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lisphilar/monkeypox_linelist-to-sir_20220902.ipynb

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monkeypox_linelist-to-sir_20220902.ipynb
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
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"authorship_tag": "ABX9TyOJD73tft9IAxP3uP207a3z",
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{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
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"source": [
"<a href=\"https://colab.research.google.com/gist/lisphilar/23d23f8692f70f2663a6c4890758a7ab/monkeypox_linelist-to-sir_20220902.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",
"execution_count": 1,
"metadata": {
"id": "jUeS4l15ZgUB"
},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"source": [
"raw = pd.read_csv(\"https://raw.githubusercontent.com/globaldothealth/monkeypox/main/latest.csv\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "OuAmBW9HZ8aV",
"outputId": "2d2b1fd6-bb01-4b1e-9e61-5d36cab3127a"
},
"execution_count": 2,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py:3326: DtypeWarning: Columns (3,12,14,16,18,19,20,21,22,23,24,25,29) have mixed types.Specify dtype option on import or set low_memory=False.\n",
" exec(code_obj, self.user_global_ns, self.user_ns)\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"raw = pd.read_csv(\"https://raw.githubusercontent.com/globaldothealth/monkeypox/main/latest.csv\", engine=\"python\")"
],
"metadata": {
"id": "GmNIiVKraCur"
},
"execution_count": 4,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"## Check records"
],
"metadata": {
"id": "_1wAoOvxdPmJ"
}
},
{
"cell_type": "code",
"source": [
"raw.info()"
],
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"id": "_klrZPU8ahho",
"outputId": "6b39fcb5-52e5-4223-9bcc-91834870f0ba"
},
"execution_count": 5,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 55052 entries, 0 to 55051\n",
"Data columns (total 36 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 ID 55052 non-null object \n",
" 1 Status 55052 non-null object \n",
" 2 Location 40757 non-null object \n",
" 3 City 1274 non-null object \n",
" 4 Country 55052 non-null object \n",
" 5 Country_ISO3 55052 non-null object \n",
" 6 Age 2758 non-null object \n",
" 7 Gender 2251 non-null object \n",
" 8 Date_onset 66 non-null object \n",
" 9 Date_confirmation 52089 non-null object \n",
" 10 Symptoms 207 non-null object \n",
" 11 Hospitalised (Y/N/NA) 308 non-null object \n",
" 12 Date_hospitalisation 35 non-null object \n",
" 13 Isolated (Y/N/NA) 432 non-null object \n",
" 14 Date_isolation 16 non-null object \n",
" 15 Outcome 93 non-null object \n",
" 16 Contact_comment 91 non-null object \n",
" 17 Contact_ID 27 non-null float64\n",
" 18 Contact_location 6 non-null object \n",
" 19 Travel_history (Y/N/NA) 351 non-null object \n",
" 20 Travel_history_entry 38 non-null object \n",
" 21 Travel_history_start 10 non-null object \n",
" 22 Travel_history_location 111 non-null object \n",
" 23 Travel_history_country 95 non-null object \n",
" 24 Genomics_Metadata 24 non-null object \n",
" 25 Confirmation_method 99 non-null object \n",
" 26 Source 55052 non-null object \n",
" 27 Source_II 7468 non-null object \n",
" 28 Source_III 845 non-null object \n",
" 29 Source_IV 54 non-null object \n",
" 30 Source_V 0 non-null float64\n",
" 31 Source_VI 0 non-null float64\n",
" 32 Source_VII 0 non-null float64\n",
" 33 Date_entry 55052 non-null object \n",
" 34 Date_death 75 non-null object \n",
" 35 Date_last_modified 55052 non-null object \n",
"dtypes: float64(4), object(32)\n",
"memory usage: 15.1+ MB\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"raw.head()"
],
"metadata": {
"colab": {
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"height": 595
},
"id": "E4E41rH_akay",
"outputId": "c8b54fc4-6257-4b71-8ff4-03ffc644a8ab"
},
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"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" ID Status Location City Country \\\n",
"0 N1 confirmed Guy's and St Thomas Hospital London London England \n",
"1 N2 confirmed Guy's and St Thomas Hospital London London England \n",
"2 N3 confirmed London London England \n",
"3 N4 confirmed London London England \n",
"4 N5 confirmed London London England \n",
"\n",
" Country_ISO3 Age Gender Date_onset Date_confirmation ... \\\n",
"0 GBR NaN NaN 2022-04-29 2022-05-06 ... \n",
"1 GBR NaN NaN 2022-05-05 2022-05-12 ... \n",
"2 GBR NaN NaN 2022-04-30 2022-05-13 ... \n",
"3 GBR NaN male NaN 2022-05-15 ... \n",
"4 GBR NaN male NaN 2022-05-15 ... \n",
"\n",
" Source \\\n",
"0 https://www.gov.uk/government/news/monkeypox-c... \n",
"1 https://www.gov.uk/government/news/monkeypox-c... \n",
"2 https://www.gov.uk/government/news/monkeypox-c... \n",
"3 https://www.gov.uk/government/news/monkeypox-c... \n",
"4 https://www.gov.uk/government/news/monkeypox-c... \n",
"\n",
" Source_II Source_III Source_IV \\\n",
"0 https://www.who.int/emergencies/disease-outbre... NaN NaN \n",
"1 NaN NaN NaN \n",
"2 NaN NaN NaN \n",
"3 NaN NaN NaN \n",
"4 NaN NaN NaN \n",
"\n",
" Source_V Source_VI Source_VII Date_entry Date_death Date_last_modified \n",
"0 NaN NaN NaN 2022-05-18 NaN 2022-05-18 \n",
"1 NaN NaN NaN 2022-05-18 NaN 2022-05-18 \n",
"2 NaN NaN NaN 2022-05-18 NaN 2022-05-18 \n",
"3 NaN NaN NaN 2022-05-18 NaN 2022-05-18 \n",
"4 NaN NaN NaN 2022-05-18 NaN 2022-05-18 \n",
"\n",
"[5 rows x 36 columns]"
],
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"\n",
" <div id=\"df-b4a88862-fc3e-4420-a0e9-8bc532737eff\">\n",
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>ID</th>\n",
" <th>Status</th>\n",
" <th>Location</th>\n",
" <th>City</th>\n",
" <th>Country</th>\n",
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" <th>Date_confirmation</th>\n",
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" <td>2022-05-06</td>\n",
" <td>...</td>\n",
" <td>https://www.gov.uk/government/news/monkeypox-c...</td>\n",
" <td>https://www.who.int/emergencies/disease-outbre...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2022-05-18</td>\n",
" <td>NaN</td>\n",
" <td>2022-05-18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>N2</td>\n",
" <td>confirmed</td>\n",
" <td>Guy's and St Thomas Hospital London</td>\n",
" <td>London</td>\n",
" <td>England</td>\n",
" <td>GBR</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2022-05-05</td>\n",
" <td>2022-05-12</td>\n",
" <td>...</td>\n",
" <td>https://www.gov.uk/government/news/monkeypox-c...</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>2022-05-18</td>\n",
" <td>NaN</td>\n",
" <td>2022-05-18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>N3</td>\n",
" <td>confirmed</td>\n",
" <td>London</td>\n",
" <td>London</td>\n",
" <td>England</td>\n",
" <td>GBR</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2022-04-30</td>\n",
" <td>2022-05-13</td>\n",
" <td>...</td>\n",
" <td>https://www.gov.uk/government/news/monkeypox-c...</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>2022-05-18</td>\n",
" <td>NaN</td>\n",
" <td>2022-05-18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>N4</td>\n",
" <td>confirmed</td>\n",
" <td>London</td>\n",
" <td>London</td>\n",
" <td>England</td>\n",
" <td>GBR</td>\n",
" <td>NaN</td>\n",
" <td>male</td>\n",
" <td>NaN</td>\n",
" <td>2022-05-15</td>\n",
" <td>...</td>\n",
" <td>https://www.gov.uk/government/news/monkeypox-c...</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>2022-05-18</td>\n",
" <td>NaN</td>\n",
" <td>2022-05-18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>N5</td>\n",
" <td>confirmed</td>\n",
" <td>London</td>\n",
" <td>London</td>\n",
" <td>England</td>\n",
" <td>GBR</td>\n",
" <td>NaN</td>\n",
" <td>male</td>\n",
" <td>NaN</td>\n",
" <td>2022-05-15</td>\n",
" <td>...</td>\n",
" <td>https://www.gov.uk/government/news/monkeypox-c...</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>2022-05-18</td>\n",
" <td>NaN</td>\n",
" <td>2022-05-18</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 36 columns</p>\n",
"</div>\n",
" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b4a88862-fc3e-4420-a0e9-8bc532737eff')\"\n",
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"\n",
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" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
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" element.appendChild(docLink);\n",
" }\n",
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" "
]
},
"metadata": {},
"execution_count": 6
}
]
},
{
"cell_type": "code",
"source": [
"raw.Status.unique()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "CsYchIAwap9F",
"outputId": "34074f52-ccba-4d6d-cf61-439b49b86b4e"
},
"execution_count": 10,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"array(['confirmed', 'discarded', 'suspected', 'omit_error'], dtype=object)"
]
},
"metadata": {},
"execution_count": 10
}
]
},
{
"cell_type": "code",
"source": [
"raw.Outcome.unique()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "Q9OGG1yVbBqr",
"outputId": "efa3bb77-20e7-4750-c979-963077328acc"
},
"execution_count": 11,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"array([nan, 'Recovered', 'Death'], dtype=object)"
]
},
"metadata": {},
"execution_count": 11
}
]
},
{
"cell_type": "markdown",
"source": [
"## Per protocol set"
],
"metadata": {
"id": "hXu_iqPfdU0O"
}
},
{
"cell_type": "code",
"source": [
"date_cols = [\n",
" \"Date_onset\", \"Date_confirmation\", \"Date_hospitalisation\",\n",
" \"Date_isolation\", \"Date_death\", \"Date_last_modified\"\n",
"]\n",
"cols = [\"ID\", \"Status\", \"City\", \"Country_ISO3\", \"Outcome\", *date_cols]\n",
"df = raw.loc[:, cols].rename(columns={\"Country_ISO3\": \"ISO3\"})\n",
"df = df.loc[df[\"Status\"].isin([\"confirmed\", \"suspected\"])]\n",
"\n",
"for col in date_cols:\n",
" df[col] = pd.to_datetime(df[col])\n",
"\n",
"df[\"Date_min\"] = df[date_cols].min(axis=1)\n",
"df[\"Date_recovered\"] = df[[\"Outcome\", \"Date_last_modified\"]].apply(\n",
" lambda x: x[1] if x[0] == \"Recovered\" else pd.NaT, axis=1)\n",
"df[\"City\"] = df[\"City\"].fillna(\"Unknown\")\n",
"\n",
"ppt_df = df.copy()\n",
"ppt_df"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 488
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"id": "Lcm-VQG6dUI-",
"outputId": "8a105fb8-33ab-45d8-f80a-85a592c70db0"
},
"execution_count": 19,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" ID Status City ISO3 Outcome Date_onset Date_confirmation \\\n",
"0 N1 confirmed London GBR NaN 2022-04-29 2022-05-06 \n",
"1 N2 confirmed London GBR NaN 2022-05-05 2022-05-12 \n",
"2 N3 confirmed London GBR NaN 2022-04-30 2022-05-13 \n",
"3 N4 confirmed London GBR NaN NaT 2022-05-15 \n",
"4 N5 confirmed London GBR NaN NaT 2022-05-15 \n",
"... ... ... ... ... ... ... ... \n",
"55047 E2915 suspected Unknown NGA NaN NaT NaT \n",
"55048 E2916 suspected Unknown NGA NaN NaT NaT \n",
"55049 E2917 suspected Unknown NGA NaN NaT NaT \n",
"55050 E2918 confirmed Unknown NGA NaN NaT 2022-08-07 \n",
"55051 E2919 suspected Unknown NGA NaN NaT NaT \n",
"\n",
" Date_hospitalisation Date_isolation Date_death Date_last_modified \\\n",
"0 2022-05-04 2022-05-04 NaT 2022-05-18 \n",
"1 2022-05-06 2022-05-09 NaT 2022-05-18 \n",
"2 NaT NaT NaT 2022-05-18 \n",
"3 NaT NaT NaT 2022-05-18 \n",
"4 NaT NaT NaT 2022-05-18 \n",
"... ... ... ... ... \n",
"55047 NaT NaT NaT 2022-08-19 \n",
"55048 NaT NaT NaT 2022-08-19 \n",
"55049 NaT NaT NaT 2022-08-19 \n",
"55050 NaT NaT NaT 2022-08-19 \n",
"55051 NaT NaT NaT 2022-08-19 \n",
"\n",
" Date_min Date_recovered \n",
"0 2022-04-29 NaT \n",
"1 2022-05-05 NaT \n",
"2 2022-04-30 NaT \n",
"3 2022-05-15 NaT \n",
"4 2022-05-15 NaT \n",
"... ... ... \n",
"55047 2022-08-19 NaT \n",
"55048 2022-08-19 NaT \n",
"55049 2022-08-19 NaT \n",
"55050 2022-08-07 NaT \n",
"55051 2022-08-19 NaT \n",
"\n",
"[54364 rows x 13 columns]"
],
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" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>ID</th>\n",
" <th>Status</th>\n",
" <th>City</th>\n",
" <th>ISO3</th>\n",
" <th>Outcome</th>\n",
" <th>Date_onset</th>\n",
" <th>Date_confirmation</th>\n",
" <th>Date_hospitalisation</th>\n",
" <th>Date_isolation</th>\n",
" <th>Date_death</th>\n",
" <th>Date_last_modified</th>\n",
" <th>Date_min</th>\n",
" <th>Date_recovered</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>N1</td>\n",
" <td>confirmed</td>\n",
" <td>London</td>\n",
" <td>GBR</td>\n",
" <td>NaN</td>\n",
" <td>2022-04-29</td>\n",
" <td>2022-05-06</td>\n",
" <td>2022-05-04</td>\n",
" <td>2022-05-04</td>\n",
" <td>NaT</td>\n",
" <td>2022-05-18</td>\n",
" <td>2022-04-29</td>\n",
" <td>NaT</td>\n",
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" <tr>\n",
" <th>1</th>\n",
" <td>N2</td>\n",
" <td>confirmed</td>\n",
" <td>London</td>\n",
" <td>GBR</td>\n",
" <td>NaN</td>\n",
" <td>2022-05-05</td>\n",
" <td>2022-05-12</td>\n",
" <td>2022-05-06</td>\n",
" <td>2022-05-09</td>\n",
" <td>NaT</td>\n",
" <td>2022-05-18</td>\n",
" <td>2022-05-05</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>N3</td>\n",
" <td>confirmed</td>\n",
" <td>London</td>\n",
" <td>GBR</td>\n",
" <td>NaN</td>\n",
" <td>2022-04-30</td>\n",
" <td>2022-05-13</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>2022-05-18</td>\n",
" <td>2022-04-30</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>N4</td>\n",
" <td>confirmed</td>\n",
" <td>London</td>\n",
" <td>GBR</td>\n",
" <td>NaN</td>\n",
" <td>NaT</td>\n",
" <td>2022-05-15</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>2022-05-18</td>\n",
" <td>2022-05-15</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>N5</td>\n",
" <td>confirmed</td>\n",
" <td>London</td>\n",
" <td>GBR</td>\n",
" <td>NaN</td>\n",
" <td>NaT</td>\n",
" <td>2022-05-15</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>2022-05-18</td>\n",
" <td>2022-05-15</td>\n",
" <td>NaT</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",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>55047</th>\n",
" <td>E2915</td>\n",
" <td>suspected</td>\n",
" <td>Unknown</td>\n",
" <td>NGA</td>\n",
" <td>NaN</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>2022-08-19</td>\n",
" <td>2022-08-19</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>55048</th>\n",
" <td>E2916</td>\n",
" <td>suspected</td>\n",
" <td>Unknown</td>\n",
" <td>NGA</td>\n",
" <td>NaN</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>2022-08-19</td>\n",
" <td>2022-08-19</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>55049</th>\n",
" <td>E2917</td>\n",
" <td>suspected</td>\n",
" <td>Unknown</td>\n",
" <td>NGA</td>\n",
" <td>NaN</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>2022-08-19</td>\n",
" <td>2022-08-19</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>55050</th>\n",
" <td>E2918</td>\n",
" <td>confirmed</td>\n",
" <td>Unknown</td>\n",
" <td>NGA</td>\n",
" <td>NaN</td>\n",
" <td>NaT</td>\n",
" <td>2022-08-07</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>2022-08-19</td>\n",
" <td>2022-08-07</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" <tr>\n",
" <th>55051</th>\n",
" <td>E2919</td>\n",
" <td>suspected</td>\n",
" <td>Unknown</td>\n",
" <td>NGA</td>\n",
" <td>NaN</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>2022-08-19</td>\n",
" <td>2022-08-19</td>\n",
" <td>NaT</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
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"metadata": {},
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]
},
{
"cell_type": "markdown",
"source": [
"## Daily new confirmed cases"
],
"metadata": {
"id": "7UAhSfmJhmme"
}
},
{
"cell_type": "code",
"source": [
"df = ppt_df.rename(columns={\"Date_min\": \"Date\"})\n",
"series = df.groupby([\"ISO3\", \"City\", \"Date\"])[\"ID\"].count()\n",
"series.name = \"Confirmed\"\n",
"c_df = pd.DataFrame(series).reset_index()\n",
"c_df"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 424
},
"id": "77WzD8WxgJk2",
"outputId": "5d7d2c34-e230-4cb1-8a96-ed800685ac08"
},
"execution_count": 20,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" ISO3 City Date Confirmed\n",
"0 ABW Unknown 2022-08-22 1\n",
"1 ABW Unknown 2022-08-29 1\n",
"2 AND Unknown 2022-07-25 1\n",
"3 AND Unknown 2022-07-26 2\n",
"4 AND Unknown 2022-08-08 1\n",
"... ... ... ... ...\n",
"1618 ZAF Johannesburg 2022-08-17 1\n",
"1619 ZAF Unknown 2022-06-22 1\n",
"1620 ZAF Unknown 2022-07-11 1\n",
"1621 ZAF Unknown 2022-08-15 1\n",
"1622 ZMB Unknown 2022-06-24 1\n",
"\n",
"[1623 rows x 4 columns]"
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"metadata": {},
"execution_count": 20
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]
},
{
"cell_type": "markdown",
"source": [
"## Daily new recovered cases"
],
"metadata": {
"id": "PWSbvnoph7dg"
}
},
{
"cell_type": "code",
"source": [
"ppt_df.loc[ppt_df.Outcome == \"Recovered\"]"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 270
},
"id": "Q-IMfk2LiHHf",
"outputId": "38a1c2e8-b295-4702-a94b-c4faf8827b26"
},
"execution_count": 22,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" ID Status City ISO3 Outcome Date_onset \\\n",
"107 N108 confirmed Melbourne AUS Recovered 2022-05-08 \n",
"28406 N28407 confirmed Unknown TUR Recovered NaT \n",
"28407 N28408 confirmed Unknown TUR Recovered NaT \n",
"28408 N28409 confirmed Unknown TUR Recovered NaT \n",
"28409 N28410 confirmed Unknown TUR Recovered NaT \n",
"\n",
" Date_confirmation Date_hospitalisation Date_isolation Date_death \\\n",
"107 2022-05-20 2022-05-19 2022-05-20 NaT \n",
"28406 2022-08-02 NaT NaT NaT \n",
"28407 2022-08-02 NaT NaT NaT \n",
"28408 2022-08-02 NaT NaT NaT \n",
"28409 2022-08-02 NaT NaT NaT \n",
"\n",
" Date_last_modified Date_min Date_recovered \n",
"107 2022-06-30 2022-05-08 2022-06-30 \n",
"28406 2022-08-05 2022-08-02 2022-08-05 \n",
"28407 2022-08-05 2022-08-02 2022-08-05 \n",
"28408 2022-08-05 2022-08-02 2022-08-05 \n",
"28409 2022-08-05 2022-08-02 2022-08-05 "
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" <th></th>\n",
" <th>ID</th>\n",
" <th>Status</th>\n",
" <th>City</th>\n",
" <th>ISO3</th>\n",
" <th>Outcome</th>\n",
" <th>Date_onset</th>\n",
" <th>Date_confirmation</th>\n",
" <th>Date_hospitalisation</th>\n",
" <th>Date_isolation</th>\n",
" <th>Date_death</th>\n",
" <th>Date_last_modified</th>\n",
" <th>Date_min</th>\n",
" <th>Date_recovered</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>107</th>\n",
" <td>N108</td>\n",
" <td>confirmed</td>\n",
" <td>Melbourne</td>\n",
" <td>AUS</td>\n",
" <td>Recovered</td>\n",
" <td>2022-05-08</td>\n",
" <td>2022-05-20</td>\n",
" <td>2022-05-19</td>\n",
" <td>2022-05-20</td>\n",
" <td>NaT</td>\n",
" <td>2022-06-30</td>\n",
" <td>2022-05-08</td>\n",
" <td>2022-06-30</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28406</th>\n",
" <td>N28407</td>\n",
" <td>confirmed</td>\n",
" <td>Unknown</td>\n",
" <td>TUR</td>\n",
" <td>Recovered</td>\n",
" <td>NaT</td>\n",
" <td>2022-08-02</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>2022-08-05</td>\n",
" <td>2022-08-02</td>\n",
" <td>2022-08-05</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28407</th>\n",
" <td>N28408</td>\n",
" <td>confirmed</td>\n",
" <td>Unknown</td>\n",
" <td>TUR</td>\n",
" <td>Recovered</td>\n",
" <td>NaT</td>\n",
" <td>2022-08-02</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>2022-08-05</td>\n",
" <td>2022-08-02</td>\n",
" <td>2022-08-05</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28408</th>\n",
" <td>N28409</td>\n",
" <td>confirmed</td>\n",
" <td>Unknown</td>\n",
" <td>TUR</td>\n",
" <td>Recovered</td>\n",
" <td>NaT</td>\n",
" <td>2022-08-02</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>2022-08-05</td>\n",
" <td>2022-08-02</td>\n",
" <td>2022-08-05</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28409</th>\n",
" <td>N28410</td>\n",
" <td>confirmed</td>\n",
" <td>Unknown</td>\n",
" <td>TUR</td>\n",
" <td>Recovered</td>\n",
" <td>NaT</td>\n",
" <td>2022-08-02</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>NaT</td>\n",
" <td>2022-08-05</td>\n",
" <td>2022-08-02</td>\n",
" <td>2022-08-05</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>\n",
" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a985f137-c5ec-4de8-b7d5-a95b1e2dfc3f')\"\n",
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" </svg>\n",
" </button>\n",
" \n",
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"\n",
" .colab-df-convert:hover {\n",
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"\n",
" async function convertToInteractive(key) {\n",
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" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
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"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
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" const docLink = document.createElement('div');\n",
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" element.appendChild(docLink);\n",
" }\n",
" </script>\n",
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" "
]
},
"metadata": {},
"execution_count": 22
}
]
},
{
"cell_type": "code",
"source": [
"df = ppt_df.rename(columns={\"Date_recovered\": \"Date\"})\n",
"series = df.groupby([\"ISO3\", \"City\", \"Date\"])[\"ID\"].count()\n",
"series.name = \"Recovered\"\n",
"r_df = pd.DataFrame(series).reset_index()\n",
"r_df"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 112
},
"id": "UzJK9mcwhpid",
"outputId": "764e9430-2a23-41c6-ff5c-060d4e6b428c"
},
"execution_count": 21,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" ISO3 City Date Recovered\n",
"0 AUS Melbourne 2022-06-30 1\n",
"1 TUR Unknown 2022-08-05 4"
],
"text/html": [
"\n",
" <div id=\"df-b7e83210-9727-485e-a2b2-05a86bef8374\">\n",
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" <th></th>\n",
" <th>ISO3</th>\n",
" <th>City</th>\n",
" <th>Date</th>\n",
" <th>Recovered</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>AUS</td>\n",
" <td>Melbourne</td>\n",
" <td>2022-06-30</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>TUR</td>\n",
" <td>Unknown</td>\n",
" <td>2022-08-05</td>\n",
" <td>4</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>\n",
" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b7e83210-9727-485e-a2b2-05a86bef8374')\"\n",
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" style=\"display:none;\">\n",
" \n",
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"\n",
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" const buttonEl =\n",
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"\n",
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" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
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" element.appendChild(docLink);\n",
" }\n",
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]
},
"metadata": {},
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]
},
{
"cell_type": "markdown",
"source": [
"## Daily new fatal cases"
],
"metadata": {
"id": "1QCUguUbiq8w"
}
},
{
"cell_type": "code",
"source": [
"df = ppt_df.rename(columns={\"Date_death\": \"Date\"})\n",
"series = df.groupby([\"ISO3\", \"City\", \"Date\"])[\"ID\"].count()\n",
"series.name = \"Fatal\"\n",
"f_df = pd.DataFrame(series).reset_index()\n",
"f_df"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 896
},
"id": "WXi3Sphuh-hs",
"outputId": "2e7f7409-a271-465c-896e-521997a60918"
},
"execution_count": 23,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" ISO3 City Date Fatal\n",
"0 BRA Unknown 2022-07-28 1\n",
"1 BRA Unknown 2022-08-29 1\n",
"2 CAF Unknown 2022-03-04 2\n",
"3 COD Unknown 2022-01-16 18\n",
"4 COD Unknown 2022-01-23 3\n",
"5 COD Unknown 2022-02-13 8\n",
"6 COD Unknown 2022-02-27 8\n",
"7 COD Unknown 2022-03-27 4\n",
"8 COD Unknown 2022-04-10 3\n",
"9 COD Unknown 2022-04-24 2\n",
"10 COD Unknown 2022-05-08 1\n",
"11 COD Unknown 2022-05-22 6\n",
"12 COD Unknown 2022-05-29 1\n",
"13 COG Unknown 2022-05-30 3\n",
"14 CUB Unknown 2022-08-21 1\n",
"15 ECU Unknown 2022-08-08 1\n",
"16 ESP Unknown 2022-07-29 1\n",
"17 ESP Unknown 2022-07-30 1\n",
"18 GHA Unknown 2022-07-26 1\n",
"19 IND Unknown 2022-07-30 1\n",
"20 MEX Unknown 2022-08-15 1\n",
"21 NGA Unknown 2022-05-29 1\n",
"22 NGA Unknown 2022-07-10 2\n",
"23 NGA Unknown 2022-07-31 1\n",
"24 PER Unknown 2022-08-01 1\n",
"25 PER Unknown 2022-08-26 1\n",
"26 USA Unknown 2022-08-29 1"
],
"text/html": [
"\n",
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" <th></th>\n",
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" <th>Date</th>\n",
" <th>Fatal</th>\n",
" </tr>\n",
" </thead>\n",
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" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>BRA</td>\n",
" <td>Unknown</td>\n",
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" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>CAF</td>\n",
" <td>Unknown</td>\n",
" <td>2022-03-04</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>COD</td>\n",
" <td>Unknown</td>\n",
" <td>2022-01-16</td>\n",
" <td>18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>COD</td>\n",
" <td>Unknown</td>\n",
" <td>2022-01-23</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>COD</td>\n",
" <td>Unknown</td>\n",
" <td>2022-02-13</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>COD</td>\n",
" <td>Unknown</td>\n",
" <td>2022-02-27</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>COD</td>\n",
" <td>Unknown</td>\n",
" <td>2022-03-27</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>COD</td>\n",
" <td>Unknown</td>\n",
" <td>2022-04-10</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>COD</td>\n",
" <td>Unknown</td>\n",
" <td>2022-04-24</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>COD</td>\n",
" <td>Unknown</td>\n",
" <td>2022-05-08</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>COD</td>\n",
" <td>Unknown</td>\n",
" <td>2022-05-22</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>COD</td>\n",
" <td>Unknown</td>\n",
" <td>2022-05-29</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>COG</td>\n",
" <td>Unknown</td>\n",
" <td>2022-05-30</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>CUB</td>\n",
" <td>Unknown</td>\n",
" <td>2022-08-21</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>ECU</td>\n",
" <td>Unknown</td>\n",
" <td>2022-08-08</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>ESP</td>\n",
" <td>Unknown</td>\n",
" <td>2022-07-29</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>ESP</td>\n",
" <td>Unknown</td>\n",
" <td>2022-07-30</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>GHA</td>\n",
" <td>Unknown</td>\n",
" <td>2022-07-26</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>IND</td>\n",
" <td>Unknown</td>\n",
" <td>2022-07-30</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>MEX</td>\n",
" <td>Unknown</td>\n",
" <td>2022-08-15</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>NGA</td>\n",
" <td>Unknown</td>\n",
" <td>2022-05-29</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>NGA</td>\n",
" <td>Unknown</td>\n",
" <td>2022-07-10</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>NGA</td>\n",
" <td>Unknown</td>\n",
" <td>2022-07-31</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>PER</td>\n",
" <td>Unknown</td>\n",
" <td>2022-08-01</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>PER</td>\n",
" <td>Unknown</td>\n",
" <td>2022-08-26</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>USA</td>\n",
" <td>Unknown</td>\n",
" <td>2022-08-29</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>\n",
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]
},
"metadata": {},
"execution_count": 23
}
]
},
{
"cell_type": "markdown",
"source": [
"## All data (Cumulative number)"
],
"metadata": {
"id": "hylM59U0iyua"
}
},
{
"cell_type": "markdown",
"source": [
"At city level (including unknown):"
],
"metadata": {
"id": "imgx9-4vi790"
}
},
{
"cell_type": "code",
"source": [
"df = c_df.copy()\n",
"df = df.merge(r_df, how=\"outer\", on=[\"ISO3\", \"City\", \"Date\"])\n",
"df = df.merge(f_df, how=\"outer\", on=[\"ISO3\", \"City\", \"Date\"])\n",
"df = df.pivot_table(columns=[\"ISO3\", \"City\"], index=\"Date\").reindex(\n",
" index=pd.date_range(start=df.Date.min(), end=df.Date.max(), freq=\"D\", name=\"Date\"))\n",
"df = df.ffill().fillna(0)\n",
"df = df.cumsum().stack().stack().fillna(0)\n",
"df = df.sort_values([\"ISO3\", \"City\", \"Date\"])\n",
"df = df.swaplevel(0, 2).reset_index().convert_dtypes()\n",
"all_df_city = df.copy()\n",
"all_df_city"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 424
},
"id": "4MdZQU1_iv-A",
"outputId": "b25a8935-2c2a-49c6-a1d6-e8d78d90014e"
},
"execution_count": 24,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" ISO3 City Date Confirmed Fatal Recovered\n",
"0 ABW Unknown 2022-01-16 0 0 0\n",
"1 ABW Unknown 2022-01-17 0 0 0\n",
"2 ABW Unknown 2022-01-18 0 0 0\n",
"3 ABW Unknown 2022-01-19 0 0 0\n",
"4 ABW Unknown 2022-01-20 0 0 0\n",
"... ... ... ... ... ... ...\n",
"60871 ZMB Unknown 2022-08-27 65 0 0\n",
"60872 ZMB Unknown 2022-08-28 66 0 0\n",
"60873 ZMB Unknown 2022-08-29 67 0 0\n",
"60874 ZMB Unknown 2022-08-30 68 0 0\n",
"60875 ZMB Unknown 2022-08-31 69 0 0\n",
"\n",
"[60876 rows x 6 columns]"
],
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" <th></th>\n",
" <th>ISO3</th>\n",
" <th>City</th>\n",
" <th>Date</th>\n",
" <th>Confirmed</th>\n",
" <th>Fatal</th>\n",
" <th>Recovered</th>\n",
" </tr>\n",
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" <tr>\n",
" <th>0</th>\n",
" <td>ABW</td>\n",
" <td>Unknown</td>\n",
" <td>2022-01-16</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>ABW</td>\n",
" <td>Unknown</td>\n",
" <td>2022-01-17</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>ABW</td>\n",
" <td>Unknown</td>\n",
" <td>2022-01-18</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>ABW</td>\n",
" <td>Unknown</td>\n",
" <td>2022-01-19</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>ABW</td>\n",
" <td>Unknown</td>\n",
" <td>2022-01-20</td>\n",
" <td>0</td>\n",
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" <tr>\n",
" <th>60871</th>\n",
" <td>ZMB</td>\n",
" <td>Unknown</td>\n",
" <td>2022-08-27</td>\n",
" <td>65</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>60872</th>\n",
" <td>ZMB</td>\n",
" <td>Unknown</td>\n",
" <td>2022-08-28</td>\n",
" <td>66</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>60873</th>\n",
" <td>ZMB</td>\n",
" <td>Unknown</td>\n",
" <td>2022-08-29</td>\n",
" <td>67</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>60874</th>\n",
" <td>ZMB</td>\n",
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" <td>2022-08-30</td>\n",
" <td>68</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>60875</th>\n",
" <td>ZMB</td>\n",
" <td>Unknown</td>\n",
" <td>2022-08-31</td>\n",
" <td>69</td>\n",
" <td>0</td>\n",
" <td>0</td>\n",
" </tr>\n",
" </tbody>\n",
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"<p>60876 rows × 6 columns</p>\n",
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"\n",
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" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
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" element.appendChild(docLink);\n",
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]
},
"metadata": {},
"execution_count": 24
}
]
},
{
"cell_type": "markdown",
"source": [
"At country level (City = \"-\") and city level (City != \"=\")"
],
"metadata": {
"id": "S_x80FxZjBZQ"
}
},
{
"cell_type": "code",
"source": [
"df2 = all_df_city.groupby([\"ISO3\", \"Date\"], as_index=False).sum()\n",
"df2.insert(1, \"City\", \"-\")\n",
"df = pd.concat([df2, all_df_city], axis=0)\n",
"df = df.loc[df[\"City\"] != \"Unknown\"]\n",
"all_df = df.copy()\n",
"all_df"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 424
},
"id": "XRC52rVYi4Bh",
"outputId": "e82a51b0-4aa4-453b-cd2c-2e7d5195ad8c"
},
"execution_count": 26,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" ISO3 City Date Confirmed Fatal Recovered\n",
"0 ABW - 2022-01-16 0 0 0\n",
"1 ABW - 2022-01-17 0 0 0\n",
"2 ABW - 2022-01-18 0 0 0\n",
"3 ABW - 2022-01-19 0 0 0\n",
"4 ABW - 2022-01-20 0 0 0\n",
"... ... ... ... ... ... ...\n",
"60415 ZAF Johannesburg 2022-08-27 11 0 0\n",
"60416 ZAF Johannesburg 2022-08-28 12 0 0\n",
"60417 ZAF Johannesburg 2022-08-29 13 0 0\n",
"60418 ZAF Johannesburg 2022-08-30 14 0 0\n",
"60419 ZAF Johannesburg 2022-08-31 15 0 0\n",
"\n",
"[61788 rows x 6 columns]"
],
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" <th>Date</th>\n",
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" border-radius: 50%;\n",
" cursor: pointer;\n",
" display: none;\n",
" fill: #1967D2;\n",
" height: 32px;\n",
" padding: 0 0 0 0;\n",
" width: 32px;\n",
" }\n",
"\n",
" .colab-df-convert:hover {\n",
" background-color: #E2EBFA;\n",
" box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
" fill: #174EA6;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-convert {\n",
" background-color: #3B4455;\n",
" fill: #D2E3FC;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-convert:hover {\n",
" background-color: #434B5C;\n",
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
" fill: #FFFFFF;\n",
" }\n",
" </style>\n",
"\n",
" <script>\n",
" const buttonEl =\n",
" document.querySelector('#df-880e5bc6-02c8-429a-9c76-941a6ade4ae4 button.colab-df-convert');\n",
" buttonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
"\n",
" async function convertToInteractive(key) {\n",
" const element = document.querySelector('#df-880e5bc6-02c8-429a-9c76-941a6ade4ae4');\n",
" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
" const docLink = document.createElement('div');\n",
" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
" </script>\n",
" </div>\n",
" </div>\n",
" "
]
},
"metadata": {},
"execution_count": 26
}
]
},
{
"cell_type": "markdown",
"source": [
"## Optional: check data"
],
"metadata": {
"id": "stAZtn4cjd0e"
}
},
{
"cell_type": "code",
"source": [
"import numpy as np\n",
"\n",
"try:\n",
" import covsirphy as cs\n",
"except ImportError:\n",
" !pip install --upgrade covsirphy -qq\n",
" import covsirphy as cs\n",
"cs.__version__"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 35
},
"id": "eBI7eVDGi6mt",
"outputId": "425c0c65-5b33-45ad-b3b0-fdeef7aedacf"
},
"execution_count": 33,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"'2.25.0'"
],
"application/vnd.google.colaboratory.intrinsic+json": {
"type": "string"
}
},
"metadata": {},
"execution_count": 33
}
]
},
{
"cell_type": "code",
"source": [
"gis = cs.GIS(layers=[\"ISO3\", \"City\"], country=\"ISO3\", date=\"Date\")\n",
"gis.register(data=all_df, convert_iso3=False)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "DiVv1EaAjkZN",
"outputId": "b78a9dce-1065-423a-f662-36cdd20e5c0f"
},
"execution_count": 28,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<covsirphy.gis.gis.GIS at 0x7f9a66e9ccd0>"
]
},
"metadata": {},
"execution_count": 28
}
]
},
{
"cell_type": "code",
"source": [
"variable = \"Confirmed\"\n",
"gis.choropleth(variable=variable, filename=None, title=f\"Choropleth map (the number of {variable} cases)\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 352
},
"id": "NjQv6lujjuTv",
"outputId": "dfebec35-f819-43d7-bd09-47177bec4cbc"
},
"execution_count": 29,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Retrieving GIS data from Natural Earth https://www.naturalearthdata.com/\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 648x432 with 2 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"variable = \"Recovered\"\n",
"gis.choropleth(variable=variable, filename=None, title=f\"Choropleth map (the number of {variable} cases)\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 329
},
"id": "_7SKYfmajvV6",
"outputId": "2565e2d8-9831-4101-f3c7-45f2d1e9a99a"
},
"execution_count": 30,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 648x432 with 2 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"variable = \"Fatal\"\n",
"gis.choropleth(variable=variable, filename=None, title=f\"Choropleth map (the number of {variable} cases)\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 332
},
"id": "O698tNDUjxAj",
"outputId": "cfb5d04d-3276-4e62-a7ae-f1428b323669"
},
"execution_count": 31,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 648x432 with 2 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"source": [
"global_df = gis.subset(geo=None).set_index(\"Date\").astype(np.int64)\n",
"global_df.tail()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 238
},
"id": "D1X0CfRZjyvm",
"outputId": "91fa9794-f984-444a-8a9e-7d7c3d6de4fe"
},
"execution_count": 36,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
" Confirmed Fatal Recovered\n",
"Date \n",
"2022-08-27 171478 1724 151\n",
"2022-08-28 174405 1739 156\n",
"2022-08-29 177120 1755 161\n",
"2022-08-30 179330 1771 166\n",
"2022-08-31 181753 1787 171"
],
"text/html": [
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" <th></th>\n",
" <th>Confirmed</th>\n",
" <th>Fatal</th>\n",
" <th>Recovered</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Date</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
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" <tbody>\n",
" <tr>\n",
" <th>2022-08-27</th>\n",
" <td>171478</td>\n",
" <td>1724</td>\n",
" <td>151</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2022-08-28</th>\n",
" <td>174405</td>\n",
" <td>1739</td>\n",
" <td>156</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2022-08-29</th>\n",
" <td>177120</td>\n",
" <td>1755</td>\n",
" <td>161</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2022-08-30</th>\n",
" <td>179330</td>\n",
" <td>1771</td>\n",
" <td>166</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2022-08-31</th>\n",
" <td>181753</td>\n",
" <td>1787</td>\n",
" <td>171</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>\n",
" <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-fa96489a-4f82-4da7-80f4-7df16d18b82f')\"\n",
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" width=\"24px\">\n",
" <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
" <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
" </svg>\n",
" </button>\n",
" \n",
" <style>\n",
" .colab-df-container {\n",
" display:flex;\n",
" flex-wrap:wrap;\n",
" gap: 12px;\n",
" }\n",
"\n",
" .colab-df-convert {\n",
" background-color: #E8F0FE;\n",
" border: none;\n",
" border-radius: 50%;\n",
" cursor: pointer;\n",
" display: none;\n",
" fill: #1967D2;\n",
" height: 32px;\n",
" padding: 0 0 0 0;\n",
" width: 32px;\n",
" }\n",
"\n",
" .colab-df-convert:hover {\n",
" background-color: #E2EBFA;\n",
" box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
" fill: #174EA6;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-convert {\n",
" background-color: #3B4455;\n",
" fill: #D2E3FC;\n",
" }\n",
"\n",
" [theme=dark] .colab-df-convert:hover {\n",
" background-color: #434B5C;\n",
" box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
" filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
" fill: #FFFFFF;\n",
" }\n",
" </style>\n",
"\n",
" <script>\n",
" const buttonEl =\n",
" document.querySelector('#df-fa96489a-4f82-4da7-80f4-7df16d18b82f button.colab-df-convert');\n",
" buttonEl.style.display =\n",
" google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
"\n",
" async function convertToInteractive(key) {\n",
" const element = document.querySelector('#df-fa96489a-4f82-4da7-80f4-7df16d18b82f');\n",
" const dataTable =\n",
" await google.colab.kernel.invokeFunction('convertToInteractive',\n",
" [key], {});\n",
" if (!dataTable) return;\n",
"\n",
" const docLinkHtml = 'Like what you see? Visit the ' +\n",
" '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
" + ' to learn more about interactive tables.';\n",
" element.innerHTML = '';\n",
" dataTable['output_type'] = 'display_data';\n",
" await google.colab.output.renderOutput(dataTable, element);\n",
" const docLink = document.createElement('div');\n",
" docLink.innerHTML = docLinkHtml;\n",
" element.appendChild(docLink);\n",
" }\n",
" </script>\n",
" </div>\n",
" </div>\n",
" "
]
},
"metadata": {},
"execution_count": 36
}
]
},
{
"cell_type": "code",
"source": [
"cs.line_plot(global_df, title=\"The number of cases (Global)\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 439
},
"id": "IgnugEw1j1va",
"outputId": "0a9ec3a9-716e-49ed-b044-3f25abe047f3"
},
"execution_count": 35,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"<Figure size 648x432 with 1 Axes>"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
}
]
}
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