pandasでOUTER JOINする方法

pandas_outer_join.ipynb

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   "source": [
    "import pandas as pd\n",
    "from pandas import DataFrame"
   ]
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    "df1 = DataFrame({\"data1\":range(3,8)})"
   ]
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       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>data1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>6</td>\n",
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       "      <th>4</th>\n",
       "      <td>7</td>\n",
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       "  </tbody>\n",
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      "text/plain": [
       "   data1\n",
       "0      3\n",
       "1      4\n",
       "2      5\n",
       "3      6\n",
       "4      7"
      ]
     },
     "execution_count": 3,
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   ],
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    "df1"
   ]
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   "execution_count": 4,
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   "source": [
    "df2 = DataFrame({\"data2\": range(5)[::-1]})"
   ]
  },
  {
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   "execution_count": 5,
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       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>data2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4</td>\n",
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       "      <th>1</th>\n",
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       "      <th>2</th>\n",
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      "text/plain": [
       "   data2\n",
       "0      4\n",
       "1      3\n",
       "2      2\n",
       "3      1\n",
       "4      0"
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    "df2"
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   "execution_count": 6,
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   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>data1</th>\n",
       "      <th>data2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5.0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NaN</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "   data1  data2\n",
       "0    3.0    3.0\n",
       "1    4.0    4.0\n",
       "2    5.0    NaN\n",
       "3    6.0    NaN\n",
       "4    7.0    NaN\n",
       "5    NaN    2.0\n",
       "6    NaN    1.0\n",
       "7    NaN    0.0"
      ]
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     "execution_count": 6,
     "metadata": {},
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   ],
   "source": [
    "df = pd.merge(df1,df2, left_on=\"data1\", right_on=\"data2\", how=\"outer\")\n",
    "df"
   ]
  }
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