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Generate a mask for the upper triangle\n",
    "mask = np.zeros_like(c, dtype=np.bool)\n",
    "mask[np.triu_indices_from(mask)] = True\n",
    "mask[:, 2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x127743278>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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7PF7CnCeJ7F5taXRKNyLj44ipUokGJ3cmMi6Wfes2MXPCc7x+xlDWfDODc597MKQxi0jZ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\n",
      "text/plain": [
       "<Figure size 504x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(7, 5))\n",
    "sns.heatmap(c, cmap=\"RdBu_r\", mask=mask, annot=True)"
   ]
  },
  {
   "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": "3.6.1"
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
   ],
   "window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}