{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "# Stuff that will appear at the top of notebooks;\n",
    "\n",
    "from datascience import *\n",
    "import numpy as np\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plots\n",
    "plots.style.use('fivethirtyeight')\n",
    "import warnings\n",
    "warnings.simplefilter(action=\"ignore\", category=FutureWarning)\n",
    "\n",
    "from urllib.request import urlopen \n",
    "import re\n",
    "def read_url(url): \n",
    "    return re.sub('\\\\s+', ' ', urlopen(url).read().decode())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>Data As Of</th> <th>Start Date</th> <th>End Date</th> <th>Group</th> <th>Year</th> <th>Month</th> <th>State</th> <th>Sex</th> <th>Age Group</th> <th>COVID-19 Deaths</th> <th>Total Deaths</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>4/28/2021 </td> <td>1/1/2020  </td> <td>4/24/2021</td> <td>By Total</td> <td>nan </td> <td>nan  </td> <td>United States</td> <td>All Sexes</td> <td>All Ages    </td> <td>557486         </td> <td>4.35558e+06 </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>4/28/2021 </td> <td>1/1/2020  </td> <td>4/24/2021</td> <td>By Total</td> <td>nan </td> <td>nan  </td> <td>United States</td> <td>All Sexes</td> <td>Under 1 year</td> <td>66             </td> <td>23862       </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>4/28/2021 </td> <td>1/1/2020  </td> <td>4/24/2021</td> <td>By Total</td> <td>nan </td> <td>nan  </td> <td>United States</td> <td>All Sexes</td> <td>0-17 years  </td> <td>277            </td> <td>41811       </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>4/28/2021 </td> <td>1/1/2020  </td> <td>4/24/2021</td> <td>By Total</td> <td>nan </td> <td>nan  </td> <td>United States</td> <td>All Sexes</td> <td>1-4 years   </td> <td>34             </td> <td>4286        </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>4/28/2021 </td> <td>1/1/2020  </td> <td>4/24/2021</td> <td>By Total</td> <td>nan </td> <td>nan  </td> <td>United States</td> <td>All Sexes</td> <td>5-14 years  </td> <td>98             </td> <td>6930        </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>4/28/2021 </td> <td>1/1/2020  </td> <td>4/24/2021</td> <td>By Total</td> <td>nan </td> <td>nan  </td> <td>United States</td> <td>All Sexes</td> <td>15-24 years </td> <td>844            </td> <td>44906       </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>4/28/2021 </td> <td>1/1/2020  </td> <td>4/24/2021</td> <td>By Total</td> <td>nan </td> <td>nan  </td> <td>United States</td> <td>All Sexes</td> <td>18-29 years </td> <td>2097           </td> <td>79315       </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>4/28/2021 </td> <td>1/1/2020  </td> <td>4/24/2021</td> <td>By Total</td> <td>nan </td> <td>nan  </td> <td>United States</td> <td>All Sexes</td> <td>25-34 years </td> <td>3741           </td> <td>92911       </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>4/28/2021 </td> <td>1/1/2020  </td> <td>4/24/2021</td> <td>By Total</td> <td>nan </td> <td>nan  </td> <td>United States</td> <td>All Sexes</td> <td>30-39 years </td> <td>6089           </td> <td>113155      </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>4/28/2021 </td> <td>1/1/2020  </td> <td>4/24/2021</td> <td>By Total</td> <td>nan </td> <td>nan  </td> <td>United States</td> <td>All Sexes</td> <td>35-44 years </td> <td>9724           </td> <td>133834      </td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>\n",
       "<p>... (52316 rows omitted)</p>"
      ],
      "text/plain": [
       "Data As Of | Start Date | End Date  | Group    | Year | Month | State         | Sex       | Age Group    | COVID-19 Deaths | Total Deaths\n",
       "4/28/2021  | 1/1/2020   | 4/24/2021 | By Total | nan  | nan   | United States | All Sexes | All Ages     | 557486          | 4.35558e+06\n",
       "4/28/2021  | 1/1/2020   | 4/24/2021 | By Total | nan  | nan   | United States | All Sexes | Under 1 year | 66              | 23862\n",
       "4/28/2021  | 1/1/2020   | 4/24/2021 | By Total | nan  | nan   | United States | All Sexes | 0-17 years   | 277             | 41811\n",
       "4/28/2021  | 1/1/2020   | 4/24/2021 | By Total | nan  | nan   | United States | All Sexes | 1-4 years    | 34              | 4286\n",
       "4/28/2021  | 1/1/2020   | 4/24/2021 | By Total | nan  | nan   | United States | All Sexes | 5-14 years   | 98              | 6930\n",
       "4/28/2021  | 1/1/2020   | 4/24/2021 | By Total | nan  | nan   | United States | All Sexes | 15-24 years  | 844             | 44906\n",
       "4/28/2021  | 1/1/2020   | 4/24/2021 | By Total | nan  | nan   | United States | All Sexes | 18-29 years  | 2097            | 79315\n",
       "4/28/2021  | 1/1/2020   | 4/24/2021 | By Total | nan  | nan   | United States | All Sexes | 25-34 years  | 3741            | 92911\n",
       "4/28/2021  | 1/1/2020   | 4/24/2021 | By Total | nan  | nan   | United States | All Sexes | 30-39 years  | 6089            | 113155\n",
       "4/28/2021  | 1/1/2020   | 4/24/2021 | By Total | nan  | nan   | United States | All Sexes | 35-44 years  | 9724            | 133834\n",
       "... (52316 rows omitted)"
      ]
     },
     "execution_count": 11,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Import data to covid\n",
    "# https://data.cdc.gov/api/views/9mfq-cb36/rows.csv\n",
    "covid = Table.read_table('Provisional.csv')\n",
    "covid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>Order</th> <th>State</th> <th>Governor</th> <th>Party</th> <th>Inauguration</th> <th>End of term</th> <th>Term limits</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>1    </td> <td>Alabama    </td> <td>Kay Ivey      </td> <td>Republican</td> <td>10-Apr-17   </td> <td>2023       </td> <td>y          </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>3    </td> <td>Alaska     </td> <td>Mike Dunleavy </td> <td>Republican</td> <td>3-Dec-18    </td> <td>2023       </td> <td>y          </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>5    </td> <td>Arizona    </td> <td>Doug Ducey    </td> <td>Republican</td> <td>5-Jan-15    </td> <td>2023       </td> <td>n          </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>7    </td> <td>Arkansas   </td> <td>Asa Hutchinson</td> <td>Republican</td> <td>13-Jan-15   </td> <td>2023       </td> <td>n          </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>9    </td> <td>California </td> <td>Gavin Newsom  </td> <td>Democratic</td> <td>7-Jan-19    </td> <td>2023       </td> <td>y          </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>11   </td> <td>Colorado   </td> <td>Jared Polis   </td> <td>Democratic</td> <td>8-Jan-19    </td> <td>2023       </td> <td>y          </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>13   </td> <td>Connecticut</td> <td>Ned Lamont    </td> <td>Democratic</td> <td>9-Jan-19    </td> <td>2023       </td> <td>y          </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>15   </td> <td>Delaware   </td> <td>John Carney   </td> <td>Democratic</td> <td>17-Jan-17   </td> <td>2025       </td> <td>n          </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>17   </td> <td>Florida    </td> <td>Ron DeSantis  </td> <td>Republican</td> <td>8-Jan-19    </td> <td>2023       </td> <td>y          </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>19   </td> <td>Georgia    </td> <td>Brian Kemp    </td> <td>Republican</td> <td>14-Jan-19   </td> <td>2023       </td> <td>y          </td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>\n",
       "<p>... (40 rows omitted)</p>"
      ],
      "text/plain": [
       "Order | State       | Governor       | Party      | Inauguration | End of term | Term limits\n",
       "1     | Alabama     | Kay Ivey       | Republican | 10-Apr-17    | 2023        | y\n",
       "3     | Alaska      | Mike Dunleavy  | Republican | 3-Dec-18     | 2023        | y\n",
       "5     | Arizona     | Doug Ducey     | Republican | 5-Jan-15     | 2023        | n\n",
       "7     | Arkansas    | Asa Hutchinson | Republican | 13-Jan-15    | 2023        | n\n",
       "9     | California  | Gavin Newsom   | Democratic | 7-Jan-19     | 2023        | y\n",
       "11    | Colorado    | Jared Polis    | Democratic | 8-Jan-19     | 2023        | y\n",
       "13    | Connecticut | Ned Lamont     | Democratic | 9-Jan-19     | 2023        | y\n",
       "15    | Delaware    | John Carney    | Democratic | 17-Jan-17    | 2025        | n\n",
       "17    | Florida     | Ron DeSantis   | Republican | 8-Jan-19     | 2023        | y\n",
       "19    | Georgia     | Brian Kemp     | Republican | 14-Jan-19    | 2023        | y\n",
       "... (40 rows omitted)"
      ]
     },
     "execution_count": 14,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Put data in folder\n",
    "mydata = Table.read_table('state_governors2021.csv')\n",
    "mydata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>Party</th> <th>End of term</th> <th>count</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>Democratic</td> <td>2022       </td> <td>4    </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Democratic</td> <td>2023       </td> <td>15   </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Republican</td> <td>2023       </td> <td>20   </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Democratic</td> <td>2024       </td> <td>1    </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Republican</td> <td>2024       </td> <td>2    </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Democratic</td> <td>2025       </td> <td>3    </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Republican</td> <td>2025       </td> <td>5    </td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "Party      | End of term | count\n",
       "Democratic | 2022        | 4\n",
       "Democratic | 2023        | 15\n",
       "Republican | 2023        | 20\n",
       "Democratic | 2024        | 1\n",
       "Republican | 2024        | 2\n",
       "Democratic | 2025        | 3\n",
       "Republican | 2025        | 5"
      ]
     },
     "execution_count": 33,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_bar = mydata.group(['Party', 'End of term']).sort('End of term')\n",
    "my_bar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "execution_count": 32,
     "metadata": {
      "image/png": {
       "height": 265,
       "width": 644
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_bar.select(0, 1, 2).barh(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>Party</th> <th>2022</th> <th>2023</th> <th>2024</th> <th>2025</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>Democratic</td> <td>4   </td> <td>15  </td> <td>1   </td> <td>3   </td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Republican</td> <td>0   </td> <td>20  </td> <td>2   </td> <td>5   </td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "Party      | 2022 | 2023 | 2024 | 2025\n",
       "Democratic | 4    | 15   | 1    | 3\n",
       "Republican | 0    | 20   | 2    | 5"
      ]
     },
     "execution_count": 41,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mydata.pivot('End of term', 'Party')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "# Import data\n",
    "# https://data.cdc.gov/api/views/9bhg-hcku/rows.csv"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (system-wide)",
   "language": "python",
   "metadata": {
    "cocalc": {
     "description": "Python 3 programming language",
     "priority": 100,
     "url": "https://www.python.org/"
    }
   },
   "name": "python3",
   "resource_dir": "/ext/jupyter/kernels/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": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}