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   "execution_count": 60,
   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'matplotlib'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-60-ffb398b1b277>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mpandas\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0maltair\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0malt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'matplotlib'"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import altair as alt\n",
    "import matplotlib"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Look at the metadata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "metadata_df = pd.read_json('../../data/covidtracking/states-metadata.json')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>state</th>\n",
       "      <th>covid19SiteOld</th>\n",
       "      <th>covid19SiteSecondary</th>\n",
       "      <th>twitter</th>\n",
       "      <th>pui</th>\n",
       "      <th>pum</th>\n",
       "      <th>notes</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AK</td>\n",
       "      <td>http://dhss.alaska.gov/dph/Epi/id/Pages/COVID-...</td>\n",
       "      <td>http://dhss.alaska.gov/dph/Epi/id/Pages/COVID-...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>@Alaska_DHSS</td>\n",
       "      <td>All data</td>\n",
       "      <td>False</td>\n",
       "      <td>Unclear if their reported number means \"person...</td>\n",
       "      <td>Alaska</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AL</td>\n",
       "      <td>http://www.alabamapublichealth.gov/infectiousd...</td>\n",
       "      <td>https://alpublichealth.maps.arcgis.com/apps/op...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>@alpublichealth</td>\n",
       "      <td>No data</td>\n",
       "      <td>False</td>\n",
       "      <td>Last negative count from 3/16.</td>\n",
       "      <td>Alabama</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AR</td>\n",
       "      <td>https://www.healthy.arkansas.gov/programs-serv...</td>\n",
       "      <td>https://www.healthy.arkansas.gov/programs-serv...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>@adhpio</td>\n",
       "      <td>All data</td>\n",
       "      <td>True</td>\n",
       "      <td>Pending = \"PUIs\"</td>\n",
       "      <td>Arkansas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AZ</td>\n",
       "      <td>https://www.azdhs.gov/preparedness/epidemiolog...</td>\n",
       "      <td>https://www.azdhs.gov/preparedness/epidemiolog...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>@azdhs</td>\n",
       "      <td>All data</td>\n",
       "      <td>False</td>\n",
       "      <td>Negative = “Ruled Out”. Our total is slightly ...</td>\n",
       "      <td>Arizona</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CA</td>\n",
       "      <td>https://www.cdph.ca.gov/Programs/CID/DCDC/Page...</td>\n",
       "      <td>https://www.latimes.com/projects/california-co...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>@CAPublicHealth</td>\n",
       "      <td>Only positives</td>\n",
       "      <td>False</td>\n",
       "      <td>Only positives reported regularly. Add deaths ...</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  state                                     covid19SiteOld  \\\n",
       "0    AK  http://dhss.alaska.gov/dph/Epi/id/Pages/COVID-...   \n",
       "1    AL  http://www.alabamapublichealth.gov/infectiousd...   \n",
       "2    AR  https://www.healthy.arkansas.gov/programs-serv...   \n",
       "3    AZ  https://www.azdhs.gov/preparedness/epidemiolog...   \n",
       "4    CA  https://www.cdph.ca.gov/Programs/CID/DCDC/Page...   \n",
       "\n",
       "                                         covid19Site  covid19SiteSecondary  \\\n",
       "0  http://dhss.alaska.gov/dph/Epi/id/Pages/COVID-...                   NaN   \n",
       "1  https://alpublichealth.maps.arcgis.com/apps/op...                   NaN   \n",
       "2  https://www.healthy.arkansas.gov/programs-serv...                   NaN   \n",
       "3  https://www.azdhs.gov/preparedness/epidemiolog...                   NaN   \n",
       "4  https://www.latimes.com/projects/california-co...                   NaN   \n",
       "           twitter             pui    pum  \\\n",
       "0     @Alaska_DHSS        All data  False   \n",
       "1  @alpublichealth         No data  False   \n",
       "2          @adhpio        All data   True   \n",
       "3           @azdhs        All data  False   \n",
       "4  @CAPublicHealth  Only positives  False   \n",
       "                                               notes        name  \n",
       "0  Unclear if their reported number means \"person...      Alaska  \n",
       "1                     Last negative count from 3/16.     Alabama  \n",
       "2                                   Pending = \"PUIs\"    Arkansas  \n",
       "3  Negative = “Ruled Out”. Our total is slightly ...     Arizona  \n",
       "4  Only positives reported regularly. Add deaths ...  California  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metadata_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Look at the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_df = pd.read_json('../../data/covidtracking/states-daily.json')\n",
    "data_df['date'] = pd.to_datetime(data_df['date'], format=\"%Y%m%d\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>state</th>\n",
       "      <th>positive</th>\n",
       "      <th>negative</th>\n",
       "      <th>pending</th>\n",
       "      <th>death</th>\n",
       "      <th>total</th>\n",
       "      <th>dateChecked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-03-19</td>\n",
       "      <td>6</td>\n",
       "      <td>400.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>406</td>\n",
       "      <td>2020-03-19T20:00:00Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-03-19</td>\n",
       "      <td>68</td>\n",
       "      <td>28.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>96</td>\n",
       "      <td>2020-03-19T20:00:00Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-03-19</td>\n",
       "      <td>46</td>\n",
       "      <td>310.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>469</td>\n",
       "      <td>2020-03-19T20:00:00Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-03-19</td>\n",
       "      <td>AS</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2020-03-19T20:00:00Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-03-19</td>\n",
       "      <td>AZ</td>\n",
       "      <td>44</td>\n",
       "      <td>175.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>349</td>\n",
       "      <td>2020-03-19T20:00:00Z</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date state  positive  negative  pending  death  total  \\\n",
       "0 2020-03-19    AK         6     400.0      NaN    NaN    406   \n",
       "1 2020-03-19    AL        68      28.0      NaN    0.0     96   \n",
       "2 2020-03-19    AR        46     310.0    113.0    NaN    469   \n",
       "3 2020-03-19    AS         0       NaN      NaN    0.0      0   \n",
       "4 2020-03-19    AZ        44     175.0    130.0    0.0    349   \n",
       "0  2020-03-19T20:00:00Z  \n",
       "1  2020-03-19T20:00:00Z  \n",
       "2  2020-03-19T20:00:00Z  \n",
       "3  2020-03-19T20:00:00Z  \n",
       "4  2020-03-19T20:00:00Z  "
     "execution_count": 223,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Daily counts and totals"
   "execution_count": 257,
   "metadata": {},
   "outputs": [],
   "source": [
    "# compute daily differences\n",
    "tdf = data_df.sort_values(['state', 'date'], ascending=[True, False]).set_index(['state', 'date'])\n",
    "diffs_df = tdf[['positive', 'negative', 'death']].groupby(level='state').diff(periods=-1).dropna(how='all')\n",
    "tdf_diff=tdf.join(diffs_df, rsuffix='_diff').reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 276,
   "metadata": {},
   "outputs": [],
   "source": [
    "# \"Normalizing\" the totals\n",
    "tdf_diff['total_10'] = tdf_diff['total']/10."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 278,
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:7: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  import sys\n",
      "/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:9: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  if __name__ == '__main__':\n"
     ]
    },
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\"positive_diff\": 108.0, \"negative_diff\": 1535.0, \"death_diff\": 4.0, \"total_10\": 1412.9, \"daily_positive\": 108.0}, {\"state\": \"WA\", \"date\": \"2020-03-17T00:00:00\", \"positive\": 904, \"negative\": 11582.0, \"pending\": null, \"death\": 48.0, \"total\": 12486, \"dateChecked\": \"2020-03-17T20:00:00Z\", \"positive_diff\": 135.0, \"negative_diff\": 2131.0, \"death_diff\": 6.0, \"total_10\": 1248.6, \"daily_positive\": 135.0}, {\"state\": \"WA\", \"date\": \"2020-03-16T00:00:00\", \"positive\": 769, \"negative\": 9451.0, \"pending\": null, \"death\": 42.0, \"total\": 10220, \"dateChecked\": \"2020-03-16T20:00:00Z\", \"positive_diff\": 127.0, \"negative_diff\": 2329.0, \"death_diff\": 2.0, \"total_10\": 1022.0, \"daily_positive\": 127.0}, {\"state\": \"WA\", \"date\": \"2020-03-15T00:00:00\", \"positive\": 642, \"negative\": 7122.0, \"pending\": null, \"death\": 40.0, \"total\": 7764, \"dateChecked\": \"2020-03-15T20:00:00Z\", \"positive_diff\": 74.0, \"negative_diff\": 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\"positive_diff\": 0.0, \"negative_diff\": null, \"death_diff\": null, \"total_10\": 21.6, \"daily_positive\": 0.0}, {\"state\": \"NY\", \"date\": \"2020-03-11T00:00:00\", \"positive\": 216, \"negative\": null, \"pending\": null, \"death\": null, \"total\": 216, \"dateChecked\": \"2020-03-11T20:00:00Z\", \"positive_diff\": 43.0, \"negative_diff\": null, \"death_diff\": null, \"total_10\": 21.6, \"daily_positive\": 43.0}, {\"state\": \"NY\", \"date\": \"2020-03-10T00:00:00\", \"positive\": 173, \"negative\": 92.0, \"pending\": null, \"death\": null, \"total\": 265, \"dateChecked\": \"2020-03-10T20:00:00Z\", \"positive_diff\": 31.0, \"negative_diff\": 0.0, \"death_diff\": null, \"total_10\": 26.5, \"daily_positive\": 31.0}, {\"state\": \"NY\", \"date\": \"2020-03-09T00:00:00\", \"positive\": 142, \"negative\": 92.0, \"pending\": null, \"death\": null, \"total\": 234, \"dateChecked\": \"2020-03-09T20:00:00Z\", \"positive_diff\": 37.0, \"negative_diff\": 0.0, \"death_diff\": null, \"total_10\": 23.4, \"daily_positive\": 37.0}, {\"state\": \"NY\", \"date\": \"2020-03-08T00:00:00\", \"positive\": 105, \"negative\": 92.0, \"pending\": null, \"death\": null, \"total\": 197, \"dateChecked\": \"2020-03-08T21:00:00Z\", \"positive_diff\": 29.0, \"negative_diff\": 0.0, \"death_diff\": null, \"total_10\": 19.7, \"daily_positive\": 29.0}, {\"state\": \"NY\", \"date\": \"2020-03-07T00:00:00\", \"positive\": 76, \"negative\": 92.0, \"pending\": 236.0, \"death\": null, \"total\": 404, \"dateChecked\": \"2020-03-07T21:00:00Z\", \"positive_diff\": 43.0, \"negative_diff\": 0.0, \"death_diff\": null, \"total_10\": 40.4, \"daily_positive\": 43.0}, {\"state\": \"NY\", \"date\": \"2020-03-06T00:00:00\", \"positive\": 33, \"negative\": 92.0, \"pending\": 236.0, \"death\": null, \"total\": 361, \"dateChecked\": \"2020-03-06T21:00:00Z\", \"positive_diff\": 11.0, \"negative_diff\": 16.0, \"death_diff\": null, \"total_10\": 36.1, \"daily_positive\": 11.0}, {\"state\": \"NY\", \"date\": \"2020-03-05T00:00:00\", \"positive\": 22, \"negative\": 76.0, \"pending\": 24.0, \"death\": null, \"total\": 122, \"dateChecked\": \"2020-03-05T21:00:00Z\", \"positive_diff\": 16.0, \"negative_diff\": 28.0, \"death_diff\": null, \"total_10\": 12.2, \"daily_positive\": 16.0}, {\"state\": \"NY\", \"date\": \"2020-03-04T00:00:00\", \"positive\": 6, \"negative\": 48.0, \"pending\": 24.0, \"death\": null, \"total\": 78, \"dateChecked\": \"2020-03-04T21:00:00Z\", \"positive_diff\": null, \"negative_diff\": null, \"death_diff\": null, \"total_10\": 7.8, \"daily_positive\": null}]}}, {\"mode\": \"vega-lite\"});\n",
       "</script>"
       "alt.HConcatChart(...)"
     "execution_count": 278,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# produce the charts for a few states\n",
    "\n",
    "charts=[]\n",
    "for state in ['WA', 'CA', 'NY']: \n",
    "    state_df = tdf_diff[tdf_diff['state'] == state]\n",
    "\n",
    "    state_df['daily_positive'] = state_df['positive'][::-1].diff()\n",
    "\n",
    "    state_df['total_10'] = state_df['total']/10.\n",
    "\n",
    "    base = alt.Chart(state_df, title=state).encode(alt.X('date', axis=alt.Axis(title='Date'))).properties(width=250, height=150)\n",
    "    dailies = base.mark_bar(size=10).encode(alt.Y('daily_positive', axis=alt.Axis(title='Daily positive')))\n",
    "\n",
    "    totals = base.mark_line(color='red').encode(alt.Y('total_10', axis=alt.Axis(title='Total/10'))) \n",
    "    positives = totals.mark_line(color='orange').encode(alt.Y('positive', axis=alt.Axis(title='Positive')))\n",
    "    cumulative = totals + positives\n",
    "\n",
    "    charts.append(alt.layer(dailies, cumulative).resolve_scale(y='independent'))\n",
    "\n",
    "\n",
    "alt.hconcat(*charts)"
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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