Dashboard.run.ipynb

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     "status": "completed"
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    "tags": []
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   "source": [
    "import pandas as pd\n",
    "import os\n",
    "from IPython.display import display, HTML, Markdown"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
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     "duration": 0.02437,
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     "exception": false,
     "start_time": "2020-03-13T17:04:15.082216",
     "status": "completed"
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    "tags": [
     "parameters"
    ]
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   "outputs": [],
   "source": [
    "ts_folder = \"../data/covid-19_jhu-csse/\"\n",
    "rates_folder = \"../data/covid-19_rates/\"\n",
    "out_folder = None\n",
    "PAPERMILL_OUTPUT_PATH = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
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     "end_time": "2020-03-13T17:04:15.137496",
     "exception": false,
     "start_time": "2020-03-13T17:04:15.114850",
     "status": "completed"
    },
    "tags": [
     "injected-parameters"
    ]
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   "outputs": [],
   "source": [
    "# Parameters\n",
    "PAPERMILL_INPUT_PATH = \"notebooks/Dashboard.ipynb\"\n",
    "PAPERMILL_OUTPUT_PATH = \"runs/Dashboard.run.ipynb\"\n",
    "ts_folder = \"./data/covid-19_jhu-csse/\"\n",
    "rates_folder = \"./data/covid-19_rates/\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
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     "duration": 0.021072,
     "end_time": "2020-03-13T17:04:15.168525",
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     "start_time": "2020-03-13T17:04:15.147453",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Read in the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
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     "status": "completed"
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    "tags": []
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   "source": [
    "def read_jhu_covid_df(name):\n",
    "    filename = os.path.join(ts_folder, f\"time_series_19-covid-{name}.csv\")\n",
    "    df = pd.read_csv(filename)\n",
    "    df = df.set_index(['Province/State', 'Country/Region', 'Lat', 'Long'])\n",
    "    df.columns = pd.to_datetime(df.columns)\n",
    "    return df\n",
    "\n",
    "\n",
    "jhu_frames_map = {\n",
    "    \"confirmed\": read_jhu_covid_df(\"Confirmed\"),\n",
    "    \"deaths\": read_jhu_covid_df(\"Deaths\"),\n",
    "    \"recovered\": read_jhu_covid_df(\"Recovered\")\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
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   "source": [
    "def read_rates_covid_df(name):\n",
    "    filename = os.path.join(rates_folder, f\"ts_rates_19-covid-{name}.csv\")\n",
    "    df = pd.read_csv(filename).drop(\"Unnamed: 0\", axis=1)\n",
    "    df = df.set_index(['Country/Region'])\n",
    "    df.columns = pd.to_datetime(df.columns)\n",
    "    return df\n",
    "\n",
    "\n",
    "rates_frames_map = {\n",
    "    \"confirmed\": read_rates_covid_df(\"confirmed\"),\n",
    "    \"deaths\": read_rates_covid_df(\"deaths\"),\n",
    "    \"recovered\": read_rates_covid_df(\"recovered\")\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
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     "duration": 0.017688,
     "end_time": "2020-03-13T17:04:15.314301",
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   "outputs": [],
   "source": [
    "# Compile data needed for the visualizations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
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   "source": [
    "# Compute geospatial coordinates\n",
    "country_coords_df = jhu_frames_map['confirmed'].reset_index([2,3])[['Lat', 'Long']]\n",
    "country_coords_df = country_coords_df.groupby(level='Country/Region').mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
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   "source": [
    "# Identify countries with 100 or more cases\n",
    "case_count_ser = jhu_frames_map['confirmed'].iloc[:,-1].groupby(level='Country/Region').sum()\n",
    "countries_over_thresh = case_count_ser[case_count_ser > 99].index"
   ]
  },
  {
   "cell_type": "markdown",
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     "status": "completed"
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    "tags": []
   },
   "source": [
    "# Questions About COVID-19 and Its Spread\n",
    "\n",
    "These plots should be taken with a large grain of salt. I am not an epidemiologist, so the analyses shown here are completely naive. There are large discrepencies in the data from different countries for a variety of reasons (rates of testing, demographics, etc.) so that make direct comparisons inaccurate. Nonetheless, I think there is a lot of interesting information in this data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
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     "end_time": "2020-03-13T17:04:15.498158",
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   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<em>Data up to Mar 10 2020</em>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_ts = jhu_frames_map['confirmed'].iloc[:,-1].name.strftime(\"%b %d %Y\")\n",
    "display(HTML(f\"<em>Data up to {data_ts}</em>\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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     "status": "completed"
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    "tags": []
   },
   "source": [
    "## How are cases per 100,000 distributed geographically?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
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     "duration": 0.199352,
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import altair as alt\n",
    "from vega_datasets import data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "papermill": {
     "duration": 0.045428,
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   "source": [
    "# Compile the basic df\n",
    "map_df = pd.concat([\n",
    "    rates_frames_map['confirmed'].iloc[:,-1],\n",
    "    rates_frames_map['deaths'].iloc[:,-1],\n",
    "    rates_frames_map['recovered'].iloc[:,-1],\n",
    "    country_coords_df], axis=1)\n",
    "# Restrict to countries with 100 or more cases\n",
    "map_df = map_df.loc[countries_over_thresh].dropna()\n",
    "map_df = map_df.reset_index()\n",
    "map_df.columns = ['Country/Region', 'Confirmed', 'Deaths', 'Recovered', 'Lat', 'Long']"
   ]
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   "source": [
    "def map_of_variable(map_df, variable):\n",
    "    # Data generators for the background\n",
    "    sphere = alt.sphere()\n",
    "    graticule = alt.graticule()\n",
    "\n",
    "    # Source of land data\n",
    "    source = alt.topo_feature(data.world_110m.url, 'countries')\n",
    "\n",
    "    # Layering and configuring the components\n",
    "    p = alt.layer(\n",
    "        alt.Chart(sphere).mark_geoshape(fill='#cae6ef'),\n",
    "        alt.Chart(graticule).mark_geoshape(stroke='white', strokeWidth=0.5),\n",
    "        alt.Chart(source).mark_geoshape(fill='#dddddd', stroke='#aaaaaa'),\n",
    "        alt.Chart(map_df).mark_circle(opacity=0.6).encode(\n",
    "            longitude='Long:Q',\n",
    "            latitude='Lat:Q',\n",
    "            size=alt.Size(f'{variable}:Q', title=\"Cases\"),\n",
    "            color=alt.value('steelblue'),\n",
    "            tooltip=[\"Country/Region:N\", \"Confirmed:Q\", \"Deaths:Q\", \"Recovered:Q\"]\n",
    "        )\n",
    "    ).project(\n",
    "        'naturalEarth1'\n",
    "    ).properties(width=600, height=400, title=f\"{variable} cases per 100,000\"\n",
    "    ).configure_view(stroke=None)\n",
    "    return p"
   ]
  },
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       "\n",
       "<p style=\"font-size: smaller\">Data Source: \n",
       "  <a href=\"https://github.com/CSSEGISandData/COVID-19\">JHU CSSE</a> and\n",
       "  <a href=\"https://data.worldbank.org/indicator/SP.POP.TOTL\">World Bank</a>\n",
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    "display(map_of_variable(map_df, 'Confirmed'))\n",
    "display(HTML('''\n",
    "<p style=\"font-size: smaller\">Data Source: \n",
    "  <a href=\"https://github.com/CSSEGISandData/COVID-19\">JHU CSSE</a> and\n",
    "  <a href=\"https://data.worldbank.org/indicator/SP.POP.TOTL\">World Bank</a>\n",
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       "        document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "      });\n",
       "    }\n",
       "\n",
       "    function showError(err) {\n",
       "      outputDiv.innerHTML = `<div class=\"error\" style=\"color:red;\">${err}</div>`;\n",
       "      throw err;\n",
       "    }\n",
       "\n",
       "    function displayChart(vegaEmbed) {\n",
       "      vegaEmbed(outputDiv, spec, embedOpt)\n",
       "        .catch(err => showError(`Javascript Error: ${err.message}<br>This usually means there's a typo in your chart specification. See the javascript console for the full traceback.`));\n",
       "    }\n",
       "\n",
       "    if(typeof define === \"function\" && define.amd) {\n",
       "      requirejs.config({paths});\n",
       "      require([\"vega-embed\"], displayChart, err => showError(`Error loading script: ${err.message}`));\n",
       "    } else if (typeof vegaEmbed === \"function\") {\n",
       "      displayChart(vegaEmbed);\n",
       "    } else {\n",
       "      loadScript(\"vega\")\n",
       "        .then(() => loadScript(\"vega-lite\"))\n",
       "        .then(() => loadScript(\"vega-embed\"))\n",
       "        .catch(showError)\n",
       "        .then(() => displayChart(vegaEmbed));\n",
       "    }\n",
       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"layer\": [{\"mark\": \"bar\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"field\": \"Confirmed\"}, \"y\": {\"type\": \"nominal\", \"field\": \"Country/Region\", \"sort\": \"-x\"}}}, {\"mark\": {\"type\": \"text\", \"align\": \"left\", \"baseline\": \"middle\", \"dx\": 3}, \"encoding\": {\"text\": {\"type\": \"quantitative\", \"field\": \"Confirmed\", \"format\": \".3\"}, \"x\": {\"type\": \"quantitative\", \"field\": \"Confirmed\"}, \"y\": {\"type\": \"nominal\", \"field\": \"Country/Region\", \"sort\": \"-x\"}}}], \"data\": {\"name\": \"data-433f706ddfa6221156e78c265aebad1f\"}, \"height\": 900, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.0.2.json\", \"datasets\": {\"data-433f706ddfa6221156e78c265aebad1f\": [{\"Country/Region\": \"Australia\", \"Confirmed\": 0.4281306826095598, \"Deaths\": 0.012003663998398872, \"Recovered\": 0.0840256479887921, \"Lat\": -23.1315375, \"Long\": 140.0609875}, {\"Country/Region\": \"Austria\", \"Confirmed\": 2.057185925638154, \"Deaths\": 0.0, \"Recovered\": 0.04521287748655284, \"Lat\": 47.5162, \"Long\": 14.5501}, {\"Country/Region\": \"Bahrain\", \"Confirmed\": 7.00887387149166, \"Deaths\": 0.0, \"Recovered\": 1.4017747742983322, \"Lat\": 26.0275, \"Long\": 50.55}, {\"Country/Region\": \"Belgium\", \"Confirmed\": 2.3375802000128174, \"Deaths\": 0.0, \"Recovered\": 0.008754982022519914, \"Lat\": 50.8333, \"Long\": 4.0}, {\"Country/Region\": \"Denmark\", \"Confirmed\": 4.519231399481772, \"Deaths\": 0.0, \"Recovered\": 0.01724897480718234, \"Lat\": 56.2639, \"Long\": 9.5018}, {\"Country/Region\": \"France\", \"Confirmed\": 2.663193607427707, \"Deaths\": 0.04926311045129727, \"Recovered\": 0.017913858345926282, \"Lat\": 47.0, \"Long\": 2.0}, {\"Country/Region\": \"Germany\", \"Confirmed\": 1.7569474368355689, \"Deaths\": 0.0024117329263357162, \"Recovered\": 0.021705596337021446, \"Lat\": 51.0, \"Long\": 9.0}, {\"Country/Region\": \"Hong Kong SAR\", \"Confirmed\": 1.61052207757348, \"Deaths\": 0.040263051939337005, \"Recovered\": 0.8723661253523016, \"Lat\": 22.3, \"Long\": 114.2}, {\"Country/Region\": \"Iran (Islamic Republic of)\", \"Confirmed\": 9.831263513326588, \"Deaths\": 0.3557445514023921, \"Recovered\": 3.3386198277660917, \"Lat\": 32.0, \"Long\": 53.0}, {\"Country/Region\": \"Italy\", \"Confirmed\": 16.794281862259982, \"Deaths\": 1.0441611838689575, \"Recovered\": 1.198054987513669, \"Lat\": 43.0, \"Long\": 12.0}, {\"Country/Region\": \"Japan\", \"Confirmed\": 0.4591829073311989, \"Deaths\": 0.007903320263876057, \"Recovered\": 0.07982353466514817, \"Lat\": 36.0, \"Long\": 138.0}, {\"Country/Region\": \"Mainland China\", \"Confirmed\": 5.798467757569664, \"Deaths\": 0.2251692718617392, \"Recovered\": 4.315696509732684, \"Lat\": 33.40693612903227, \"Long\": 111.54290322580646}, {\"Country/Region\": \"Malaysia\", \"Confirmed\": 0.4091525198482584, \"Deaths\": 0.0, \"Recovered\": 0.07612139904153642, \"Lat\": 2.5, \"Long\": 112.5}, {\"Country/Region\": \"Netherlands\", \"Confirmed\": 2.216932407413909, \"Deaths\": 0.02321395191009329, \"Recovered\": 0.0, \"Lat\": 52.1326, \"Long\": 5.2913}, {\"Country/Region\": \"Norway\", \"Confirmed\": 7.526810498997428, \"Deaths\": 0.0, \"Recovered\": 0.018817026247493568, \"Lat\": 60.472, \"Long\": 8.4689}, {\"Country/Region\": \"Republic of Korea\", \"Confirmed\": 14.550136054326911, \"Deaths\": 0.10457970809711876, \"Recovered\": 0.4783553314812655, \"Lat\": 36.0, \"Long\": 128.0}, {\"Country/Region\": \"Singapore\", \"Confirmed\": 2.837545551473431, \"Deaths\": 0.0, \"Recovered\": 1.3833034563432978, \"Lat\": 1.2833, \"Long\": 103.8333}, {\"Country/Region\": \"Spain\", \"Confirmed\": 3.6277054737195855, \"Deaths\": 0.07490837261367876, \"Recovered\": 0.06848765496107773, \"Lat\": 40.0, \"Long\": -4.0}, {\"Country/Region\": \"Sweden\", \"Confirmed\": 3.4861425832316537, \"Deaths\": 0.0, \"Recovered\": 0.009820119952765223, \"Lat\": 63.0, \"Long\": 16.0}, {\"Country/Region\": \"Switzerland\", \"Confirmed\": 5.7652500550986465, \"Deaths\": 0.035225560418118015, \"Recovered\": 0.035225560418118015, \"Lat\": 46.8182, \"Long\": 8.2275}, {\"Country/Region\": \"UK\", \"Confirmed\": 0.5745312032182892, \"Deaths\": 0.009024050312329149, \"Recovered\": 0.027072150936987446, \"Lat\": 55.0, \"Long\": -3.0}, {\"Country/Region\": \"US\", \"Confirmed\": 0.5104420019995022, \"Deaths\": 0.017116618031121033, \"Recovered\": 0.004584808401193134, \"Lat\": 38.77302746113991, \"Long\": -93.61047823834195}]}}, {\"mode\": \"vega-lite\"});\n",
       "</script>"
      ],
      "text/plain": [
       "alt.LayerChart(...)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bars = alt.Chart(map_df).mark_bar().encode(\n",
    "    x='Confirmed:Q',\n",
    "    y=alt.Y(\"Country/Region:N\", sort='-x')\n",
    ")\n",
    "\n",
    "text = bars.mark_text(\n",
    "    align='left',\n",
    "    baseline='middle',\n",
    "    dx=3  # Nudges text to right so it doesn't appear on top of the bar\n",
    ").encode(\n",
    "    text=alt.Text('Confirmed:Q', format=\".3\")\n",
    ")\n",
    "\n",
    "(bars + text).properties(height=900)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  },
  "papermill": {
   "duration": 2.520956,
   "end_time": "2020-03-13T17:04:16.371464",
   "environment_variables": {},
   "exception": null,
   "input_path": "notebooks/Dashboard.ipynb",
   "output_path": "runs/Dashboard.run.ipynb",
   "parameters": {
    "PAPERMILL_INPUT_PATH": "notebooks/Dashboard.ipynb",
    "PAPERMILL_OUTPUT_PATH": "runs/Dashboard.run.ipynb",
    "rates_folder": "./data/covid-19_rates/",
    "ts_folder": "./data/covid-19_jhu-csse/"
   },
   "start_time": "2020-03-13T17:04:13.850508",
   "version": "1.1.0"
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