2-data-handling.ipynb

{
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  {
   "cell_type": "markdown",
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    "collapsed": true
   },
   "source": [
    "# データハンドリング\n",
    "\n",
    "## この章で扱うもの\n",
    "\n",
    "- 千葉市の過去3年間の気象データ\n",
    "- 千葉市の過去3年間のインフルエンザ発見件数のデータ\n",
    "- 上記のデータを組合せて、この次の章で使用する可視化や機械学習で使用しやすいデータにする\n",
    "\n",
    "### 気象データ\n",
    "\n",
    "気象データは気象庁のWebサイトから様々なデータが取得可能です。\n",
    "今回は、過去3年間の千葉市をターゲットにしているので、必要な項目を選択しCSVで入手します。\n",
    "\n",
    "\n",
    "### インフルエンザ発見件数\n",
    "\n",
    "千葉市のオープンデータに、「インフルエンザの週毎の定点当たり報告数」というものがあり、それを用いる\n",
    "\n",
    "\n",
    "## この章で取り扱う手順\n",
    "\n",
    "- データの入手(2箇所から、CSVデータ)\n",
    "- データの概要確認\n",
    "- データの結合\n",
    "- データの加工\n",
    "- 欠損値処理\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 必要なライブラリのインポート"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# データの入手・概要を確認・加工"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 気象データ\n",
    "\n",
    "気象庁の過去の気象データ\n",
    "http://www.data.jma.go.jp/gmd/risk/obsdl/index.php"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_weather = pd.read_csv(\"data/気象庁千葉.csv\", encoding='shift_jis')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "pandas の read_csv関数で、CSVデータを読込。読み込みの際に文字エンコーディングを指定している"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>ダウンロードした時刻：2017/06/17 12:09:19</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <th>千葉</th>\n",
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       "      <th>千葉</th>\n",
       "      <th>千葉</th>\n",
       "      <td>千葉</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>年月日</th>\n",
       "      <th>平均気温(℃)</th>\n",
       "      <th>平均気温(℃)</th>\n",
       "      <th>平均気温(℃)</th>\n",
       "      <th>最高気温(℃)</th>\n",
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       "      <th>最高気温(℃)</th>\n",
       "      <th>最低気温(℃)</th>\n",
       "      <th>最低気温(℃)</th>\n",
       "      <th>最低気温(℃)</th>\n",
       "      <th>平均湿度(％)</th>\n",
       "      <th>平均湿度(％)</th>\n",
       "      <th>平均湿度(％)</th>\n",
       "      <th>最小相対湿度(％)</th>\n",
       "      <th>最小相対湿度(％)</th>\n",
       "      <th>最小相対湿度(％)</th>\n",
       "      <th>平均現地気圧(hPa)</th>\n",
       "      <th>平均現地気圧(hPa)</th>\n",
       "      <th>平均現地気圧(hPa)</th>\n",
       "      <th>降水量の合計(mm)</th>\n",
       "      <th>降水量の合計(mm)</th>\n",
       "      <th>降水量の合計(mm)</th>\n",
       "      <th>降水量の合計(mm)</th>\n",
       "      <th>日照時間(時間)</th>\n",
       "      <th>日照時間(時間)</th>\n",
       "      <th>日照時間(時間)</th>\n",
       "      <th>日照時間(時間)</th>\n",
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       "      <td>平均風速(m/s)</td>\n",
       "    </tr>\n",
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       "      <th rowspan=\"2\" valign=\"top\">NaN</th>\n",
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       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
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       "      <th>均質番号</th>\n",
       "      <th>NaN</th>\n",
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       "      <th>品質情報</th>\n",
       "      <th>均質番号</th>\n",
       "      <th>NaN</th>\n",
       "      <th>現象なし情報</th>\n",
       "      <th>品質情報</th>\n",
       "      <th>均質番号</th>\n",
       "      <th>NaN</th>\n",
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       "      <th>NaN</th>\n",
       "      <th>品質情報</th>\n",
       "      <td>均質番号</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014/1/1</th>\n",
       "      <th>9.8</th>\n",
       "      <th>8</th>\n",
       "      <th>1</th>\n",
       "      <th>13.7</th>\n",
       "      <th>8</th>\n",
       "      <th>1</th>\n",
       "      <th>3.9</th>\n",
       "      <th>8</th>\n",
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       "      <th>54</th>\n",
       "      <th>8</th>\n",
       "      <th>1</th>\n",
       "      <th>37</th>\n",
       "      <th>8</th>\n",
       "      <th>1</th>\n",
       "      <th>1005.3</th>\n",
       "      <th>8</th>\n",
       "      <th>1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>8</th>\n",
       "      <th>1</th>\n",
       "      <th>9.2</th>\n",
       "      <th>0</th>\n",
       "      <th>8</th>\n",
       "      <th>1</th>\n",
       "      <th>5.3</th>\n",
       "      <th>8</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "                                                                                                                                                                                                                                                                               ダウンロードした時刻：2017/06/17 12:09:19\n",
       "NaN      千葉      千葉      千葉      千葉      千葉      千葉      千葉      千葉      千葉      千葉      千葉      千葉      千葉        千葉        千葉        千葉          千葉          千葉          千葉         千葉         千葉         千葉         千葉       千葉       千葉       千葉       千葉        千葉                                    千葉\n",
       "年月日      平均気温(℃) 平均気温(℃) 平均気温(℃) 最高気温(℃) 最高気温(℃) 最高気温(℃) 最低気温(℃) 最低気温(℃) 最低気温(℃) 平均湿度(％) 平均湿度(％) 平均湿度(％) 最小相対湿度(％) 最小相対湿度(％) 最小相対湿度(％) 平均現地気圧(hPa) 平均現地気圧(hPa) 平均現地気圧(hPa) 降水量の合計(mm) 降水量の合計(mm) 降水量の合計(mm) 降水量の合計(mm) 日照時間(時間) 日照時間(時間) 日照時間(時間) 日照時間(時間) 平均風速(m/s) 平均風速(m/s)                      平均風速(m/s)\n",
       "NaN      NaN     NaN     NaN     NaN     NaN     NaN     NaN     NaN     NaN     NaN     NaN     NaN     NaN       NaN       NaN       NaN         NaN         NaN         NaN        NaN        NaN        NaN        NaN      NaN      NaN      NaN      NaN       NaN                                  NaN\n",
       "                 品質情報    均質番号    NaN     品質情報    均質番号    NaN     品質情報    均質番号    NaN     品質情報    均質番号    NaN       品質情報      均質番号      NaN         品質情報        均質番号        NaN        現象なし情報     品質情報       均質番号       NaN      現象なし情報   品質情報     均質番号     NaN       品質情報                                均質番号\n",
       "2014/1/1 9.8     8       1       13.7    8       1       3.9     8       1       54      8       1       37        8         1         1005.3      8           1           0          1          8          1          9.2      0        8        1        5.3       8                                      1"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_weather.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "headメソッドで、データの先頭を確認。うまく取り込みているようです。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1220, 1)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_weather.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "データの行と列の数を確認。なぜか、1列になっています。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ダウンロードした時刻：2017/06/17 12:09:19\n",
      "\n",
      "\n",
      "\n",
      ",千葉,千葉,千葉,千葉,千葉,千葉,千葉,千葉,千葉,千葉,千葉,千葉,千葉,千葉,千葉,千葉,千葉,千葉,千葉,千葉,千葉,千葉,千葉,千葉,千葉,千葉,千葉,千葉,千葉\n",
      "\n",
      "年月日,平均気温(℃),平均気温(℃),平均気温(℃),最高気温(℃),最高気温(℃),最高気温(℃),最低気温(℃),最低気温(℃),最低気温(℃),平均湿度(％),平均湿度(％),平均湿度(％),最小相対湿度(％),最小相対湿度(％),最小相対湿度(％),平均現地気圧(hPa),平均現地気圧(hPa),平均現地気圧(hPa),降水量の合計(mm),降水量の合計(mm),降水量の合計(mm),降水量の合計(mm),日照時間(時間),日照時間(時間),日照時間(時間),日照時間(時間),平均風速(m/s),平均風速(m/s),平均風速(m/s)\n",
      "\n",
      ",,,,,,,,,,,,,,,,,,,,,,,,,,,,,\n",
      "\n",
      ",,品質情報,均質番号,,品質情報,均質番号,,品質情報,均質番号,,品質情報,均質番号,,品質情報,均質番号,,品質情報,均質番号,,現象なし情報,品質情報,均質番号,,現象なし情報,品質情報,均質番号,,品質情報,均質番号\n",
      "\n",
      "2014/1/1,9.8,8,1,13.7,8,1,3.9,8,1,54,8,1,37,8,1,1005.3,8,1,0,1,8,1,9.2,0,8,1,5.3,8,1\n",
      "\n",
      "2014/1/2,8.0,8,1,12.9,8,1,4.4,8,1,41,8,1,26,8,1,1011.3,8,1,0,1,8,1,9.1,0,8,1,3.0,8,1\n",
      "\n",
      "2014/1/3,5.9,8,1,9.9,8,1,2.7,8,1,43,8,1,32,8,1,1014.9,8,1,0,1,8,1,4.1,0,8,1,1.6,8,1\n",
      "\n",
      "2014/1/4,6.7,8,1,11.5,8,1,2.1,8,1,47,8,1,29,8,1,1009.5,8,1,0,1,8,1,5.9,0,8,1,2.4,8,1\n",
      "\n"
     ]
    }
   ],
   "source": [
    "f = open(\"data/気象庁千葉.csv\", encoding=\"shift_jis\")\n",
    "for l in f.readlines()[:10]:\n",
    "    print(l)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "元のCSVをテキストファイルとして読み込んで表示してみます。\n",
    "行と列の情報以外に１行目にデータ以外の情報が入っていました。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_weather = pd.read_csv(\"data/気象庁千葉.csv\", encoding='shift_jis', skiprows=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "気象データのCSVを再度読み込みます。今回は、３行目まで読み込み無視するように宣言しました。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1218, 30)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_weather.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "問題なく取り込めているようです。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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       "      <th>降水量の合計(mm).1</th>\n",
       "      <th>降水量の合計(mm).2</th>\n",
       "      <th>降水量の合計(mm).3</th>\n",
       "      <th>日照時間(時間)</th>\n",
       "      <th>日照時間(時間).1</th>\n",
       "      <th>日照時間(時間).2</th>\n",
       "      <th>日照時間(時間).3</th>\n",
       "      <th>平均風速(m/s)</th>\n",
       "      <th>平均風速(m/s).1</th>\n",
       "      <th>平均風速(m/s).2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>品質情報</td>\n",
       "      <td>均質番号</td>\n",
       "      <td>NaN</td>\n",
       "      <td>品質情報</td>\n",
       "      <td>均質番号</td>\n",
       "      <td>NaN</td>\n",
       "      <td>品質情報</td>\n",
       "      <td>均質番号</td>\n",
       "      <td>...</td>\n",
       "      <td>現象なし情報</td>\n",
       "      <td>品質情報</td>\n",
       "      <td>均質番号</td>\n",
       "      <td>NaN</td>\n",
       "      <td>現象なし情報</td>\n",
       "      <td>品質情報</td>\n",
       "      <td>均質番号</td>\n",
       "      <td>NaN</td>\n",
       "      <td>品質情報</td>\n",
       "      <td>均質番号</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014/1/1</td>\n",
       "      <td>9.8</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>13.7</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>3.9</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>9.2</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>5.3</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014/1/2</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>12.9</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>4.4</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>9.1</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014/1/3</td>\n",
       "      <td>5.9</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>9.9</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>2.7</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>4.1</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>1.6</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        年月日  平均気温(℃) 平均気温(℃).1 平均気温(℃).2  最高気温(℃) 最高気温(℃).1 最高気温(℃).2  \\\n",
       "0       NaN      NaN       NaN       NaN      NaN       NaN       NaN   \n",
       "1       NaN      NaN      品質情報      均質番号      NaN      品質情報      均質番号   \n",
       "2  2014/1/1      9.8         8         1     13.7         8         1   \n",
       "3  2014/1/2      8.0         8         1     12.9         8         1   \n",
       "4  2014/1/3      5.9         8         1      9.9         8         1   \n",
       "\n",
       "   最低気温(℃) 最低気温(℃).1 最低気温(℃).2     ...       降水量の合計(mm).1 降水量の合計(mm).2  \\\n",
       "0      NaN       NaN       NaN     ...                NaN          NaN   \n",
       "1      NaN      品質情報      均質番号     ...             現象なし情報         品質情報   \n",
       "2      3.9         8         1     ...                  1            8   \n",
       "3      4.4         8         1     ...                  1            8   \n",
       "4      2.7         8         1     ...                  1            8   \n",
       "\n",
       "  降水量の合計(mm).3  日照時間(時間) 日照時間(時間).1 日照時間(時間).2  日照時間(時間).3 平均風速(m/s)  \\\n",
       "0          NaN       NaN        NaN        NaN         NaN       NaN   \n",
       "1         均質番号       NaN     現象なし情報       品質情報        均質番号       NaN   \n",
       "2            1       9.2          0          8           1       5.3   \n",
       "3            1       9.1          0          8           1       3.0   \n",
       "4            1       4.1          0          8           1       1.6   \n",
       "\n",
       "  平均風速(m/s).1  平均風速(m/s).2  \n",
       "0         NaN          NaN  \n",
       "1        品質情報         均質番号  \n",
       "2           8            1  \n",
       "3           8            1  \n",
       "4           8            1  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_weather.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>年月日</th>\n",
       "      <th>平均気温(℃)</th>\n",
       "      <th>平均気温(℃).1</th>\n",
       "      <th>平均気温(℃).2</th>\n",
       "      <th>最高気温(℃)</th>\n",
       "      <th>最高気温(℃).1</th>\n",
       "      <th>最高気温(℃).2</th>\n",
       "      <th>最低気温(℃)</th>\n",
       "      <th>最低気温(℃).1</th>\n",
       "      <th>最低気温(℃).2</th>\n",
       "      <th>...</th>\n",
       "      <th>降水量の合計(mm).1</th>\n",
       "      <th>降水量の合計(mm).2</th>\n",
       "      <th>降水量の合計(mm).3</th>\n",
       "      <th>日照時間(時間)</th>\n",
       "      <th>日照時間(時間).1</th>\n",
       "      <th>日照時間(時間).2</th>\n",
       "      <th>日照時間(時間).3</th>\n",
       "      <th>平均風速(m/s)</th>\n",
       "      <th>平均風速(m/s).1</th>\n",
       "      <th>平均風速(m/s).2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1213</th>\n",
       "      <td>2017/4/26</td>\n",
       "      <td>17.0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>19.7</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>14.2</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>6.5</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1214</th>\n",
       "      <td>2017/4/27</td>\n",
       "      <td>14.7</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>17.6</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>11.6</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>2.6</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>4.5</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1215</th>\n",
       "      <td>2017/4/28</td>\n",
       "      <td>16.0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>20.1</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>12.7</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>7.4</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>2.7</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1216</th>\n",
       "      <td>2017/4/29</td>\n",
       "      <td>16.3</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>21.9</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>11.8</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>12.1</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1217</th>\n",
       "      <td>2017/4/30</td>\n",
       "      <td>18.0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>23.2</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>12.1</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>12.6</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>3.7</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            年月日  平均気温(℃) 平均気温(℃).1 平均気温(℃).2  最高気温(℃) 最高気温(℃).1 最高気温(℃).2  \\\n",
       "1213  2017/4/26     17.0         8         1     19.7         8         1   \n",
       "1214  2017/4/27     14.7         8         1     17.6         8         1   \n",
       "1215  2017/4/28     16.0         8         1     20.1         8         1   \n",
       "1216  2017/4/29     16.3         8         1     21.9         8         1   \n",
       "1217  2017/4/30     18.0         8         1     23.2         8         1   \n",
       "\n",
       "      最低気温(℃) 最低気温(℃).1 最低気温(℃).2     ...       降水量の合計(mm).1 降水量の合計(mm).2  \\\n",
       "1213     14.2         8         1     ...                  1            8   \n",
       "1214     11.6         8         1     ...                  0            8   \n",
       "1215     12.7         8         1     ...                  1            8   \n",
       "1216     11.8         8         1     ...                  1            8   \n",
       "1217     12.1         8         1     ...                  1            8   \n",
       "\n",
       "     降水量の合計(mm).3  日照時間(時間) 日照時間(時間).1 日照時間(時間).2  日照時間(時間).3 平均風速(m/s)  \\\n",
       "1213            1       0.2          0          8           1       6.5   \n",
       "1214            1       2.6          0          8           1       4.5   \n",
       "1215            1       7.4          0          8           1       2.7   \n",
       "1216            1      12.1          0          8           1       3.5   \n",
       "1217            1      12.6          0          8           1       3.7   \n",
       "\n",
       "     平均風速(m/s).1  平均風速(m/s).2  \n",
       "1213           8            1  \n",
       "1214           8            1  \n",
       "1215           8            1  \n",
       "1216           8            1  \n",
       "1217           8            1  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_weather.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ".head()メソッドと.tail()メソッドを使い、データの概要を見てみました。データとしては良さそうです。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "年月日                 NaN\n",
       "平均気温(℃)             NaN\n",
       "平均気温(℃).1          品質情報\n",
       "平均気温(℃).2          均質番号\n",
       "最高気温(℃)             NaN\n",
       "最高気温(℃).1          品質情報\n",
       "最高気温(℃).2          均質番号\n",
       "最低気温(℃)             NaN\n",
       "最低気温(℃).1          品質情報\n",
       "最低気温(℃).2          均質番号\n",
       "平均湿度(％)             NaN\n",
       "平均湿度(％).1          品質情報\n",
       "平均湿度(％).2          均質番号\n",
       "最小相対湿度(％)           NaN\n",
       "最小相対湿度(％).1        品質情報\n",
       "最小相対湿度(％).2        均質番号\n",
       "平均現地気圧(hPa)         NaN\n",
       "平均現地気圧(hPa).1      品質情報\n",
       "平均現地気圧(hPa).2      均質番号\n",
       "降水量の合計(mm)          NaN\n",
       "降水量の合計(mm).1     現象なし情報\n",
       "降水量の合計(mm).2       品質情報\n",
       "降水量の合計(mm).3       均質番号\n",
       "日照時間(時間)            NaN\n",
       "日照時間(時間).1       現象なし情報\n",
       "日照時間(時間).2         品質情報\n",
       "日照時間(時間).3         均質番号\n",
       "平均風速(m/s)           NaN\n",
       "平均風速(m/s).1        品質情報\n",
       "平均風速(m/s).2        均質番号\n",
       "Name: 1, dtype: object"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_weather.iloc[1, :]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "年月日              False\n",
       "平均気温(℃)          False\n",
       "平均気温(℃).1         True\n",
       "平均気温(℃).2         True\n",
       "最高気温(℃)          False\n",
       "最高気温(℃).1         True\n",
       "最高気温(℃).2         True\n",
       "最低気温(℃)          False\n",
       "最低気温(℃).1         True\n",
       "最低気温(℃).2         True\n",
       "平均湿度(％)          False\n",
       "平均湿度(％).1         True\n",
       "平均湿度(％).2         True\n",
       "最小相対湿度(％)        False\n",
       "最小相対湿度(％).1       True\n",
       "最小相対湿度(％).2       True\n",
       "平均現地気圧(hPa)      False\n",
       "平均現地気圧(hPa).1     True\n",
       "平均現地気圧(hPa).2     True\n",
       "降水量の合計(mm)       False\n",
       "降水量の合計(mm).1      True\n",
       "降水量の合計(mm).2      True\n",
       "降水量の合計(mm).3      True\n",
       "日照時間(時間)         False\n",
       "日照時間(時間).1        True\n",
       "日照時間(時間).2        True\n",
       "日照時間(時間).3        True\n",
       "平均風速(m/s)        False\n",
       "平均風速(m/s).1       True\n",
       "平均風速(m/s).2       True\n",
       "Name: 1, dtype: bool"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_weather.iloc[1, :].notnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 1, 4, 7, 10, 13, 16, 19, 23, 27]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[i for i, t in enumerate(df_weather.iloc[1, :].isnull()) if t]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_weather_temp = df_weather.iloc[:, [i for i, t in enumerate(df_weather.iloc[1, :].isnull()) if t]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ここではリスト内包表記でカラムの位置を取得していますが以下でも同じ動作になります。(pandasの機能を用いた方法)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_weather = df_weather[df_weather.columns[df_weather.iloc[1].isnull()]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "        年月日  平均気温(℃)  最高気温(℃)  最低気温(℃)  平均湿度(％)  最小相対湿度(％)  平均現地気圧(hPa)  \\\n",
       "0       NaN      NaN      NaN      NaN      NaN        NaN          NaN   \n",
       "1       NaN      NaN      NaN      NaN      NaN        NaN          NaN   \n",
       "2  2014/1/1      9.8     13.7      3.9     54.0       37.0       1005.3   \n",
       "3  2014/1/2      8.0     12.9      4.4     41.0       26.0       1011.3   \n",
       "4  2014/1/3      5.9      9.9      2.7     43.0       32.0       1014.9   \n",
       "\n",
       "   降水量の合計(mm)  日照時間(時間)  平均風速(m/s)  \n",
       "0         NaN       NaN        NaN  \n",
       "1         NaN       NaN        NaN  \n",
       "2         0.0       9.2        5.3  \n",
       "3         0.0       9.1        3.0  \n",
       "4         0.0       4.1        1.6  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_weather.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "      <th>1215</th>\n",
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       "      <td>62.0</td>\n",
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       "      <td>0.0</td>\n",
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       "      <th>1216</th>\n",
       "      <td>2017/4/29</td>\n",
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       "    <tr>\n",
       "      <th>1217</th>\n",
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       "      <td>57.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1009.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.6</td>\n",
       "      <td>3.7</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            年月日  平均気温(℃)  最高気温(℃)  最低気温(℃)  平均湿度(％)  最小相対湿度(％)  平均現地気圧(hPa)  \\\n",
       "1213  2017/4/26     17.0     19.7     14.2     69.0       53.0       1014.3   \n",
       "1214  2017/4/27     14.7     17.6     11.6     69.0       45.0       1004.9   \n",
       "1215  2017/4/28     16.0     20.1     12.7     62.0       31.0       1006.2   \n",
       "1216  2017/4/29     16.3     21.9     11.8     64.0       34.0       1005.7   \n",
       "1217  2017/4/30     18.0     23.2     12.1     57.0       31.0       1009.2   \n",
       "\n",
       "      降水量の合計(mm)  日照時間(時間)  平均風速(m/s)  \n",
       "1213         0.0       0.2        6.5  \n",
       "1214         6.5       2.6        4.5  \n",
       "1215         0.0       7.4        2.7  \n",
       "1216         0.0      12.1        3.5  \n",
       "1217         0.0      12.6        3.7  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_weather.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1218, 10)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_weather.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_weather = df_weather.drop([0, 1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_weather['年月日'] = pd.to_datetime(df_weather[\"年月日\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_weather = df_weather.set_index('年月日')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>2014-01-02</th>\n",
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       "      <th>2014-01-03</th>\n",
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       "      <th>2014-01-04</th>\n",
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       "      <th>2014-01-05</th>\n",
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       "      <td>40.0</td>\n",
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      "text/plain": [
       "            平均気温(℃)  最高気温(℃)  最低気温(℃)  平均湿度(％)  最小相対湿度(％)  平均現地気圧(hPa)  \\\n",
       "年月日                                                                      \n",
       "2014-01-01      9.8     13.7      3.9     54.0       37.0       1005.3   \n",
       "2014-01-02      8.0     12.9      4.4     41.0       26.0       1011.3   \n",
       "2014-01-03      5.9      9.9      2.7     43.0       32.0       1014.9   \n",
       "2014-01-04      6.7     11.5      2.1     47.0       29.0       1009.5   \n",
       "2014-01-05      4.4      6.9      2.3     40.0       28.0       1016.6   \n",
       "\n",
       "            降水量の合計(mm)  日照時間(時間)  平均風速(m/s)  \n",
       "年月日                                          \n",
       "2014-01-01         0.0       9.2        5.3  \n",
       "2014-01-02         0.0       9.1        3.0  \n",
       "2014-01-03         0.0       4.1        1.6  \n",
       "2014-01-04         0.0       5.9        2.4  \n",
       "2014-01-05         0.0       1.1        2.5  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_weather.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>2017-04-27</th>\n",
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       "      <th>2017-04-28</th>\n",
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       "      <td>62.0</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>2.7</td>\n",
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       "    <tr>\n",
       "      <th>2017-04-29</th>\n",
       "      <td>16.3</td>\n",
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       "      <td>11.8</td>\n",
       "      <td>64.0</td>\n",
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       "      <th>2017-04-30</th>\n",
       "      <td>18.0</td>\n",
       "      <td>23.2</td>\n",
       "      <td>12.1</td>\n",
       "      <td>57.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1009.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.6</td>\n",
       "      <td>3.7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            平均気温(℃)  最高気温(℃)  最低気温(℃)  平均湿度(％)  最小相対湿度(％)  平均現地気圧(hPa)  \\\n",
       "年月日                                                                      \n",
       "2017-04-26     17.0     19.7     14.2     69.0       53.0       1014.3   \n",
       "2017-04-27     14.7     17.6     11.6     69.0       45.0       1004.9   \n",
       "2017-04-28     16.0     20.1     12.7     62.0       31.0       1006.2   \n",
       "2017-04-29     16.3     21.9     11.8     64.0       34.0       1005.7   \n",
       "2017-04-30     18.0     23.2     12.1     57.0       31.0       1009.2   \n",
       "\n",
       "            降水量の合計(mm)  日照時間(時間)  平均風速(m/s)  \n",
       "年月日                                          \n",
       "2017-04-26         0.0       0.2        6.5  \n",
       "2017-04-27         6.5       2.6        4.5  \n",
       "2017-04-28         0.0       7.4        2.7  \n",
       "2017-04-29         0.0      12.1        3.5  \n",
       "2017-04-30         0.0      12.6        3.7  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_weather.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "平均気温(℃)        float64\n",
       "最高気温(℃)        float64\n",
       "最低気温(℃)        float64\n",
       "平均湿度(％)        float64\n",
       "最小相対湿度(％)      float64\n",
       "平均現地気圧(hPa)    float64\n",
       "降水量の合計(mm)     float64\n",
       "日照時間(時間)       float64\n",
       "平均風速(m/s)      float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_weather.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_weather.to_pickle(\"df_weather.db\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 千葉市のインフルエンザの状況\n",
    "\n",
    "千葉県のオープンデータ\n",
    "http://www.city.chiba.jp/opendata/index.php\n",
    "\n",
    "- インフルエンザの週毎の定点当たり報告数\n",
    "- ライセンス: CC-BY\n",
    "- 2014年、2015年、2016年"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "201412influenza.csv     201612influenza.csv     気象庁千葉.csv\r\n",
      "201512influenza.csv     201712influenza.csv     気象庁千葉2017.csv\r\n"
     ]
    }
   ],
   "source": [
    "!ls data/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_2014 = pd.read_csv(\"data/201412influenza.csv\", encoding=\"shift_jis\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe thead th {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2014年</th>\n",
       "      <th>インフルエンザ</th>\n",
       "      <th>Unnamed: 2</th>\n",
       "      <th>Unnamed: 3</th>\n",
       "      <th>Unnamed: 4</th>\n",
       "      <th>Unnamed: 5</th>\n",
       "      <th>Unnamed: 6</th>\n",
       "      <th>Unnamed: 7</th>\n",
       "      <th>Unnamed: 8</th>\n",
       "      <th>Unnamed: 9</th>\n",
       "      <th>...</th>\n",
       "      <th>Unnamed: 43</th>\n",
       "      <th>Unnamed: 44</th>\n",
       "      <th>Unnamed: 45</th>\n",
       "      <th>Unnamed: 46</th>\n",
       "      <th>Unnamed: 47</th>\n",
       "      <th>Unnamed: 48</th>\n",
       "      <th>Unnamed: 49</th>\n",
       "      <th>Unnamed: 50</th>\n",
       "      <th>Unnamed: 51</th>\n",
       "      <th>Unnamed: 52</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>週数</td>\n",
       "      <td>第1週</td>\n",
       "      <td>第2週</td>\n",
       "      <td>第3週</td>\n",
       "      <td>第4週</td>\n",
       "      <td>第5週</td>\n",
       "      <td>第6週</td>\n",
       "      <td>第7週</td>\n",
       "      <td>第8週</td>\n",
       "      <td>第9週</td>\n",
       "      <td>...</td>\n",
       "      <td>第43週</td>\n",
       "      <td>第44週</td>\n",
       "      <td>第45週</td>\n",
       "      <td>第46週</td>\n",
       "      <td>第47週</td>\n",
       "      <td>第48週</td>\n",
       "      <td>第49週</td>\n",
       "      <td>第50週</td>\n",
       "      <td>第51週</td>\n",
       "      <td>第52週</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>市全体（報告数/定点数）</td>\n",
       "      <td>0.178571429</td>\n",
       "      <td>2.814814815</td>\n",
       "      <td>9.75</td>\n",
       "      <td>25.32142857</td>\n",
       "      <td>31.32142857</td>\n",
       "      <td>33.25</td>\n",
       "      <td>26.21428571</td>\n",
       "      <td>25.53571429</td>\n",
       "      <td>30.60714286</td>\n",
       "      <td>...</td>\n",
       "      <td>0.285714286</td>\n",
       "      <td>0.571428571</td>\n",
       "      <td>0.571428571</td>\n",
       "      <td>1.107142857</td>\n",
       "      <td>3.111111111</td>\n",
       "      <td>5.357142857</td>\n",
       "      <td>7.964285714</td>\n",
       "      <td>12.75</td>\n",
       "      <td>20.21428571</td>\n",
       "      <td>31.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>中央区（報告数/定点数）</td>\n",
       "      <td>0.75</td>\n",
       "      <td>7</td>\n",
       "      <td>22.25</td>\n",
       "      <td>47.25</td>\n",
       "      <td>63</td>\n",
       "      <td>54</td>\n",
       "      <td>34</td>\n",
       "      <td>35.25</td>\n",
       "      <td>44.5</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>2.5</td>\n",
       "      <td>7</td>\n",
       "      <td>7.8</td>\n",
       "      <td>15</td>\n",
       "      <td>27.6</td>\n",
       "      <td>40.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>花見川区（報告数/定点数）</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3.75</td>\n",
       "      <td>15.5</td>\n",
       "      <td>17.25</td>\n",
       "      <td>20.25</td>\n",
       "      <td>17</td>\n",
       "      <td>16.5</td>\n",
       "      <td>17</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.75</td>\n",
       "      <td>1.25</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3.75</td>\n",
       "      <td>4.75</td>\n",
       "      <td>7</td>\n",
       "      <td>14.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>稲毛区（報告数/定点数）</td>\n",
       "      <td>0.2</td>\n",
       "      <td>2.8</td>\n",
       "      <td>12.8</td>\n",
       "      <td>21.4</td>\n",
       "      <td>27.8</td>\n",
       "      <td>37.4</td>\n",
       "      <td>29.2</td>\n",
       "      <td>24.8</td>\n",
       "      <td>25.2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.4</td>\n",
       "      <td>1.8</td>\n",
       "      <td>3.8</td>\n",
       "      <td>7.4</td>\n",
       "      <td>17.2</td>\n",
       "      <td>21.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 53 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           2014年      インフルエンザ   Unnamed: 2 Unnamed: 3   Unnamed: 4  \\\n",
       "0             週数          第1週          第2週        第3週          第4週   \n",
       "1   市全体（報告数/定点数）  0.178571429  2.814814815       9.75  25.32142857   \n",
       "2   中央区（報告数/定点数）         0.75            7      22.25        47.25   \n",
       "3  花見川区（報告数/定点数）            0            1       3.75         15.5   \n",
       "4   稲毛区（報告数/定点数）          0.2          2.8       12.8         21.4   \n",
       "\n",
       "    Unnamed: 5 Unnamed: 6   Unnamed: 7   Unnamed: 8   Unnamed: 9     ...      \\\n",
       "0          第5週        第6週          第7週          第8週          第9週     ...       \n",
       "1  31.32142857      33.25  26.21428571  25.53571429  30.60714286     ...       \n",
       "2           63         54           34        35.25         44.5     ...       \n",
       "3        17.25      20.25           17         16.5           17     ...       \n",
       "4         27.8       37.4         29.2         24.8         25.2     ...       \n",
       "\n",
       "   Unnamed: 43  Unnamed: 44  Unnamed: 45  Unnamed: 46  Unnamed: 47  \\\n",
       "0         第43週         第44週         第45週         第46週         第47週   \n",
       "1  0.285714286  0.571428571  0.571428571  1.107142857  3.111111111   \n",
       "2            0            0            0          0.6          2.5   \n",
       "3            0          0.5         0.75         1.25          1.5   \n",
       "4            0            0            0          0.8          0.4   \n",
       "\n",
       "   Unnamed: 48  Unnamed: 49 Unnamed: 50  Unnamed: 51 Unnamed: 52  \n",
       "0         第48週         第49週        第50週         第51週        第52週  \n",
       "1  5.357142857  7.964285714       12.75  20.21428571       31.08  \n",
       "2            7          7.8          15         27.6        40.4  \n",
       "3          2.5         3.75        4.75            7        14.5  \n",
       "4          1.8          3.8         7.4         17.2        21.2  \n",
       "\n",
       "[5 rows x 53 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2014.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_2014 = pd.DataFrame(df_2014.iloc[1, 1:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_2014.columns = ['報告数']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>インフルエンザ</th>\n",
       "      <td>0.178571429</td>\n",
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      "text/plain": [
       "                    報告数\n",
       "インフルエンザ     0.178571429\n",
       "Unnamed: 2  2.814814815\n",
       "Unnamed: 3         9.75\n",
       "Unnamed: 4  25.32142857\n",
       "Unnamed: 5  31.32142857"
      ]
     },
     "execution_count": 30,
     "metadata": {},
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    }
   ],
   "source": [
    "df_2014.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "                     報告数\n",
       "Unnamed: 48  5.357142857\n",
       "Unnamed: 49  7.964285714\n",
       "Unnamed: 50        12.75\n",
       "Unnamed: 51  20.21428571\n",
       "Unnamed: 52        31.08"
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     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "df_2014.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "date_index = pd.date_range(start=\"2013-12-30\", periods=52, freq=\"W-MON\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2013-12-30', '2014-01-06', '2014-01-13', '2014-01-20',\n",
       "               '2014-01-27', '2014-02-03', '2014-02-10', '2014-02-17',\n",
       "               '2014-02-24', '2014-03-03', '2014-03-10', '2014-03-17',\n",
       "               '2014-03-24', '2014-03-31', '2014-04-07', '2014-04-14',\n",
       "               '2014-04-21', '2014-04-28', '2014-05-05', '2014-05-12',\n",
       "               '2014-05-19', '2014-05-26', '2014-06-02', '2014-06-09',\n",
       "               '2014-06-16', '2014-06-23', '2014-06-30', '2014-07-07',\n",
       "               '2014-07-14', '2014-07-21', '2014-07-28', '2014-08-04',\n",
       "               '2014-08-11', '2014-08-18', '2014-08-25', '2014-09-01',\n",
       "               '2014-09-08', '2014-09-15', '2014-09-22', '2014-09-29',\n",
       "               '2014-10-06', '2014-10-13', '2014-10-20', '2014-10-27',\n",
       "               '2014-11-03', '2014-11-10', '2014-11-17', '2014-11-24',\n",
       "               '2014-12-01', '2014-12-08', '2014-12-15', '2014-12-22'],\n",
       "              dtype='datetime64[ns]', freq='W-MON')"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date_index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_2014.index = date_index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <th>2013-12-30</th>\n",
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       "      <th>2014-01-06</th>\n",
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       "    <tr>\n",
       "      <th>2014-01-13</th>\n",
       "      <td>9.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-20</th>\n",
       "      <td>25.32142857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-27</th>\n",
       "      <td>31.32142857</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    報告数\n",
       "2013-12-30  0.178571429\n",
       "2014-01-06  2.814814815\n",
       "2014-01-13         9.75\n",
       "2014-01-20  25.32142857\n",
       "2014-01-27  31.32142857"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2014.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
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       "      <th>報告数</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2014-11-24</th>\n",
       "      <td>5.357142857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-01</th>\n",
       "      <td>7.964285714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-08</th>\n",
       "      <td>12.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-15</th>\n",
       "      <td>20.21428571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-22</th>\n",
       "      <td>31.08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    報告数\n",
       "2014-11-24  5.357142857\n",
       "2014-12-01  7.964285714\n",
       "2014-12-08        12.75\n",
       "2014-12-15  20.21428571\n",
       "2014-12-22        31.08"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2014.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_2015 = pd.read_csv(\"data/201512influenza.csv\", encoding=\"shift_jis\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2014-12-29</th>\n",
       "      <td>4.038461538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-01-05</th>\n",
       "      <td>25.77777778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-01-12</th>\n",
       "      <td>27.92857143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-01-19</th>\n",
       "      <td>31.71428571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-01-26</th>\n",
       "      <td>27.21428571</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    報告数\n",
       "2014-12-29  4.038461538\n",
       "2015-01-05  25.77777778\n",
       "2015-01-12  27.92857143\n",
       "2015-01-19  31.71428571\n",
       "2015-01-26  27.21428571"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2015 = pd.DataFrame(df_2015.iloc[1, 1:])\n",
    "df_2015.columns = [\"報告数\"]\n",
    "date_index_2015 = pd.date_range(start=\"2014-12-29\", periods=53, freq=\"W-MON\")\n",
    "df_2015.index =date_index_2015\n",
    "df_2015.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
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       "      <th>報告数</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2015-11-30</th>\n",
       "      <td>0.071428571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-07</th>\n",
       "      <td>0.107142857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-14</th>\n",
       "      <td>0.071428571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-21</th>\n",
       "      <td>0.148148148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-28</th>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    報告数\n",
       "2015-11-30  0.071428571\n",
       "2015-12-07  0.107142857\n",
       "2015-12-14  0.071428571\n",
       "2015-12-21  0.148148148\n",
       "2015-12-28            0"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2015.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_2016 = pd.read_csv(\"data/201612influenza.csv\", encoding='shift_jis')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>報告数</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-01-04</th>\n",
       "      <td>1.444444444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-11</th>\n",
       "      <td>5.857142857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-18</th>\n",
       "      <td>15.67857143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-25</th>\n",
       "      <td>30.17857143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-02-01</th>\n",
       "      <td>46.21428571</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    報告数\n",
       "2016-01-04  1.444444444\n",
       "2016-01-11  5.857142857\n",
       "2016-01-18  15.67857143\n",
       "2016-01-25  30.17857143\n",
       "2016-02-01  46.21428571"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2016 = pd.DataFrame(df_2016.iloc[1, 1:])\n",
    "df_2016.columns = [\"報告数\"]\n",
    "date_index_2016 = pd.date_range(start=\"2016-1-4\", periods=53, freq=\"W-MON\")\n",
    "df_2016.index =date_index_2016\n",
    "df_2016.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>報告数</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-12-05</th>\n",
       "      <td>3.857142857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-12</th>\n",
       "      <td>4.178571429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-19</th>\n",
       "      <td>6.892857143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-26</th>\n",
       "      <td>4.434782609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-02</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    報告数\n",
       "2016-12-05  3.857142857\n",
       "2016-12-12  4.178571429\n",
       "2016-12-19  6.892857143\n",
       "2016-12-26  4.434782609\n",
       "2017-01-02          NaN"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2016.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 取り込めたデータを再確認\n",
    "\n",
    "いずれも、千葉市の\n",
    "\n",
    "- df_weather:  ２０１４年１月２０１７年４月までの気象データフレーム\n",
    "- ser_2014:  ２０１４年１月から２０１４年１２月までのインフルエンザの報告件数シリーズ\n",
    "- ser_2015:  ２０１5年１月から２０１5年１２月までのインフルエンザの報告件数データ\n",
    "- ser_2016:  ２０１6年１月から２０１6年１２月までのインフルエンザの報告件数データ"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>平均気温(℃)</th>\n",
       "      <th>最高気温(℃)</th>\n",
       "      <th>最低気温(℃)</th>\n",
       "      <th>平均湿度(％)</th>\n",
       "      <th>最小相対湿度(％)</th>\n",
       "      <th>平均現地気圧(hPa)</th>\n",
       "      <th>降水量の合計(mm)</th>\n",
       "      <th>日照時間(時間)</th>\n",
       "      <th>平均風速(m/s)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>年月日</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2014-01-01</th>\n",
       "      <td>9.8</td>\n",
       "      <td>13.7</td>\n",
       "      <td>3.9</td>\n",
       "      <td>54.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>1005.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.2</td>\n",
       "      <td>5.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-02</th>\n",
       "      <td>8.0</td>\n",
       "      <td>12.9</td>\n",
       "      <td>4.4</td>\n",
       "      <td>41.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1011.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.1</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-03</th>\n",
       "      <td>5.9</td>\n",
       "      <td>9.9</td>\n",
       "      <td>2.7</td>\n",
       "      <td>43.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1014.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>1.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-04</th>\n",
       "      <td>6.7</td>\n",
       "      <td>11.5</td>\n",
       "      <td>2.1</td>\n",
       "      <td>47.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>1009.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.9</td>\n",
       "      <td>2.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-05</th>\n",
       "      <td>4.4</td>\n",
       "      <td>6.9</td>\n",
       "      <td>2.3</td>\n",
       "      <td>40.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>1016.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.1</td>\n",
       "      <td>2.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            平均気温(℃)  最高気温(℃)  最低気温(℃)  平均湿度(％)  最小相対湿度(％)  平均現地気圧(hPa)  \\\n",
       "年月日                                                                      \n",
       "2014-01-01      9.8     13.7      3.9     54.0       37.0       1005.3   \n",
       "2014-01-02      8.0     12.9      4.4     41.0       26.0       1011.3   \n",
       "2014-01-03      5.9      9.9      2.7     43.0       32.0       1014.9   \n",
       "2014-01-04      6.7     11.5      2.1     47.0       29.0       1009.5   \n",
       "2014-01-05      4.4      6.9      2.3     40.0       28.0       1016.6   \n",
       "\n",
       "            降水量の合計(mm)  日照時間(時間)  平均風速(m/s)  \n",
       "年月日                                          \n",
       "2014-01-01         0.0       9.2        5.3  \n",
       "2014-01-02         0.0       9.1        3.0  \n",
       "2014-01-03         0.0       4.1        1.6  \n",
       "2014-01-04         0.0       5.9        2.4  \n",
       "2014-01-05         0.0       1.1        2.5  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_weather.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>報告数</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-12-30</th>\n",
       "      <td>0.178571429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-06</th>\n",
       "      <td>2.814814815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-13</th>\n",
       "      <td>9.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-20</th>\n",
       "      <td>25.32142857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-27</th>\n",
       "      <td>31.32142857</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    報告数\n",
       "2013-12-30  0.178571429\n",
       "2014-01-06  2.814814815\n",
       "2014-01-13         9.75\n",
       "2014-01-20  25.32142857\n",
       "2014-01-27  31.32142857"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2014.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>報告数</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2014-12-29</th>\n",
       "      <td>4.038461538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-01-05</th>\n",
       "      <td>25.77777778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-01-12</th>\n",
       "      <td>27.92857143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-01-19</th>\n",
       "      <td>31.71428571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-01-26</th>\n",
       "      <td>27.21428571</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    報告数\n",
       "2014-12-29  4.038461538\n",
       "2015-01-05  25.77777778\n",
       "2015-01-12  27.92857143\n",
       "2015-01-19  31.71428571\n",
       "2015-01-26  27.21428571"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2015.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>報告数</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-01-04</th>\n",
       "      <td>1.444444444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-11</th>\n",
       "      <td>5.857142857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-18</th>\n",
       "      <td>15.67857143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-25</th>\n",
       "      <td>30.17857143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-02-01</th>\n",
       "      <td>46.21428571</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    報告数\n",
       "2016-01-04  1.444444444\n",
       "2016-01-11  5.857142857\n",
       "2016-01-18  15.67857143\n",
       "2016-01-25  30.17857143\n",
       "2016-02-01  46.21428571"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2016.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# データの結合と欠損値の処理\n",
    "\n",
    "上記のデータを一つのデータフレームにまとめていきます。\n",
    "必要に応じて欠損値も処理していきます。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## インフルエンザの報告件数を3年分まとめる"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_influ = pd.concat([df_2014, df_2015, df_2016])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(158, 1)"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_influ.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>報告数</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-12-30</th>\n",
       "      <td>0.178571429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-06</th>\n",
       "      <td>2.814814815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-13</th>\n",
       "      <td>9.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-20</th>\n",
       "      <td>25.32142857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-27</th>\n",
       "      <td>31.32142857</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    報告数\n",
       "2013-12-30  0.178571429\n",
       "2014-01-06  2.814814815\n",
       "2014-01-13         9.75\n",
       "2014-01-20  25.32142857\n",
       "2014-01-27  31.32142857"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_influ.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>報告数</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-12-05</th>\n",
       "      <td>3.857142857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-12</th>\n",
       "      <td>4.178571429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-19</th>\n",
       "      <td>6.892857143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-26</th>\n",
       "      <td>4.434782609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-02</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    報告数\n",
       "2016-12-05  3.857142857\n",
       "2016-12-12  4.178571429\n",
       "2016-12-19  6.892857143\n",
       "2016-12-26  4.434782609\n",
       "2017-01-02          NaN"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_influ.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_influ = df_influ.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(157, 1)"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_influ.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_infｌu = pd.DataFrame(df_influ.astype(np.float32))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>報告数</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-12-30</th>\n",
       "      <td>0.178571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-06</th>\n",
       "      <td>2.814815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-13</th>\n",
       "      <td>9.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-20</th>\n",
       "      <td>25.321428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-27</th>\n",
       "      <td>31.321428</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  報告数\n",
       "2013-12-30   0.178571\n",
       "2014-01-06   2.814815\n",
       "2014-01-13   9.750000\n",
       "2014-01-20  25.321428\n",
       "2014-01-27  31.321428"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_influ.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "報告数    float32\n",
       "dtype: object"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_influ.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_influ.to_pickle(\"df_influ.db\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 気象データとつなげる"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = pd.concat([df_influ, df_weather], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1217, 10)"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>報告数</th>\n",
       "      <th>平均気温(℃)</th>\n",
       "      <th>最高気温(℃)</th>\n",
       "      <th>最低気温(℃)</th>\n",
       "      <th>平均湿度(％)</th>\n",
       "      <th>最小相対湿度(％)</th>\n",
       "      <th>平均現地気圧(hPa)</th>\n",
       "      <th>降水量の合計(mm)</th>\n",
       "      <th>日照時間(時間)</th>\n",
       "      <th>平均風速(m/s)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-12-30</th>\n",
       "      <td>0.178571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-01</th>\n",
       "      <td>NaN</td>\n",
       "      <td>9.8</td>\n",
       "      <td>13.7</td>\n",
       "      <td>3.9</td>\n",
       "      <td>54.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>1005.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.2</td>\n",
       "      <td>5.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-02</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>12.9</td>\n",
       "      <td>4.4</td>\n",
       "      <td>41.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1011.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.1</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-03</th>\n",
       "      <td>NaN</td>\n",
       "      <td>5.9</td>\n",
       "      <td>9.9</td>\n",
       "      <td>2.7</td>\n",
       "      <td>43.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1014.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>1.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-04</th>\n",
       "      <td>NaN</td>\n",
       "      <td>6.7</td>\n",
       "      <td>11.5</td>\n",
       "      <td>2.1</td>\n",
       "      <td>47.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>1009.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.9</td>\n",
       "      <td>2.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 報告数  平均気温(℃)  最高気温(℃)  最低気温(℃)  平均湿度(％)  最小相対湿度(％)  \\\n",
       "2013-12-30  0.178571      NaN      NaN      NaN      NaN        NaN   \n",
       "2014-01-01       NaN      9.8     13.7      3.9     54.0       37.0   \n",
       "2014-01-02       NaN      8.0     12.9      4.4     41.0       26.0   \n",
       "2014-01-03       NaN      5.9      9.9      2.7     43.0       32.0   \n",
       "2014-01-04       NaN      6.7     11.5      2.1     47.0       29.0   \n",
       "\n",
       "            平均現地気圧(hPa)  降水量の合計(mm)  日照時間(時間)  平均風速(m/s)  \n",
       "2013-12-30          NaN         NaN       NaN        NaN  \n",
       "2014-01-01       1005.3         0.0       9.2        5.3  \n",
       "2014-01-02       1011.3         0.0       9.1        3.0  \n",
       "2014-01-03       1014.9         0.0       4.1        1.6  \n",
       "2014-01-04       1009.5         0.0       5.9        2.4  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>報告数</th>\n",
       "      <th>平均気温(℃)</th>\n",
       "      <th>最高気温(℃)</th>\n",
       "      <th>最低気温(℃)</th>\n",
       "      <th>平均湿度(％)</th>\n",
       "      <th>最小相対湿度(％)</th>\n",
       "      <th>平均現地気圧(hPa)</th>\n",
       "      <th>降水量の合計(mm)</th>\n",
       "      <th>日照時間(時間)</th>\n",
       "      <th>平均風速(m/s)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-03-22</th>\n",
       "      <td>NaN</td>\n",
       "      <td>10.5</td>\n",
       "      <td>15.0</td>\n",
       "      <td>6.6</td>\n",
       "      <td>35.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1010.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.7</td>\n",
       "      <td>5.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-23</th>\n",
       "      <td>NaN</td>\n",
       "      <td>10.0</td>\n",
       "      <td>14.1</td>\n",
       "      <td>6.5</td>\n",
       "      <td>38.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1015.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.8</td>\n",
       "      <td>2.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-24</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.7</td>\n",
       "      <td>13.8</td>\n",
       "      <td>5.6</td>\n",
       "      <td>38.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>1015.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-25</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.5</td>\n",
       "      <td>12.3</td>\n",
       "      <td>3.7</td>\n",
       "      <td>38.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>1019.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.4</td>\n",
       "      <td>3.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-26</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.5</td>\n",
       "      <td>9.6</td>\n",
       "      <td>5.9</td>\n",
       "      <td>81.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>1016.9</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-27</th>\n",
       "      <td>NaN</td>\n",
       "      <td>5.1</td>\n",
       "      <td>7.1</td>\n",
       "      <td>2.3</td>\n",
       "      <td>84.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>1008.8</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>4.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-28</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.3</td>\n",
       "      <td>13.7</td>\n",
       "      <td>3.8</td>\n",
       "      <td>61.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1017.9</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.1</td>\n",
       "      <td>3.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-29</th>\n",
       "      <td>NaN</td>\n",
       "      <td>9.4</td>\n",
       "      <td>14.1</td>\n",
       "      <td>5.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>1021.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.8</td>\n",
       "      <td>2.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-30</th>\n",
       "      <td>NaN</td>\n",
       "      <td>11.9</td>\n",
       "      <td>16.0</td>\n",
       "      <td>6.4</td>\n",
       "      <td>63.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>1017.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.6</td>\n",
       "      <td>2.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31</th>\n",
       "      <td>NaN</td>\n",
       "      <td>9.1</td>\n",
       "      <td>13.1</td>\n",
       "      <td>5.8</td>\n",
       "      <td>57.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>1016.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-01</th>\n",
       "      <td>NaN</td>\n",
       "      <td>6.5</td>\n",
       "      <td>8.3</td>\n",
       "      <td>4.9</td>\n",
       "      <td>76.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>1012.8</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-02</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.4</td>\n",
       "      <td>13.3</td>\n",
       "      <td>4.7</td>\n",
       "      <td>56.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1013.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.3</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-03</th>\n",
       "      <td>NaN</td>\n",
       "      <td>9.7</td>\n",
       "      <td>15.4</td>\n",
       "      <td>6.3</td>\n",
       "      <td>62.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>1015.7</td>\n",
       "      <td>1.5</td>\n",
       "      <td>6.9</td>\n",
       "      <td>3.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-04</th>\n",
       "      <td>NaN</td>\n",
       "      <td>10.8</td>\n",
       "      <td>16.6</td>\n",
       "      <td>5.4</td>\n",
       "      <td>58.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1023.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.7</td>\n",
       "      <td>3.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-05</th>\n",
       "      <td>NaN</td>\n",
       "      <td>14.7</td>\n",
       "      <td>17.7</td>\n",
       "      <td>10.9</td>\n",
       "      <td>59.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>1026.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.7</td>\n",
       "      <td>5.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-06</th>\n",
       "      <td>NaN</td>\n",
       "      <td>16.9</td>\n",
       "      <td>20.6</td>\n",
       "      <td>13.6</td>\n",
       "      <td>63.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1022.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.8</td>\n",
       "      <td>7.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-07</th>\n",
       "      <td>NaN</td>\n",
       "      <td>17.6</td>\n",
       "      <td>19.4</td>\n",
       "      <td>16.7</td>\n",
       "      <td>80.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>1015.7</td>\n",
       "      <td>1.5</td>\n",
       "      <td>1.6</td>\n",
       "      <td>8.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-08</th>\n",
       "      <td>NaN</td>\n",
       "      <td>16.3</td>\n",
       "      <td>19.0</td>\n",
       "      <td>13.4</td>\n",
       "      <td>93.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>1011.8</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-09</th>\n",
       "      <td>NaN</td>\n",
       "      <td>14.5</td>\n",
       "      <td>17.7</td>\n",
       "      <td>10.8</td>\n",
       "      <td>91.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>1007.1</td>\n",
       "      <td>11.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-10</th>\n",
       "      <td>NaN</td>\n",
       "      <td>10.8</td>\n",
       "      <td>15.0</td>\n",
       "      <td>7.5</td>\n",
       "      <td>43.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>1019.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.3</td>\n",
       "      <td>3.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-11</th>\n",
       "      <td>NaN</td>\n",
       "      <td>10.6</td>\n",
       "      <td>13.6</td>\n",
       "      <td>8.2</td>\n",
       "      <td>85.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>1005.7</td>\n",
       "      <td>40.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-12</th>\n",
       "      <td>NaN</td>\n",
       "      <td>15.4</td>\n",
       "      <td>21.9</td>\n",
       "      <td>9.7</td>\n",
       "      <td>54.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>1001.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.2</td>\n",
       "      <td>3.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-13</th>\n",
       "      <td>NaN</td>\n",
       "      <td>12.4</td>\n",
       "      <td>17.1</td>\n",
       "      <td>7.6</td>\n",
       "      <td>51.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>1013.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.9</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-14</th>\n",
       "      <td>NaN</td>\n",
       "      <td>15.0</td>\n",
       "      <td>20.9</td>\n",
       "      <td>8.6</td>\n",
       "      <td>47.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1016.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.7</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-15</th>\n",
       "      <td>NaN</td>\n",
       "      <td>18.2</td>\n",
       "      <td>21.5</td>\n",
       "      <td>16.5</td>\n",
       "      <td>60.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>1013.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-16</th>\n",
       "      <td>NaN</td>\n",
       "      <td>19.0</td>\n",
       "      <td>23.4</td>\n",
       "      <td>14.1</td>\n",
       "      <td>56.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1013.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.5</td>\n",
       "      <td>3.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-17</th>\n",
       "      <td>NaN</td>\n",
       "      <td>18.7</td>\n",
       "      <td>25.1</td>\n",
       "      <td>15.6</td>\n",
       "      <td>68.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1012.1</td>\n",
       "      <td>14.5</td>\n",
       "      <td>4.1</td>\n",
       "      <td>4.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-18</th>\n",
       "      <td>NaN</td>\n",
       "      <td>20.1</td>\n",
       "      <td>25.9</td>\n",
       "      <td>15.9</td>\n",
       "      <td>70.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>992.6</td>\n",
       "      <td>20.5</td>\n",
       "      <td>3.8</td>\n",
       "      <td>8.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-19</th>\n",
       "      <td>NaN</td>\n",
       "      <td>17.6</td>\n",
       "      <td>23.8</td>\n",
       "      <td>13.7</td>\n",
       "      <td>48.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>998.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.5</td>\n",
       "      <td>6.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-20</th>\n",
       "      <td>NaN</td>\n",
       "      <td>15.3</td>\n",
       "      <td>19.7</td>\n",
       "      <td>11.8</td>\n",
       "      <td>45.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>1011.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.7</td>\n",
       "      <td>4.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-21</th>\n",
       "      <td>NaN</td>\n",
       "      <td>15.5</td>\n",
       "      <td>17.7</td>\n",
       "      <td>13.8</td>\n",
       "      <td>71.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>1007.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>2.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-22</th>\n",
       "      <td>NaN</td>\n",
       "      <td>14.9</td>\n",
       "      <td>18.7</td>\n",
       "      <td>11.3</td>\n",
       "      <td>69.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>1007.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>2.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-23</th>\n",
       "      <td>NaN</td>\n",
       "      <td>13.5</td>\n",
       "      <td>19.3</td>\n",
       "      <td>10.4</td>\n",
       "      <td>51.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1016.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.3</td>\n",
       "      <td>3.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-24</th>\n",
       "      <td>NaN</td>\n",
       "      <td>14.1</td>\n",
       "      <td>17.5</td>\n",
       "      <td>11.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>1026.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.7</td>\n",
       "      <td>3.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-25</th>\n",
       "      <td>NaN</td>\n",
       "      <td>15.7</td>\n",
       "      <td>20.4</td>\n",
       "      <td>11.4</td>\n",
       "      <td>57.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>1025.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.7</td>\n",
       "      <td>4.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-26</th>\n",
       "      <td>NaN</td>\n",
       "      <td>17.0</td>\n",
       "      <td>19.7</td>\n",
       "      <td>14.2</td>\n",
       "      <td>69.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>1014.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>6.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-27</th>\n",
       "      <td>NaN</td>\n",
       "      <td>14.7</td>\n",
       "      <td>17.6</td>\n",
       "      <td>11.6</td>\n",
       "      <td>69.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>1004.9</td>\n",
       "      <td>6.5</td>\n",
       "      <td>2.6</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-28</th>\n",
       "      <td>NaN</td>\n",
       "      <td>16.0</td>\n",
       "      <td>20.1</td>\n",
       "      <td>12.7</td>\n",
       "      <td>62.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1006.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.4</td>\n",
       "      <td>2.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-29</th>\n",
       "      <td>NaN</td>\n",
       "      <td>16.3</td>\n",
       "      <td>21.9</td>\n",
       "      <td>11.8</td>\n",
       "      <td>64.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>1005.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.1</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-30</th>\n",
       "      <td>NaN</td>\n",
       "      <td>18.0</td>\n",
       "      <td>23.2</td>\n",
       "      <td>12.1</td>\n",
       "      <td>57.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>1009.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.6</td>\n",
       "      <td>3.7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            報告数  平均気温(℃)  最高気温(℃)  最低気温(℃)  平均湿度(％)  最小相対湿度(％)  平均現地気圧(hPa)  \\\n",
       "2017-03-22  NaN     10.5     15.0      6.6     35.0       19.0       1010.8   \n",
       "2017-03-23  NaN     10.0     14.1      6.5     38.0       25.0       1015.2   \n",
       "2017-03-24  NaN      8.7     13.8      5.6     38.0       15.0       1015.3   \n",
       "2017-03-25  NaN      7.5     12.3      3.7     38.0       23.0       1019.8   \n",
       "2017-03-26  NaN      7.5      9.6      5.9     81.0       50.0       1016.9   \n",
       "2017-03-27  NaN      5.1      7.1      2.3     84.0       70.0       1008.8   \n",
       "2017-03-28  NaN      8.3     13.7      3.8     61.0       25.0       1017.9   \n",
       "2017-03-29  NaN      9.4     14.1      5.0     65.0       41.0       1021.6   \n",
       "2017-03-30  NaN     11.9     16.0      6.4     63.0       40.0       1017.2   \n",
       "2017-03-31  NaN      9.1     13.1      5.8     57.0       34.0       1016.5   \n",
       "2017-04-01  NaN      6.5      8.3      4.9     76.0       54.0       1012.8   \n",
       "2017-04-02  NaN      8.4     13.3      4.7     56.0       32.0       1013.3   \n",
       "2017-04-03  NaN      9.7     15.4      6.3     62.0       41.0       1015.7   \n",
       "2017-04-04  NaN     10.8     16.6      5.4     58.0       32.0       1023.7   \n",
       "2017-04-05  NaN     14.7     17.7     10.9     59.0       44.0       1026.0   \n",
       "2017-04-06  NaN     16.9     20.6     13.6     63.0       32.0       1022.5   \n",
       "2017-04-07  NaN     17.6     19.4     16.7     80.0       66.0       1015.7   \n",
       "2017-04-08  NaN     16.3     19.0     13.4     93.0       88.0       1011.8   \n",
       "2017-04-09  NaN     14.5     17.7     10.8     91.0       65.0       1007.1   \n",
       "2017-04-10  NaN     10.8     15.0      7.5     43.0       24.0       1019.6   \n",
       "2017-04-11  NaN     10.6     13.6      8.2     85.0       59.0       1005.7   \n",
       "2017-04-12  NaN     15.4     21.9      9.7     54.0       23.0       1001.4   \n",
       "2017-04-13  NaN     12.4     17.1      7.6     51.0       36.0       1013.1   \n",
       "2017-04-14  NaN     15.0     20.9      8.6     47.0       30.0       1016.2   \n",
       "2017-04-15  NaN     18.2     21.5     16.5     60.0       50.0       1013.0   \n",
       "2017-04-16  NaN     19.0     23.4     14.1     56.0       26.0       1013.1   \n",
       "2017-04-17  NaN     18.7     25.1     15.6     68.0       25.0       1012.1   \n",
       "2017-04-18  NaN     20.1     25.9     15.9     70.0       45.0        992.6   \n",
       "2017-04-19  NaN     17.6     23.8     13.7     48.0       16.0        998.4   \n",
       "2017-04-20  NaN     15.3     19.7     11.8     45.0       28.0       1011.3   \n",
       "2017-04-21  NaN     15.5     17.7     13.8     71.0       50.0       1007.2   \n",
       "2017-04-22  NaN     14.9     18.7     11.3     69.0       43.0       1007.0   \n",
       "2017-04-23  NaN     13.5     19.3     10.4     51.0       26.0       1016.6   \n",
       "2017-04-24  NaN     14.1     17.5     11.0     56.0       46.0       1026.2   \n",
       "2017-04-25  NaN     15.7     20.4     11.4     57.0       36.0       1025.3   \n",
       "2017-04-26  NaN     17.0     19.7     14.2     69.0       53.0       1014.3   \n",
       "2017-04-27  NaN     14.7     17.6     11.6     69.0       45.0       1004.9   \n",
       "2017-04-28  NaN     16.0     20.1     12.7     62.0       31.0       1006.2   \n",
       "2017-04-29  NaN     16.3     21.9     11.8     64.0       34.0       1005.7   \n",
       "2017-04-30  NaN     18.0     23.2     12.1     57.0       31.0       1009.2   \n",
       "\n",
       "            降水量の合計(mm)  日照時間(時間)  平均風速(m/s)  \n",
       "2017-03-22         0.0       9.7        5.5  \n",
       "2017-03-23         0.0       5.8        2.3  \n",
       "2017-03-24         0.0       4.1        4.0  \n",
       "2017-03-25         0.0      10.4        3.2  \n",
       "2017-03-26         7.0       0.1        3.0  \n",
       "2017-03-27        30.0       0.6        4.9  \n",
       "2017-03-28         1.0       9.1        3.4  \n",
       "2017-03-29         0.0       6.8        2.7  \n",
       "2017-03-30         0.0       9.6        2.6  \n",
       "2017-03-31         5.0       1.8        3.0  \n",
       "2017-04-01         7.0       0.0        3.7  \n",
       "2017-04-02         0.0      10.3        3.0  \n",
       "2017-04-03         1.5       6.9        3.2  \n",
       "2017-04-04         0.0      11.7        3.2  \n",
       "2017-04-05         0.0       9.7        5.1  \n",
       "2017-04-06         0.0       5.8        7.2  \n",
       "2017-04-07         1.5       1.6        8.7  \n",
       "2017-04-08        17.0       0.0        5.2  \n",
       "2017-04-09        11.5       0.0        4.2  \n",
       "2017-04-10         0.0       6.3        3.8  \n",
       "2017-04-11        40.5       0.0        4.0  \n",
       "2017-04-12         0.0       9.2        3.8  \n",
       "2017-04-13         0.0       8.9        3.5  \n",
       "2017-04-14         0.0      11.7        4.5  \n",
       "2017-04-15         0.0       8.0        8.6  \n",
       "2017-04-16         0.0      10.5        3.7  \n",
       "2017-04-17        14.5       4.1        4.7  \n",
       "2017-04-18        20.5       3.8        8.1  \n",
       "2017-04-19         0.0      10.5        6.5  \n",
       "2017-04-20         0.0       9.7        4.1  \n",
       "2017-04-21         0.0       0.1        2.3  \n",
       "2017-04-22         2.5       0.5        2.9  \n",
       "2017-04-23         0.0      11.3        3.2  \n",
       "2017-04-24         0.0       5.7        3.2  \n",
       "2017-04-25         0.0      10.7        4.8  \n",
       "2017-04-26         0.0       0.2        6.5  \n",
       "2017-04-27         6.5       2.6        4.5  \n",
       "2017-04-28         0.0       7.4        2.7  \n",
       "2017-04-29         0.0      12.1        3.5  \n",
       "2017-04-30         0.0      12.6        3.7  "
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail(40)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 欠損値の処理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = df.loc[\"2014-01-01\":\"2016-12-31\", :]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1096, 10)"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>報告数</th>\n",
       "      <th>平均気温(℃)</th>\n",
       "      <th>最高気温(℃)</th>\n",
       "      <th>最低気温(℃)</th>\n",
       "      <th>平均湿度(％)</th>\n",
       "      <th>最小相対湿度(％)</th>\n",
       "      <th>平均現地気圧(hPa)</th>\n",
       "      <th>降水量の合計(mm)</th>\n",
       "      <th>日照時間(時間)</th>\n",
       "      <th>平均風速(m/s)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2014-01-01</th>\n",
       "      <td>NaN</td>\n",
       "      <td>9.8</td>\n",
       "      <td>13.7</td>\n",
       "      <td>3.9</td>\n",
       "      <td>54.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>1005.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.2</td>\n",
       "      <td>5.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-02</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>12.9</td>\n",
       "      <td>4.4</td>\n",
       "      <td>41.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1011.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.1</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-03</th>\n",
       "      <td>NaN</td>\n",
       "      <td>5.9</td>\n",
       "      <td>9.9</td>\n",
       "      <td>2.7</td>\n",
       "      <td>43.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1014.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>1.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-04</th>\n",
       "      <td>NaN</td>\n",
       "      <td>6.7</td>\n",
       "      <td>11.5</td>\n",
       "      <td>2.1</td>\n",
       "      <td>47.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>1009.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.9</td>\n",
       "      <td>2.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-05</th>\n",
       "      <td>NaN</td>\n",
       "      <td>4.4</td>\n",
       "      <td>6.9</td>\n",
       "      <td>2.3</td>\n",
       "      <td>40.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>1016.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.1</td>\n",
       "      <td>2.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-06</th>\n",
       "      <td>2.814815</td>\n",
       "      <td>4.9</td>\n",
       "      <td>10.4</td>\n",
       "      <td>0.8</td>\n",
       "      <td>36.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1021.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.4</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-07</th>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.7</td>\n",
       "      <td>0.2</td>\n",
       "      <td>46.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1025.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.5</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-08</th>\n",
       "      <td>NaN</td>\n",
       "      <td>7.8</td>\n",
       "      <td>13.6</td>\n",
       "      <td>2.5</td>\n",
       "      <td>66.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>1014.4</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-09</th>\n",
       "      <td>NaN</td>\n",
       "      <td>6.5</td>\n",
       "      <td>9.7</td>\n",
       "      <td>3.1</td>\n",
       "      <td>77.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>1007.1</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>3.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-10</th>\n",
       "      <td>NaN</td>\n",
       "      <td>3.1</td>\n",
       "      <td>6.5</td>\n",
       "      <td>0.8</td>\n",
       "      <td>31.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>1019.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>3.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 報告数  平均気温(℃)  最高気温(℃)  最低気温(℃)  平均湿度(％)  最小相対湿度(％)  \\\n",
       "2014-01-01       NaN      9.8     13.7      3.9     54.0       37.0   \n",
       "2014-01-02       NaN      8.0     12.9      4.4     41.0       26.0   \n",
       "2014-01-03       NaN      5.9      9.9      2.7     43.0       32.0   \n",
       "2014-01-04       NaN      6.7     11.5      2.1     47.0       29.0   \n",
       "2014-01-05       NaN      4.4      6.9      2.3     40.0       28.0   \n",
       "2014-01-06  2.814815      4.9     10.4      0.8     36.0       19.0   \n",
       "2014-01-07       NaN      5.0      8.7      0.2     46.0       30.0   \n",
       "2014-01-08       NaN      7.8     13.6      2.5     66.0       39.0   \n",
       "2014-01-09       NaN      6.5      9.7      3.1     77.0       39.0   \n",
       "2014-01-10       NaN      3.1      6.5      0.8     31.0       17.0   \n",
       "\n",
       "            平均現地気圧(hPa)  降水量の合計(mm)  日照時間(時間)  平均風速(m/s)  \n",
       "2014-01-01       1005.3         0.0       9.2        5.3  \n",
       "2014-01-02       1011.3         0.0       9.1        3.0  \n",
       "2014-01-03       1014.9         0.0       4.1        1.6  \n",
       "2014-01-04       1009.5         0.0       5.9        2.4  \n",
       "2014-01-05       1016.6         0.0       1.1        2.5  \n",
       "2014-01-06       1021.4         0.0       9.4        4.5  \n",
       "2014-01-07       1025.4         0.0       6.5        2.0  \n",
       "2014-01-08       1014.4        18.0       2.5        2.5  \n",
       "2014-01-09       1007.1        10.0       0.6        3.1  \n",
       "2014-01-10       1019.9         0.0       3.3        3.6  "
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
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       "      <th>報告数</th>\n",
       "      <th>平均気温(℃)</th>\n",
       "      <th>最高気温(℃)</th>\n",
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       "      <th>日照時間(時間)</th>\n",
       "      <th>平均風速(m/s)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-12-27</th>\n",
       "      <td>NaN</td>\n",
       "      <td>13.0</td>\n",
       "      <td>19.2</td>\n",
       "      <td>5.3</td>\n",
       "      <td>81.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>1002.4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>7.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-28</th>\n",
       "      <td>NaN</td>\n",
       "      <td>6.8</td>\n",
       "      <td>10.2</td>\n",
       "      <td>3.8</td>\n",
       "      <td>40.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1018.4</td>\n",
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       "    <tr>\n",
       "      <th>2016-12-29</th>\n",
       "      <td>NaN</td>\n",
       "      <td>5.5</td>\n",
       "      <td>13.2</td>\n",
       "      <td>1.8</td>\n",
       "      <td>51.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>1017.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.3</td>\n",
       "      <td>2.3</td>\n",
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       "    <tr>\n",
       "      <th>2016-12-30</th>\n",
       "      <td>NaN</td>\n",
       "      <td>6.3</td>\n",
       "      <td>10.2</td>\n",
       "      <td>2.6</td>\n",
       "      <td>35.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1022.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.3</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>NaN</td>\n",
       "      <td>6.8</td>\n",
       "      <td>11.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>1023.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.2</td>\n",
       "      <td>1.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            報告数  平均気温(℃)  最高気温(℃)  最低気温(℃)  平均湿度(％)  最小相対湿度(％)  平均現地気圧(hPa)  \\\n",
       "2016-12-27  NaN     13.0     19.2      5.3     81.0       72.0       1002.4   \n",
       "2016-12-28  NaN      6.8     10.2      3.8     40.0       25.0       1018.4   \n",
       "2016-12-29  NaN      5.5     13.2      1.8     51.0       44.0       1017.0   \n",
       "2016-12-30  NaN      6.3     10.2      2.6     35.0       20.0       1022.0   \n",
       "2016-12-31  NaN      6.8     11.0      3.0     44.0       27.0       1023.1   \n",
       "\n",
       "            降水量の合計(mm)  日照時間(時間)  平均風速(m/s)  \n",
       "2016-12-27         5.0       0.1        7.3  \n",
       "2016-12-28         0.5       9.4        4.2  \n",
       "2016-12-29         0.0       5.3        2.3  \n",
       "2016-12-30         0.0       9.3        4.3  \n",
       "2016-12-31         0.0       9.2        1.6  "
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df[\"報告数\"] = df[\"報告数\"].fillna(method='ffill').astype(np.float32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>報告数</th>\n",
       "      <th>平均気温(℃)</th>\n",
       "      <th>最高気温(℃)</th>\n",
       "      <th>最低気温(℃)</th>\n",
       "      <th>平均湿度(％)</th>\n",
       "      <th>最小相対湿度(％)</th>\n",
       "      <th>平均現地気圧(hPa)</th>\n",
       "      <th>降水量の合計(mm)</th>\n",
       "      <th>日照時間(時間)</th>\n",
       "      <th>平均風速(m/s)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2014-01-01</th>\n",
       "      <td>NaN</td>\n",
       "      <td>9.8</td>\n",
       "      <td>13.7</td>\n",
       "      <td>3.9</td>\n",
       "      <td>54.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>1005.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.2</td>\n",
       "      <td>5.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-02</th>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>12.9</td>\n",
       "      <td>4.4</td>\n",
       "      <td>41.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1011.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.1</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-03</th>\n",
       "      <td>NaN</td>\n",
       "      <td>5.9</td>\n",
       "      <td>9.9</td>\n",
       "      <td>2.7</td>\n",
       "      <td>43.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1014.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.1</td>\n",
       "      <td>1.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-04</th>\n",
       "      <td>NaN</td>\n",
       "      <td>6.7</td>\n",
       "      <td>11.5</td>\n",
       "      <td>2.1</td>\n",
       "      <td>47.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>1009.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.9</td>\n",
       "      <td>2.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-05</th>\n",
       "      <td>NaN</td>\n",
       "      <td>4.4</td>\n",
       "      <td>6.9</td>\n",
       "      <td>2.3</td>\n",
       "      <td>40.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>1016.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.1</td>\n",
       "      <td>2.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-06</th>\n",
       "      <td>2.814815</td>\n",
       "      <td>4.9</td>\n",
       "      <td>10.4</td>\n",
       "      <td>0.8</td>\n",
       "      <td>36.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1021.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.4</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-07</th>\n",
       "      <td>2.814815</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.7</td>\n",
       "      <td>0.2</td>\n",
       "      <td>46.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>1025.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.5</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-08</th>\n",
       "      <td>2.814815</td>\n",
       "      <td>7.8</td>\n",
       "      <td>13.6</td>\n",
       "      <td>2.5</td>\n",
       "      <td>66.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>1014.4</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-09</th>\n",
       "      <td>2.814815</td>\n",
       "      <td>6.5</td>\n",
       "      <td>9.7</td>\n",
       "      <td>3.1</td>\n",
       "      <td>77.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>1007.1</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>3.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-01-10</th>\n",
       "      <td>2.814815</td>\n",
       "      <td>3.1</td>\n",
       "      <td>6.5</td>\n",
       "      <td>0.8</td>\n",
       "      <td>31.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>1019.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.3</td>\n",
       "      <td>3.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 報告数  平均気温(℃)  最高気温(℃)  最低気温(℃)  平均湿度(％)  最小相対湿度(％)  \\\n",
       "2014-01-01       NaN      9.8     13.7      3.9     54.0       37.0   \n",
       "2014-01-02       NaN      8.0     12.9      4.4     41.0       26.0   \n",
       "2014-01-03       NaN      5.9      9.9      2.7     43.0       32.0   \n",
       "2014-01-04       NaN      6.7     11.5      2.1     47.0       29.0   \n",
       "2014-01-05       NaN      4.4      6.9      2.3     40.0       28.0   \n",
       "2014-01-06  2.814815      4.9     10.4      0.8     36.0       19.0   \n",
       "2014-01-07  2.814815      5.0      8.7      0.2     46.0       30.0   \n",
       "2014-01-08  2.814815      7.8     13.6      2.5     66.0       39.0   \n",
       "2014-01-09  2.814815      6.5      9.7      3.1     77.0       39.0   \n",
       "2014-01-10  2.814815      3.1      6.5      0.8     31.0       17.0   \n",
       "\n",
       "            平均現地気圧(hPa)  降水量の合計(mm)  日照時間(時間)  平均風速(m/s)  \n",
       "2014-01-01       1005.3         0.0       9.2        5.3  \n",
       "2014-01-02       1011.3         0.0       9.1        3.0  \n",
       "2014-01-03       1014.9         0.0       4.1        1.6  \n",
       "2014-01-04       1009.5         0.0       5.9        2.4  \n",
       "2014-01-05       1016.6         0.0       1.1        2.5  \n",
       "2014-01-06       1021.4         0.0       9.4        4.5  \n",
       "2014-01-07       1025.4         0.0       6.5        2.0  \n",
       "2014-01-08       1014.4        18.0       2.5        2.5  \n",
       "2014-01-09       1007.1        10.0       0.6        3.1  \n",
       "2014-01-10       1019.9         0.0       3.3        3.6  "
      ]
     },
     "execution_count": 66,
     "metadata": {},
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   "source": [
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  {
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   "execution_count": 67,
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   "outputs": [
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       "      <td>5.3</td>\n",
       "      <td>81.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>1002.4</td>\n",
       "      <td>5.0</td>\n",
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       "      <th>2016-12-28</th>\n",
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       "                 報告数  平均気温(℃)  最高気温(℃)  最低気温(℃)  平均湿度(％)  最小相対湿度(％)  \\\n",
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       "2016-12-24  6.892857      9.3     12.7      6.2     37.0       24.0   \n",
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       "2016-12-26  4.434783      8.3     14.4      3.7     56.0       41.0   \n",
       "2016-12-27  4.434783     13.0     19.2      5.3     81.0       72.0   \n",
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       "2016-12-31  4.434783      6.8     11.0      3.0     44.0       27.0   \n",
       "\n",
       "            平均現地気圧(hPa)  降水量の合計(mm)  日照時間(時間)  平均風速(m/s)  \n",
       "2016-12-22       1015.7         4.0       2.1        5.7  \n",
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       "2016-12-24       1018.9         0.0       8.6        5.0  \n",
       "2016-12-25       1028.9         0.0       4.6        2.2  \n",
       "2016-12-26       1022.8         0.0       2.8        1.9  \n",
       "2016-12-27       1002.4         5.0       0.1        7.3  \n",
       "2016-12-28       1018.4         0.5       9.4        4.2  \n",
       "2016-12-29       1017.0         0.0       5.3        2.3  \n",
       "2016-12-30       1022.0         0.0       9.3        4.3  \n",
       "2016-12-31       1023.1         0.0       9.2        1.6  "
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