県別・年代別の死亡数.ipynb

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      "name": "県別・年代別の死亡数.ipynb",
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        "<a href=\"https://colab.research.google.com/github/nagae/ICL_B_2021/blob/main/%E7%9C%8C%E5%88%A5%E3%83%BB%E5%B9%B4%E4%BB%A3%E5%88%A5%E3%81%AE%E6%AD%BB%E4%BA%A1%E6%95%B0.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
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    {
      "cell_type": "code",
      "metadata": {
        "id": "nC6ku_TpRTzC"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "from matplotlib  import pyplot as plt, dates as mdates\n",
        "import datetime"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "40l4PyqJRclW"
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      "source": [
        "orig_df = pd.read_json(\"https://raw.githubusercontent.com/reustle/covid19japan-data/master/docs/patient_data/latest.json\")\n",
        "#日付を文字列からdatetime型に変更しておく(列名を指定して代入)\n",
        "orig_df[\"dateAnnounced\"] = pd.to_datetime(orig_df[\"dateAnnounced\"], format= \"%Y-%m-%d\")\n",
        "orig_df[\"deceasedDate\"] = pd.to_datetime(orig_df[\"deceasedDate\"], format=\"%Y-%m-%d\")\n",
        "# ファイルを読み込み，列名(columns)を使いやすい形に修正"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
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      "source": [
        "df = orig_df.copy()\n",
        "df.columns = [ \"patientId\", \"年月日\" , \"年代\", \"性別\", \"都道府県\", \"容体\", \"感染順位\", \"都道府県別感染順位\", \"陽性数\", \"residence\", \"relatedPatients\",\t\"knownCluster\",\t\"detectedCityTown\",\t\"cityPrefectureNumber\",\t\"deceasedDate\",\t\"deceasedReportedDate\",\t\"deathSourceURL\"]\n",
        "# 年代データを整数値に変換する\n",
        "for c in df.columns:\n",
        "    if c not in [\"年代\"]: # 年代以外のデータは文字型として扱う\n",
        "        df[c] = df[c].astype(str)\n",
        "    else:\n",
        "        df[c] = pd.to_numeric(df[c], errors='coerce') # 都道府県名以外のデータは数値として扱う\n",
        "        df[c] = df[c].fillna(0) # データが欠損している部分を0で埋める\n",
        "        df[c] = df[c].astype(int) # 一旦は実数型に変換する \n",
        " \n",
        "# 都道府県名と年月日からなるマルチインデックスを構築\n",
        "df = df.set_index([\"都道府県\", \"容体\",\"年代\", \"年月日\"])\n",
        "df # orig_df の概観を表示"
      ],
      "execution_count": null,
      "outputs": [
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              "      <th>都道府県</th>\n",
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              "      <th>年代</th>\n",
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              "      <td>15</td>\n",
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              "      <th rowspan=\"2\" valign=\"top\">Recovered</th>\n",
              "      <th>40</th>\n",
              "      <th>2020-01-24</th>\n",
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              "      <th rowspan=\"2\" valign=\"top\">Aichi</th>\n",
              "      <th>nan</th>\n",
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              "      <th>2020-01-26</th>\n",
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              "      <td>Aichi#1</td>\n",
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              "      <td>nan</td>\n",
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              "      <td>2021-06-29</td>\n",
              "      <td>nan</td>\n",
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              "      <th>2021-06-29</th>\n",
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              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>2021-06-29</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
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              "    <tr>\n",
              "      <th>2021-06-29</th>\n",
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              "<p>812858 rows × 13 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                    patientId  ... deathSourceURL\n",
              "都道府県     容体           年代 年月日                   ...               \n",
              "Kanagawa Recovered    30 2020-01-15        15  ...            nan\n",
              "Tokyo    Recovered    40 2020-01-24      TOK1  ...            nan\n",
              "                      30 2020-01-25      TOK2  ...            nan\n",
              "Aichi    nan          40 2020-01-26        18  ...            nan\n",
              "         Hospitalized 40 2020-01-28        19  ...            nan\n",
              "...                                       ...  ...            ...\n",
              "Osaka    Deceased     0  2021-06-29        -1  ...            nan\n",
              "                         2021-06-29        -1  ...            nan\n",
              "                         2021-06-29        -1  ...            nan\n",
              "                         2021-06-29        -1  ...            nan\n",
              "                         2021-06-29        -1  ...            nan\n",
              "\n",
              "[812858 rows x 13 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 91
        }
      ]
    },
    {
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        "outputId": "33f9f67d-27b5-4f3c-869f-e8f9fa88e0b6"
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      "source": [
        "dead_df = df.xs(\"Deceased\",level=\"容体\")[\"patientId\"].groupby(level=[\"都道府県\",\"年代\",\"年月日\"]).count().to_frame().unstack(\"年代\")\n",
        "columns = dead_df.columns.get_level_values(level=1).values.astype(str)\n",
        "columns[columns == '0'] = \"Unspecified\"\n",
        "dead_df.columns = columns\n",
        "dead_df.fillna(0,inplace=True)\n",
        "dead_df"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
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              "      <td>0.0</td>\n",
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              "    <tr>\n",
              "      <th>2021-06-07</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-06-23</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>4693 rows × 10 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                      Unspecified   20   30   40   50   60   70   80   90  100\n",
              "都道府県      年月日                                                                 \n",
              "Aichi     2020-02-29          0.0  0.0  0.0  0.0  0.0  0.0  1.0  0.0  0.0  0.0\n",
              "          2020-03-04          0.0  0.0  1.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "          2020-03-05          0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  0.0  0.0\n",
              "          2020-03-08          0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  1.0  0.0\n",
              "          2020-03-09          0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  0.0  0.0\n",
              "...                           ...  ...  ...  ...  ...  ...  ...  ...  ...  ...\n",
              "Yamanashi 2021-02-10          1.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "          2021-02-27          1.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "          2021-03-28          1.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "          2021-06-07          1.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "          2021-06-23          1.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "\n",
              "[4693 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 101
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 450
        },
        "id": "umfB2aB86HnQ",
        "outputId": "816b585c-7c46-4740-ef63-6fb73e9fcab5"
      },
      "source": [
        "dead_df.loc[\"Aichi\"]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "    .dataframe tbody tr th {\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unspecified</th>\n",
              "      <th>20</th>\n",
              "      <th>30</th>\n",
              "      <th>40</th>\n",
              "      <th>50</th>\n",
              "      <th>60</th>\n",
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              "      <th>80</th>\n",
              "      <th>90</th>\n",
              "      <th>100</th>\n",
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              "    <tr>\n",
              "      <th>年月日</th>\n",
              "      <th></th>\n",
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              "      <th></th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2020-02-29</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>1.0</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-03-04</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-03-05</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-03-08</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-03-09</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-06-24</th>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-06-25</th>\n",
              "      <td>2.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-06-26</th>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-06-28</th>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-06-29</th>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>272 rows × 10 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            Unspecified   20   30   40   50   60   70   80   90  100\n",
              "年月日                                                                 \n",
              "2020-02-29          0.0  0.0  0.0  0.0  0.0  0.0  1.0  0.0  0.0  0.0\n",
              "2020-03-04          0.0  0.0  1.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "2020-03-05          0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  0.0  0.0\n",
              "2020-03-08          0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  1.0  0.0\n",
              "2020-03-09          0.0  0.0  0.0  0.0  0.0  0.0  0.0  1.0  0.0  0.0\n",
              "...                 ...  ...  ...  ...  ...  ...  ...  ...  ...  ...\n",
              "2021-06-24          3.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "2021-06-25          2.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "2021-06-26          5.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "2021-06-28          5.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "2021-06-29          1.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0\n",
              "\n",
              "[272 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 102
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PwkAsaZe7HBg"
      },
      "source": [
        "# 以下，未定"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cFE0CrEvVNhF"
      },
      "source": [
        "dates = pd.to_datetime(df.index.get_level_values(level=\"年月日\"))\n",
        "start, end = (dates.min(), dates.max())\n",
        "dates = np.arange(start,end,np.timedelta64(1,\"D\"))\n",
        "prefs = df.index.get_level_values(level=\"都道府県\").unique().drop([\"Unspecified\",\"Port Quarantine\"])\n",
        "ages = sorted(df.index.get_level_values(level=\"年代\").unique())"
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}