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{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "papermill": {
     "duration": 0.318369,
     "end_time": "2020-03-13T17:58:07.699048",
     "start_time": "2020-03-13T17:58:07.380679",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os\n",
    "from IPython.display import display, HTML, Markdown"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "papermill": {
     "duration": 0.02116,
     "end_time": "2020-03-13T17:58:07.739632",
     "start_time": "2020-03-13T17:58:07.718472",
     "status": "completed"
    },
    "tags": [
     "parameters"
    ]
   },
   "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": {
    "papermill": {
     "duration": 0.021777,
     "end_time": "2020-03-13T17:58:07.771101",
     "start_time": "2020-03-13T17:58:07.749324",
     "status": "completed"
    },
    "tags": [
     "injected-parameters"
    ]
   },
   "outputs": [],
   "source": [
    "# Parameters\n",
    "PAPERMILL_INPUT_PATH = \"/tmp/ajs106te/notebooks/Dashboard.ipynb\"\n",
    "PAPERMILL_OUTPUT_PATH = \"runs/Dashboard.run.ipynb\"\n",
    "ts_folder = \"/tmp/ajs106te/data/covid-19_jhu-csse\"\n",
    "rates_folder = \"/tmp/ajs106te/data/covid-19_rates\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "papermill": {
     "duration": 0.020625,
     "end_time": "2020-03-13T17:58:07.801350",
     "start_time": "2020-03-13T17:58:07.780725",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Read in the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "papermill": {
     "duration": 0.088499,
     "end_time": "2020-03-13T17:58:07.900202",
     "start_time": "2020-03-13T17:58:07.811703",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "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": {
    "papermill": {
     "duration": 0.046747,
     "end_time": "2020-03-13T17:58:07.960957",
     "start_time": "2020-03-13T17:58:07.914210",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "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": {
    "papermill": {
     "duration": 0.019568,
     "end_time": "2020-03-13T17:58:07.999627",
     "start_time": "2020-03-13T17:58:07.980059",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Compile data needed for the visualizations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "papermill": {
     "duration": 0.03619,
     "end_time": "2020-03-13T17:58:08.046674",
     "start_time": "2020-03-13T17:58:08.010484",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "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": {
    "papermill": {
     "duration": 0.036248,
     "end_time": "2020-03-13T17:58:08.099308",
     "start_time": "2020-03-13T17:58:08.063060",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "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",
   "metadata": {
    "papermill": {
     "duration": 0.009486,
     "end_time": "2020-03-13T17:58:08.127085",
     "start_time": "2020-03-13T17:58:08.117599",
     "status": "completed"
    },
    "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": {
    "papermill": {
     "duration": 0.043858,
     "end_time": "2020-03-13T17:58:08.178940",
     "start_time": "2020-03-13T17:58:08.135082",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<em>Data up to Mar 12 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": {
    "papermill": {
     "duration": 0.009732,
     "end_time": "2020-03-13T17:58:08.205403",
     "start_time": "2020-03-13T17:58:08.195671",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## How are cases per 100,000 distributed geographically?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "papermill": {
     "duration": 0.215996,
     "end_time": "2020-03-13T17:58:08.429475",
     "start_time": "2020-03-13T17:58:08.213479",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import altair as alt\n",
    "from vega_datasets import data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "papermill": {
     "duration": 0.040087,
     "end_time": "2020-03-13T17:58:08.490379",
     "start_time": "2020-03-13T17:58:08.450292",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "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']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "papermill": {
     "duration": 0.034884,
     "end_time": "2020-03-13T17:58:08.543325",
     "start_time": "2020-03-13T17:58:08.508441",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "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"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "papermill": {
     "duration": 0.103115,
     "end_time": "2020-03-13T17:58:08.660915",
     "start_time": "2020-03-13T17:58:08.557800",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
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\"Belgium\", \"Confirmed\": 2.749064355071253, \"Deaths\": 0.026264946067559743, \"Recovered\": 0.008754982022519914, \"Lat\": 50.8333, \"Long\": 4.0}, {\"Country/Region\": \"Canada\", \"Confirmed\": 0.3157140090886777, \"Deaths\": 0.002698410334091263, \"Recovered\": 0.021587282672730104, \"Lat\": 50.795, \"Long\": -93.00628}, {\"Country/Region\": \"Denmark\", \"Confirmed\": 10.6426174560315, \"Deaths\": 0.0, \"Recovered\": 0.01724897480718234, \"Lat\": 59.07825, \"Long\": 1.2949999999999995}, {\"Country/Region\": \"France\", \"Confirmed\": 3.4096043718413016, \"Deaths\": 0.07165543338370511, \"Recovered\": 0.017913858345926282, \"Lat\": 27.399466666666665, \"Long\": -41.22323333333333}, {\"Country/Region\": \"Germany\", \"Confirmed\": 2.5057905104628087, \"Deaths\": 0.0036175993895035743, \"Recovered\": 0.03014666157919645, \"Lat\": 51.0, \"Long\": 9.0}, {\"Country/Region\": \"Iceland\", \"Confirmed\": 29.13110126875845, \"Deaths\": 0.0, \"Recovered\": 0.28282622591027623, \"Lat\": 64.9631, \"Long\": -19.0208}, {\"Country/Region\": \"Israel\", \"Confirmed\": 1.4745942051824668, \"Deaths\": 0.0, \"Recovered\": 0.045025777257479915, \"Lat\": 31.0, \"Long\": 35.0}, {\"Country/Region\": \"Italy\", \"Confirmed\": 20.62176968839136, \"Deaths\": 1.368496511980393, \"Recovered\": 1.7292368259002542, \"Lat\": 43.0, \"Long\": 12.0}, {\"Country/Region\": \"Japan\", \"Confirmed\": 0.5050221648616801, \"Deaths\": 0.012645312422201693, \"Recovered\": 0.09325917911373748, \"Lat\": 36.0, \"Long\": 138.0}, {\"Country/Region\": \"Malaysia\", \"Confirmed\": 0.4725870190495387, \"Deaths\": 0.0, \"Recovered\": 0.08246484896166446, \"Lat\": 2.5, \"Long\": 112.5}, {\"Country/Region\": \"Netherlands\", \"Confirmed\": 2.919154452694232, \"Deaths\": 0.02901743988761661, \"Recovered\": 0.0, \"Lat\": 52.1326, \"Long\": 5.2913}, {\"Country/Region\": \"Norway\", \"Confirmed\": 13.209552425740487, \"Deaths\": 0.0, \"Recovered\": 0.018817026247493568, \"Lat\": 60.472, \"Long\": 8.4689}, {\"Country/Region\": \"Qatar\", \"Confirmed\": 9.418778672002537, \"Deaths\": 0.0, \"Recovered\": 0.0, \"Lat\": 25.3548, \"Long\": 51.1839}, {\"Country/Region\": \"Singapore\", \"Confirmed\": 3.156769426014192, \"Deaths\": 0.0, \"Recovered\": 1.7025273308840587, \"Lat\": 1.2833, \"Long\": 103.8333}, {\"Country/Region\": \"Spain\", \"Confirmed\": 4.873324698324187, \"Deaths\": 0.11771315696435232, \"Recovered\": 0.3916637768086632, \"Lat\": 40.0, \"Long\": -4.0}, {\"Country/Region\": \"Sweden\", \"Confirmed\": 5.882251851706369, \"Deaths\": 0.009820119952765223, \"Recovered\": 0.009820119952765223, \"Lat\": 63.0, \"Long\": 16.0}, {\"Country/Region\": \"Switzerland\", \"Confirmed\": 7.655688464204314, \"Deaths\": 0.04696741389082401, \"Recovered\": 0.04696741389082401, \"Lat\": 46.8182, \"Long\": 8.2275}, {\"Country/Region\": \"US\", \"Confirmed\": 0.508302424745612, \"Deaths\": 0.012226155736515023, \"Recovered\": 0.0036678467209545055, \"Lat\": 38.88347448559672, \"Long\": 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      "text/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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    "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",
    "</p>'''))"
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     "status": "completed"
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   "outputs": [
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       "    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: ${err.message}`));\n",
       "    } else if (typeof vegaEmbed === \"function\") {\n",
       "      displayChart(vegaEmbed);\n",
       "    } else {\n",
       "      loadScript(\"vega\")\n",
       "        .then(() => loadScript(\"vega-lite\"))\n",
       "        .then(() => loadScript(\"vega-embed\"))\n",
       "        .catch(showError)\n",
       "        .then(() => displayChart(vegaEmbed));\n",
       "    }\n",
       "  })({\"config\": {\"view\": {\"continuousWidth\": 400, \"continuousHeight\": 300}}, \"layer\": [{\"mark\": \"bar\", \"encoding\": {\"x\": {\"type\": \"quantitative\", \"field\": \"Confirmed\"}, \"y\": {\"type\": \"nominal\", \"field\": \"Country/Region\", \"sort\": \"-x\"}}}, {\"mark\": {\"type\": \"text\", \"align\": \"left\", \"baseline\": \"middle\", \"dx\": 3}, \"encoding\": {\"text\": {\"type\": \"quantitative\", \"field\": \"Confirmed\", \"format\": \".3\"}, \"x\": {\"type\": \"quantitative\", \"field\": \"Confirmed\"}, \"y\": {\"type\": \"nominal\", \"field\": \"Country/Region\", \"sort\": \"-x\"}}}], \"data\": {\"name\": \"data-af06d21f07e2679aa76ca6a14f5f1418\"}, \"height\": 900, \"$schema\": \"https://vega.github.io/schema/vega-lite/v4.0.2.json\", \"datasets\": {\"data-af06d21f07e2679aa76ca6a14f5f1418\": [{\"Country/Region\": \"Australia\", \"Confirmed\": 0.5121563305983519, \"Deaths\": 0.012003663998398872, \"Recovered\": 0.0840256479887921, \"Lat\": -23.1315375, \"Long\": 140.0609875}, {\"Country/Region\": \"Austria\", \"Confirmed\": 3.4135722502347403, \"Deaths\": 0.01130321937163821, \"Recovered\": 0.04521287748655284, \"Lat\": 47.5162, \"Long\": 14.5501}, {\"Country/Region\": \"Bahrain\", \"Confirmed\": 12.424821863098854, \"Deaths\": 0.0, \"Recovered\": 2.230096231838256, \"Lat\": 26.0275, \"Long\": 50.55}, {\"Country/Region\": \"Belgium\", \"Confirmed\": 2.749064355071253, \"Deaths\": 0.026264946067559743, \"Recovered\": 0.008754982022519914, \"Lat\": 50.8333, \"Long\": 4.0}, {\"Country/Region\": \"Canada\", \"Confirmed\": 0.3157140090886777, \"Deaths\": 0.002698410334091263, \"Recovered\": 0.021587282672730104, \"Lat\": 50.795, \"Long\": -93.00628}, {\"Country/Region\": \"Denmark\", \"Confirmed\": 10.6426174560315, \"Deaths\": 0.0, \"Recovered\": 0.01724897480718234, \"Lat\": 59.07825, \"Long\": 1.2949999999999995}, {\"Country/Region\": \"France\", \"Confirmed\": 3.4096043718413016, \"Deaths\": 0.07165543338370511, \"Recovered\": 0.017913858345926282, \"Lat\": 27.399466666666665, \"Long\": -41.22323333333333}, {\"Country/Region\": \"Germany\", \"Confirmed\": 2.5057905104628087, \"Deaths\": 0.0036175993895035743, \"Recovered\": 0.03014666157919645, \"Lat\": 51.0, \"Long\": 9.0}, {\"Country/Region\": \"Iceland\", \"Confirmed\": 29.13110126875845, \"Deaths\": 0.0, \"Recovered\": 0.28282622591027623, \"Lat\": 64.9631, \"Long\": -19.0208}, {\"Country/Region\": \"Israel\", \"Confirmed\": 1.4745942051824668, \"Deaths\": 0.0, \"Recovered\": 0.045025777257479915, \"Lat\": 31.0, \"Long\": 35.0}, {\"Country/Region\": \"Italy\", \"Confirmed\": 20.62176968839136, \"Deaths\": 1.368496511980393, \"Recovered\": 1.7292368259002542, \"Lat\": 43.0, \"Long\": 12.0}, {\"Country/Region\": \"Japan\", \"Confirmed\": 0.5050221648616801, \"Deaths\": 0.012645312422201693, \"Recovered\": 0.09325917911373748, \"Lat\": 36.0, \"Long\": 138.0}, {\"Country/Region\": \"Malaysia\", \"Confirmed\": 0.4725870190495387, \"Deaths\": 0.0, \"Recovered\": 0.08246484896166446, \"Lat\": 2.5, \"Long\": 112.5}, {\"Country/Region\": \"Netherlands\", \"Confirmed\": 2.919154452694232, \"Deaths\": 0.02901743988761661, \"Recovered\": 0.0, \"Lat\": 52.1326, \"Long\": 5.2913}, {\"Country/Region\": \"Norway\", \"Confirmed\": 13.209552425740487, \"Deaths\": 0.0, \"Recovered\": 0.018817026247493568, \"Lat\": 60.472, \"Long\": 8.4689}, {\"Country/Region\": \"Qatar\", \"Confirmed\": 9.418778672002537, \"Deaths\": 0.0, \"Recovered\": 0.0, \"Lat\": 25.3548, \"Long\": 51.1839}, {\"Country/Region\": \"Singapore\", \"Confirmed\": 3.156769426014192, \"Deaths\": 0.0, \"Recovered\": 1.7025273308840587, \"Lat\": 1.2833, \"Long\": 103.8333}, {\"Country/Region\": \"Spain\", \"Confirmed\": 4.873324698324187, \"Deaths\": 0.11771315696435232, \"Recovered\": 0.3916637768086632, \"Lat\": 40.0, \"Long\": -4.0}, {\"Country/Region\": \"Sweden\", \"Confirmed\": 5.882251851706369, \"Deaths\": 0.009820119952765223, \"Recovered\": 0.009820119952765223, \"Lat\": 63.0, \"Long\": 16.0}, {\"Country/Region\": \"Switzerland\", \"Confirmed\": 7.655688464204314, \"Deaths\": 0.04696741389082401, \"Recovered\": 0.04696741389082401, \"Lat\": 46.8182, \"Long\": 8.2275}, {\"Country/Region\": \"US\", \"Confirmed\": 0.508302424745612, \"Deaths\": 0.012226155736515023, \"Recovered\": 0.0036678467209545055, \"Lat\": 38.88347448559672, \"Long\": -94.14907777777768}]}}, {\"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"
  },
  "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": 2.508313,
   "end_time": "2020-03-13T17:58:09.048792",
   "input_path": "/tmp/ajs106te/notebooks/Dashboard.ipynb",
   "output_path": "runs/Dashboard.run.ipynb",
   "parameters": {
    "PAPERMILL_INPUT_PATH": "/tmp/ajs106te/notebooks/Dashboard.ipynb",
    "PAPERMILL_OUTPUT_PATH": "runs/Dashboard.run.ipynb",
    "rates_folder": "/tmp/ajs106te/data/covid-19_rates",
    "ts_folder": "/tmp/ajs106te/data/covid-19_jhu-csse"
   "start_time": "2020-03-13T17:58:06.540479",