[RtoPy]상관분석.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 상관분석 - 1\n",
    "- 출처 : https://m.blog.naver.com/parksehoon1971/221575542220"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. 데이터 준비"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ozone</th>\n",
       "      <th>Solar.R</th>\n",
       "      <th>Wind</th>\n",
       "      <th>Temp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>41.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>7.4</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>36.0</td>\n",
       "      <td>118.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12.0</td>\n",
       "      <td>149.0</td>\n",
       "      <td>12.6</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>18.0</td>\n",
       "      <td>313.0</td>\n",
       "      <td>11.5</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.3</td>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Ozone  Solar.R  Wind  Temp\n",
       "0   41.0    190.0   7.4    67\n",
       "1   36.0    118.0   8.0    72\n",
       "2   12.0    149.0  12.6    74\n",
       "3   18.0    313.0  11.5    62\n",
       "4    NaN      NaN  14.3    56"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('airquality.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ozone</th>\n",
       "      <th>Solar.R</th>\n",
       "      <th>Wind</th>\n",
       "      <th>Temp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Ozone</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.348342</td>\n",
       "      <td>-0.601547</td>\n",
       "      <td>0.698360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Solar.R</th>\n",
       "      <td>0.348342</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.056792</td>\n",
       "      <td>0.275840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wind</th>\n",
       "      <td>-0.601547</td>\n",
       "      <td>-0.056792</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.457988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Temp</th>\n",
       "      <td>0.698360</td>\n",
       "      <td>0.275840</td>\n",
       "      <td>-0.457988</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Ozone   Solar.R      Wind      Temp\n",
       "Ozone    1.000000  0.348342 -0.601547  0.698360\n",
       "Solar.R  0.348342  1.000000 -0.056792  0.275840\n",
       "Wind    -0.601547 -0.056792  1.000000 -0.457988\n",
       "Temp     0.698360  0.275840 -0.457988  1.000000"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr = df.corr(method='pearson')\n",
    "corr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\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>Ozone</th>\n",
       "      <th>Solar.R</th>\n",
       "      <th>Wind</th>\n",
       "      <th>Temp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>41.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>7.4</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>36.0</td>\n",
       "      <td>118.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12.0</td>\n",
       "      <td>149.0</td>\n",
       "      <td>12.6</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>18.0</td>\n",
       "      <td>313.0</td>\n",
       "      <td>11.5</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>23.0</td>\n",
       "      <td>299.0</td>\n",
       "      <td>8.6</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Ozone  Solar.R  Wind  Temp\n",
       "0   41.0    190.0   7.4    67\n",
       "1   36.0    118.0   8.0    72\n",
       "2   12.0    149.0  12.6    74\n",
       "3   18.0    313.0  11.5    62\n",
       "6   23.0    299.0   8.6    65"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 결측치 제거\n",
    "df_drop_na = df.dropna()\n",
    "df_drop_na.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .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>Ozone</th>\n",
       "      <th>Solar.R</th>\n",
       "      <th>Wind</th>\n",
       "      <th>Temp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Ozone</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.348342</td>\n",
       "      <td>-0.612497</td>\n",
       "      <td>0.698541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Solar.R</th>\n",
       "      <td>0.348342</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.127183</td>\n",
       "      <td>0.294088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wind</th>\n",
       "      <td>-0.612497</td>\n",
       "      <td>-0.127183</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.497190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Temp</th>\n",
       "      <td>0.698541</td>\n",
       "      <td>0.294088</td>\n",
       "      <td>-0.497190</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Ozone   Solar.R      Wind      Temp\n",
       "Ozone    1.000000  0.348342 -0.612497  0.698541\n",
       "Solar.R  0.348342  1.000000 -0.127183  0.294088\n",
       "Wind    -0.612497 -0.127183  1.000000 -0.497190\n",
       "Temp     0.698541  0.294088 -0.497190  1.000000"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corr_1 = df_drop_na.corr(method='pearson')\n",
    "corr_1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. 데이터 시각화"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 모듈\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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edT+Gcg9YPkOxoCpMyG9QXx6ktTvOyrnl417Mw28YBPxnMsDBdBA807O/M2Ws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\n/4RFnNJeSV7zAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x9cfbd70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# pairplot\n",
    "g = sns.pairplot(df_drop_na, kind='reg', markers='+')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1142b90>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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/pOwi+YN3Gf3wvTz14qultn1+5CPMfPcNZr77Bg3j3Mc9Y04y9evVZf6H73Hz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\nBwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10dec90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Heatmap\n",
    "plt.figure(figsize=(6,5))\n",
    "sns.heatmap(data=corr_1, annot=True, fmt='.2f', linewidths=0.5, cmap='Reds')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 상관분석 - 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>제품 판매량</th>\n",
       "      <th>일인당소득</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>19</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>22</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>13</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>16</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>16</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>12</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   제품 판매량  일인당소득\n",
       "0       8     20\n",
       "1      19     34\n",
       "2      11     20\n",
       "3       5     15\n",
       "4      22     28\n",
       "5      13     28\n",
       "6       6     14\n",
       "7      16     20\n",
       "8      16     38\n",
       "9      12     32"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cor01 = pd.read_excel('cor01.xlsx')\n",
    "cor01"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>sales</th>\n",
       "      <th>gdp1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>19</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>22</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>13</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>16</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>16</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>12</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   sales  gdp1\n",
       "0      8    20\n",
       "1     19    34\n",
       "2     11    20\n",
       "3      5    15\n",
       "4     22    28\n",
       "5     13    28\n",
       "6      6    14\n",
       "7     16    20\n",
       "8     16    38\n",
       "9     12    32"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cor01.columns = ['sales','gdp1']\n",
    "cor01"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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JEpaBJAnLQJKEZSBJwjKQJGEZSJKwDCRJWAaSJCwDSRKWgSQJy0CShGUgScIykCRhGUiS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\nJGEZSJKwDCRJwP8HkQlHIQT85lcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xbc256d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 산점도\n",
    "plt.figure(figsize=(6,6)) # 플롯 사이즈 지정\n",
    "plt.scatter(cor01.sales, cor01.gdp1)\n",
    "plt.xlabel('Sales')\n",
    "plt.ylabel('GDP1')\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x6df1f90>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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3cPfaFj5109K8HQhbWeahOpD9gbp7jvfz8K5jeN2GmoCX/rEID+86xiOgIDND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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x6df1d50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# pairplot\n",
    "sns.pairplot(cor01, kind='reg', height=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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A9aeedlGreps3TnPGtrXbzS8U/82nTIwumCWYnJyk7TFdjrbtYbHWe/vpQldt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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x6c3cc70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 히스토그램\n",
    "plt.figure(figsize=(10,6))\n",
    "plt.suptitle('Histogram')\n",
    "\n",
    "plt.subplot(1,2,1)\n",
    "plt.hist(cor01.sales, bins=9) # sales를 9등분하여 히스토그램 작성\n",
    "plt.xlabel('Sales')\n",
    "plt.ylabel('Frequency')\n",
    "plt.grid()\n",
    "\n",
    "plt.subplot(1,2,2)\n",
    "plt.hist(cor01.gdp1, bins=7) \n",
    "plt.xlabel('GDP1')\n",
    "plt.ylabel('Frequency')\n",
    "plt.grid()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 상관계수\n",
    "import scipy.stats as stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.70257685636819556, 0.023466513078597345)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# pearson 상관계수 검정\n",
    "corr = stats.pearsonr(cor01.sales, cor01.gdp1)\n",
    "corr # 결과 : 피어슨상관계수, P-value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SpearmanrResult(correlation=0.73462388750813223, pvalue=0.015523515329958141)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 스피어만 상관계수 검정\n",
    "rho = stats.spearmanr(cor01.sales, cor01.gdp1)\n",
    "rho"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KendalltauResult(correlation=0.56505793121761339, pvalue=0.028078796256186304)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 켄달의 타우 검정\n",
    "tau = stats.kendalltau(cor01.sales, cor01.gdp1)\n",
    "tau"
   ]
  },
  {
   "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": "3.6.2"
  }
 },
 "nbformat": 4,
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}