Music League Data - Legwork.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "66bd1853",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Started with imports\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "0fd5f7d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "#And lets read in our Music League data\n",
    "competitors = pd.read_csv('competitors.csv')\n",
    "rounds = pd.read_csv('rounds.csv')\n",
    "submissions = pd.read_csv('submissions.csv')\n",
    "votes = pd.read_csv('votes.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "a10d42e9",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3f0226c12803401681bb8528ffcbe375</td>\n",
       "      <td>Jeffrey Blitt</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>41173c75c0744b08bdebf53a8a6faf9a</td>\n",
       "      <td>Dean</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5946dbdca98f489ab0819f9784523ad7</td>\n",
       "      <td>Dalton</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5d6108a722d84535ab787ea0cbda958f</td>\n",
       "      <td>Jake Sorscher</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>619cf681c25244809e6cbfb0dffe66a1</td>\n",
       "      <td>eestevens0131</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "                                 ID           Name\n",
       "0  3f0226c12803401681bb8528ffcbe375  Jeffrey Blitt\n",
       "1  41173c75c0744b08bdebf53a8a6faf9a           Dean\n",
       "2  5946dbdca98f489ab0819f9784523ad7         Dalton\n",
       "3  5d6108a722d84535ab787ea0cbda958f  Jake Sorscher\n",
       "4  619cf681c25244809e6cbfb0dffe66a1  eestevens0131"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Checking competitors\n",
    "competitors.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "5ecefc4b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Created</th>\n",
       "      <th>Name</th>\n",
       "      <th>Description</th>\n",
       "      <th>Playlist URL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>a57cad45e69c4f6da688d02ec1e0a330</td>\n",
       "      <td>2021-06-21T22:21:06Z</td>\n",
       "      <td>Animal Songs</td>\n",
       "      <td>Song about an animal, has an animal in the tit...</td>\n",
       "      <td>https://open.spotify.com/playlist/3AbXdrryDont...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>b7ee07c554744044adedf596430c3b64</td>\n",
       "      <td>2021-07-01T01:04:10Z</td>\n",
       "      <td>Songs with a location in the title</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://open.spotify.com/playlist/4IxbHnTuwc3j...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9e67e53f515541cc9ded6fbe26a5356f</td>\n",
       "      <td>2021-07-07T03:54:04Z</td>\n",
       "      <td>Songs with a name in the title</td>\n",
       "      <td>Like a person's name. Just has to be IN the ti...</td>\n",
       "      <td>https://open.spotify.com/playlist/6JkOvj0xsOA1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>b6d6c2c8fc754b79ac45454f68873523</td>\n",
       "      <td>2021-07-12T03:15:11Z</td>\n",
       "      <td>Pirate/Ship songs</td>\n",
       "      <td>The dread captain Athreya Ramesh has declared ...</td>\n",
       "      <td>https://open.spotify.com/playlist/3fz7CmOWVB9P...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>c49edf812e13449e8037c42dff40e66a</td>\n",
       "      <td>2021-07-20T12:23:28Z</td>\n",
       "      <td>It's About Time</td>\n",
       "      <td>Timelord James wants songs related to time! Se...</td>\n",
       "      <td>https://open.spotify.com/playlist/7cpsYBELLuu5...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 ID               Created  \\\n",
       "0  a57cad45e69c4f6da688d02ec1e0a330  2021-06-21T22:21:06Z   \n",
       "1  b7ee07c554744044adedf596430c3b64  2021-07-01T01:04:10Z   \n",
       "2  9e67e53f515541cc9ded6fbe26a5356f  2021-07-07T03:54:04Z   \n",
       "3  b6d6c2c8fc754b79ac45454f68873523  2021-07-12T03:15:11Z   \n",
       "4  c49edf812e13449e8037c42dff40e66a  2021-07-20T12:23:28Z   \n",
       "\n",
       "                                 Name  \\\n",
       "0                        Animal Songs   \n",
       "1  Songs with a location in the title   \n",
       "2     Songs with a name in the title    \n",
       "3                   Pirate/Ship songs   \n",
       "4                     It's About Time   \n",
       "\n",
       "                                         Description  \\\n",
       "0  Song about an animal, has an animal in the tit...   \n",
       "1                                                NaN   \n",
       "2  Like a person's name. Just has to be IN the ti...   \n",
       "3  The dread captain Athreya Ramesh has declared ...   \n",
       "4  Timelord James wants songs related to time! Se...   \n",
       "\n",
       "                                        Playlist URL  \n",
       "0  https://open.spotify.com/playlist/3AbXdrryDont...  \n",
       "1  https://open.spotify.com/playlist/4IxbHnTuwc3j...  \n",
       "2  https://open.spotify.com/playlist/6JkOvj0xsOA1...  \n",
       "3  https://open.spotify.com/playlist/3fz7CmOWVB9P...  \n",
       "4  https://open.spotify.com/playlist/7cpsYBELLuu5...  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Checking rounds\n",
    "rounds.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c22dd11f",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Spotify URI</th>\n",
       "      <th>Submitter ID</th>\n",
       "      <th>Created</th>\n",
       "      <th>Comment</th>\n",
       "      <th>Round ID</th>\n",
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       "      <th>0</th>\n",
       "      <td>spotify:track:0wP9okoDWmbeC2w9E8ZzPu</td>\n",
       "      <td>716e73d73d444b08b52ccc293c1b0517</td>\n",
       "      <td>2021-06-24T17:00:30Z</td>\n",
       "      <td>I submit for approval of the board, not only i...</td>\n",
       "      <td>a57cad45e69c4f6da688d02ec1e0a330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>spotify:track:1ITQbrueGLl581a25XXm9c</td>\n",
       "      <td>a4126addfdc64ee085297b198466afb2</td>\n",
       "      <td>2021-06-22T00:56:35Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a57cad45e69c4f6da688d02ec1e0a330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>spotify:track:3AaiEsiqHO2ylnnOdWninE</td>\n",
       "      <td>89daec8f4d44437b9b6f4328a734c7a4</td>\n",
       "      <td>2021-06-21T22:34:18Z</td>\n",
       "      <td>the animal is obviously shrimp</td>\n",
       "      <td>a57cad45e69c4f6da688d02ec1e0a330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>spotify:track:4qn3XK6IW2cKjWjSk37t6p</td>\n",
       "      <td>619cf681c25244809e6cbfb0dffe66a1</td>\n",
       "      <td>2021-06-21T23:29:32Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a57cad45e69c4f6da688d02ec1e0a330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>spotify:track:53is1DHKuBWeh4Jx9ISKZp</td>\n",
       "      <td>41173c75c0744b08bdebf53a8a6faf9a</td>\n",
       "      <td>2021-06-22T02:49:07Z</td>\n",
       "      <td>this is real fucking music</td>\n",
       "      <td>a57cad45e69c4f6da688d02ec1e0a330</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "                            Spotify URI                      Submitter ID  \\\n",
       "0  spotify:track:0wP9okoDWmbeC2w9E8ZzPu  716e73d73d444b08b52ccc293c1b0517   \n",
       "1  spotify:track:1ITQbrueGLl581a25XXm9c  a4126addfdc64ee085297b198466afb2   \n",
       "2  spotify:track:3AaiEsiqHO2ylnnOdWninE  89daec8f4d44437b9b6f4328a734c7a4   \n",
       "3  spotify:track:4qn3XK6IW2cKjWjSk37t6p  619cf681c25244809e6cbfb0dffe66a1   \n",
       "4  spotify:track:53is1DHKuBWeh4Jx9ISKZp  41173c75c0744b08bdebf53a8a6faf9a   \n",
       "\n",
       "                Created                                            Comment  \\\n",
       "0  2021-06-24T17:00:30Z  I submit for approval of the board, not only i...   \n",
       "1  2021-06-22T00:56:35Z                                                NaN   \n",
       "2  2021-06-21T22:34:18Z                     the animal is obviously shrimp   \n",
       "3  2021-06-21T23:29:32Z                                                NaN   \n",
       "4  2021-06-22T02:49:07Z                         this is real fucking music   \n",
       "\n",
       "                           Round ID  \n",
       "0  a57cad45e69c4f6da688d02ec1e0a330  \n",
       "1  a57cad45e69c4f6da688d02ec1e0a330  \n",
       "2  a57cad45e69c4f6da688d02ec1e0a330  \n",
       "3  a57cad45e69c4f6da688d02ec1e0a330  \n",
       "4  a57cad45e69c4f6da688d02ec1e0a330  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Checking submissions\n",
    "submissions.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4a07b417",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Spotify URI</th>\n",
       "      <th>Voter ID</th>\n",
       "      <th>Created</th>\n",
       "      <th>Points Assigned</th>\n",
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       "      <th>Round ID</th>\n",
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       "      <th>0</th>\n",
       "      <td>spotify:track:0wP9okoDWmbeC2w9E8ZzPu</td>\n",
       "      <td>a04dbd780c1e4df59e1617574f1ae4a4</td>\n",
       "      <td>2021-06-28T02:38:04Z</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>a57cad45e69c4f6da688d02ec1e0a330</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>spotify:track:3AaiEsiqHO2ylnnOdWninE</td>\n",
       "      <td>a04dbd780c1e4df59e1617574f1ae4a4</td>\n",
       "      <td>2021-06-28T02:38:04Z</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a57cad45e69c4f6da688d02ec1e0a330</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>spotify:track:7qErExxM8xsfC1cogPTyLj</td>\n",
       "      <td>a04dbd780c1e4df59e1617574f1ae4a4</td>\n",
       "      <td>2021-06-28T02:38:04Z</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>spotify:track:1ITQbrueGLl581a25XXm9c</td>\n",
       "      <td>716e73d73d444b08b52ccc293c1b0517</td>\n",
       "      <td>2021-06-28T04:55:14Z</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a57cad45e69c4f6da688d02ec1e0a330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>spotify:track:4qn3XK6IW2cKjWjSk37t6p</td>\n",
       "      <td>716e73d73d444b08b52ccc293c1b0517</td>\n",
       "      <td>2021-06-28T04:55:14Z</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a57cad45e69c4f6da688d02ec1e0a330</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "                            Spotify URI                          Voter ID  \\\n",
       "0  spotify:track:0wP9okoDWmbeC2w9E8ZzPu  a04dbd780c1e4df59e1617574f1ae4a4   \n",
       "1  spotify:track:3AaiEsiqHO2ylnnOdWninE  a04dbd780c1e4df59e1617574f1ae4a4   \n",
       "2  spotify:track:7qErExxM8xsfC1cogPTyLj  a04dbd780c1e4df59e1617574f1ae4a4   \n",
       "3  spotify:track:1ITQbrueGLl581a25XXm9c  716e73d73d444b08b52ccc293c1b0517   \n",
       "4  spotify:track:4qn3XK6IW2cKjWjSk37t6p  716e73d73d444b08b52ccc293c1b0517   \n",
       "\n",
       "                Created  Points Assigned Comment  \\\n",
       "0  2021-06-28T02:38:04Z                1     NaN   \n",
       "1  2021-06-28T02:38:04Z                1     NaN   \n",
       "2  2021-06-28T02:38:04Z                1     NaN   \n",
       "3  2021-06-28T04:55:14Z                1     NaN   \n",
       "4  2021-06-28T04:55:14Z                1     NaN   \n",
       "\n",
       "                           Round ID  \n",
       "0  a57cad45e69c4f6da688d02ec1e0a330  \n",
       "1  a57cad45e69c4f6da688d02ec1e0a330  \n",
       "2  a57cad45e69c4f6da688d02ec1e0a330  \n",
       "3  a57cad45e69c4f6da688d02ec1e0a330  \n",
       "4  a57cad45e69c4f6da688d02ec1e0a330  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Checking votes\n",
    "votes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "ced88dde",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Now lets isolate the voter and round IDs as they're the least interpretable data\n",
    "#Rounds already in competitors\n",
    "roundsByID = rounds[[\"ID\", \"Name\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "a640ea94",
   "metadata": {},
   "outputs": [
    {
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       "      <td>Animal Songs</td>\n",
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       "      <td>b7ee07c554744044adedf596430c3b64</td>\n",
       "      <td>Songs with a location in the title</td>\n",
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       "      <th>2</th>\n",
       "      <td>9e67e53f515541cc9ded6fbe26a5356f</td>\n",
       "      <td>Songs with a name in the title</td>\n",
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       "      <th>3</th>\n",
       "      <td>b6d6c2c8fc754b79ac45454f68873523</td>\n",
       "      <td>Pirate/Ship songs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>c49edf812e13449e8037c42dff40e66a</td>\n",
       "      <td>It's About Time</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 ID                                Name\n",
       "0  a57cad45e69c4f6da688d02ec1e0a330                        Animal Songs\n",
       "1  b7ee07c554744044adedf596430c3b64  Songs with a location in the title\n",
       "2  9e67e53f515541cc9ded6fbe26a5356f     Songs with a name in the title \n",
       "3  b6d6c2c8fc754b79ac45454f68873523                   Pirate/Ship songs\n",
       "4  c49edf812e13449e8037c42dff40e66a                     It's About Time"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#And see if it worked...\n",
    "roundsByID.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "3b407015",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Spotify_URI</th>\n",
       "      <th>Submitter_ID</th>\n",
       "      <th>Created</th>\n",
       "      <th>Comment</th>\n",
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       "      <td>2021-06-24T17:00:30Z</td>\n",
       "      <td>I submit for approval of the board, not only i...</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>spotify:track:1ITQbrueGLl581a25XXm9c</td>\n",
       "      <td>a4126addfdc64ee085297b198466afb2</td>\n",
       "      <td>2021-06-22T00:56:35Z</td>\n",
       "      <td>NaN</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
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       "      <td>spotify:track:3AaiEsiqHO2ylnnOdWninE</td>\n",
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       "      <td>2021-06-21T22:34:18Z</td>\n",
       "      <td>the animal is obviously shrimp</td>\n",
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       "      <td>spotify:track:4qn3XK6IW2cKjWjSk37t6p</td>\n",
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       "      <td>2021-06-21T23:29:32Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a57cad45e69c4f6da688d02ec1e0a330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>spotify:track:53is1DHKuBWeh4Jx9ISKZp</td>\n",
       "      <td>41173c75c0744b08bdebf53a8a6faf9a</td>\n",
       "      <td>2021-06-22T02:49:07Z</td>\n",
       "      <td>this is real fucking music</td>\n",
       "      <td>a57cad45e69c4f6da688d02ec1e0a330</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Spotify_URI                      Submitter_ID  \\\n",
       "0  spotify:track:0wP9okoDWmbeC2w9E8ZzPu  716e73d73d444b08b52ccc293c1b0517   \n",
       "1  spotify:track:1ITQbrueGLl581a25XXm9c  a4126addfdc64ee085297b198466afb2   \n",
       "2  spotify:track:3AaiEsiqHO2ylnnOdWninE  89daec8f4d44437b9b6f4328a734c7a4   \n",
       "3  spotify:track:4qn3XK6IW2cKjWjSk37t6p  619cf681c25244809e6cbfb0dffe66a1   \n",
       "4  spotify:track:53is1DHKuBWeh4Jx9ISKZp  41173c75c0744b08bdebf53a8a6faf9a   \n",
       "\n",
       "                Created                                            Comment  \\\n",
       "0  2021-06-24T17:00:30Z  I submit for approval of the board, not only i...   \n",
       "1  2021-06-22T00:56:35Z                                                NaN   \n",
       "2  2021-06-21T22:34:18Z                     the animal is obviously shrimp   \n",
       "3  2021-06-21T23:29:32Z                                                NaN   \n",
       "4  2021-06-22T02:49:07Z                         this is real fucking music   \n",
       "\n",
       "                           Round_ID  \n",
       "0  a57cad45e69c4f6da688d02ec1e0a330  \n",
       "1  a57cad45e69c4f6da688d02ec1e0a330  \n",
       "2  a57cad45e69c4f6da688d02ec1e0a330  \n",
       "3  a57cad45e69c4f6da688d02ec1e0a330  \n",
       "4  a57cad45e69c4f6da688d02ec1e0a330  "
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Now for some coding!\n",
    "#Want to loop through the elements of the two identifying data frames and replace all instaces of ID with all instances of\n",
    "#their names instead. If I end up regretting this it's easy to revert. \n",
    "for index, row in competitors.iterrows():\n",
    "    submissions.replace(row['ID'], row['Name'])\n",
    "#And how'd it work?\n",
    "submissions.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "c7dfc065",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3f0226c12803401681bb8528ffcbe375 Jeffrey Blitt\n",
      "41173c75c0744b08bdebf53a8a6faf9a Dean\n",
      "5946dbdca98f489ab0819f9784523ad7 Dalton\n",
      "5d6108a722d84535ab787ea0cbda958f Jake Sorscher\n",
      "619cf681c25244809e6cbfb0dffe66a1 eestevens0131\n",
      "68016b3ccb0e4780856c4bb8a8d798ed Sam Livermore\n",
      "716e73d73d444b08b52ccc293c1b0517 James Cameron\n",
      "89daec8f4d44437b9b6f4328a734c7a4 Lucy\n",
      "934a2386d8344626ba1d1aafd7108902 Annmarie\n",
      "a04dbd780c1e4df59e1617574f1ae4a4 William Sherwood\n",
      "a4126addfdc64ee085297b198466afb2 Sarah\n",
      "bf2f8fe4ff5147e5b45f3ac75940a1b7 Kate\n",
      "d2f9038dfd4243b2becf4b7114cc94fe Athreya Ramesh\n",
      "e3a109c29f194ee5b2ce022672ca72c4 joshy.harvey\n"
     ]
    }
   ],
   "source": [
    "#It didn't! Nice, lets try this to confirm we're doing what we want:\n",
    "for index, row in competitors.iterrows():\n",
    "    print(row['ID'], row['Name'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "a4281483",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "   c1   c2\n",
       "0  10  100\n",
       "1  11  110\n",
       "2  12  120"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#It is, which is even stranger. So let's try to see how replace works on a smaller scale\n",
    "df = pd.DataFrame({'c1': [10, 11, 12], 'c2': [100, 110, 120]})\n",
    "df.replace(11, 999)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "1618845e",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>2021-06-24T17:00:30Z</td>\n",
       "      <td>I submit for approval of the board, not only i...</td>\n",
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       "    </tr>\n",
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       "      <th>1</th>\n",
       "      <td>spotify:track:1ITQbrueGLl581a25XXm9c</td>\n",
       "      <td>a4126addfdc64ee085297b198466afb2</td>\n",
       "      <td>2021-06-22T00:56:35Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a57cad45e69c4f6da688d02ec1e0a330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>spotify:track:3AaiEsiqHO2ylnnOdWninE</td>\n",
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       "      <td>2021-06-21T22:34:18Z</td>\n",
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       "      <td>a57cad45e69c4f6da688d02ec1e0a330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>spotify:track:4qn3XK6IW2cKjWjSk37t6p</td>\n",
       "      <td>619cf681c25244809e6cbfb0dffe66a1</td>\n",
       "      <td>2021-06-21T23:29:32Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a57cad45e69c4f6da688d02ec1e0a330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>spotify:track:53is1DHKuBWeh4Jx9ISKZp</td>\n",
       "      <td>41173c75c0744b08bdebf53a8a6faf9a</td>\n",
       "      <td>2021-06-22T02:49:07Z</td>\n",
       "      <td>this is real fucking music</td>\n",
       "      <td>a57cad45e69c4f6da688d02ec1e0a330</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "                            Spotify_URI                      Submitter_ID  \\\n",
       "0  spotify:track:0wP9okoDWmbeC2w9E8ZzPu  716e73d73d444b08b52ccc293c1b0517   \n",
       "1  spotify:track:1ITQbrueGLl581a25XXm9c  a4126addfdc64ee085297b198466afb2   \n",
       "2  spotify:track:3AaiEsiqHO2ylnnOdWninE  89daec8f4d44437b9b6f4328a734c7a4   \n",
       "3  spotify:track:4qn3XK6IW2cKjWjSk37t6p  619cf681c25244809e6cbfb0dffe66a1   \n",
       "4  spotify:track:53is1DHKuBWeh4Jx9ISKZp  41173c75c0744b08bdebf53a8a6faf9a   \n",
       "\n",
       "                Created                                            Comment  \\\n",
       "0  2021-06-24T17:00:30Z  I submit for approval of the board, not only i...   \n",
       "1  2021-06-22T00:56:35Z                                                NaN   \n",
       "2  2021-06-21T22:34:18Z                     the animal is obviously shrimp   \n",
       "3  2021-06-21T23:29:32Z                                                NaN   \n",
       "4  2021-06-22T02:49:07Z                         this is real fucking music   \n",
       "\n",
       "                           Round_ID  \n",
       "0  a57cad45e69c4f6da688d02ec1e0a330  \n",
       "1  a57cad45e69c4f6da688d02ec1e0a330  \n",
       "2  a57cad45e69c4f6da688d02ec1e0a330  \n",
       "3  a57cad45e69c4f6da688d02ec1e0a330  \n",
       "4  a57cad45e69c4f6da688d02ec1e0a330  "
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#I didn't understand how this worked, found example at https://www.geeksforgeeks.org/python-pandas-dataframe-replace/\n",
    "#So lets see if this works instead...\n",
    "for index, row in competitors.iterrows():\n",
    "    submissions.replace(to_replace = row['ID'], value = row['Name'])\n",
    "submissions.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "05d575ce",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "    c1   c2\n",
       "0   10  100\n",
       "1  999  110\n",
       "2   12  120"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Cool, more sanity testing is in order. \n",
    "#Lets revisit our above test to see if the replace function can even work when called like that\n",
    "df = pd.DataFrame({'c1': [10, 11, 12], 'c2': [100, 110, 120]})\n",
    "df.replace(to_replace =11, value =999)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "f01e4256",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "   c1   c2\n",
       "0  10  100\n",
       "1  11  110\n",
       "2  12  120"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#And does that stay in a new cell?\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "id": "0f03c97d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#NO it doesn't, what in the actual fuck? Interesting, so I have to assign a new dataFrame at each call or something?\n",
    "#Is the inplace part of the function what I want here?\n",
    "df = pd.DataFrame({'c1': [10], 'c2': [100]})\n",
    "df.replace(to_replace =11, value =999, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "id": "294dd12f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 171,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Big money no whammy...\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "0c45d2cb",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>spotify:track:0wP9okoDWmbeC2w9E8ZzPu</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>2021-06-24T17:00:30Z</td>\n",
       "      <td>I submit for approval of the board, not only i...</td>\n",
       "      <td>a57cad45e69c4f6da688d02ec1e0a330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>spotify:track:1ITQbrueGLl581a25XXm9c</td>\n",
       "      <td>Sarah</td>\n",
       "      <td>2021-06-22T00:56:35Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a57cad45e69c4f6da688d02ec1e0a330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>spotify:track:3AaiEsiqHO2ylnnOdWninE</td>\n",
       "      <td>Lucy</td>\n",
       "      <td>2021-06-21T22:34:18Z</td>\n",
       "      <td>the animal is obviously shrimp</td>\n",
       "      <td>a57cad45e69c4f6da688d02ec1e0a330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>spotify:track:4qn3XK6IW2cKjWjSk37t6p</td>\n",
       "      <td>eestevens0131</td>\n",
       "      <td>2021-06-21T23:29:32Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a57cad45e69c4f6da688d02ec1e0a330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>spotify:track:53is1DHKuBWeh4Jx9ISKZp</td>\n",
       "      <td>Dean</td>\n",
       "      <td>2021-06-22T02:49:07Z</td>\n",
       "      <td>this is real fucking music</td>\n",
       "      <td>a57cad45e69c4f6da688d02ec1e0a330</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Spotify_URI   Submitter_ID               Created  \\\n",
       "0  spotify:track:0wP9okoDWmbeC2w9E8ZzPu  James Cameron  2021-06-24T17:00:30Z   \n",
       "1  spotify:track:1ITQbrueGLl581a25XXm9c          Sarah  2021-06-22T00:56:35Z   \n",
       "2  spotify:track:3AaiEsiqHO2ylnnOdWninE           Lucy  2021-06-21T22:34:18Z   \n",
       "3  spotify:track:4qn3XK6IW2cKjWjSk37t6p  eestevens0131  2021-06-21T23:29:32Z   \n",
       "4  spotify:track:53is1DHKuBWeh4Jx9ISKZp           Dean  2021-06-22T02:49:07Z   \n",
       "\n",
       "                                             Comment  \\\n",
       "0  I submit for approval of the board, not only i...   \n",
       "1                                                NaN   \n",
       "2                     the animal is obviously shrimp   \n",
       "3                                                NaN   \n",
       "4                         this is real fucking music   \n",
       "\n",
       "                           Round_ID  \n",
       "0  a57cad45e69c4f6da688d02ec1e0a330  \n",
       "1  a57cad45e69c4f6da688d02ec1e0a330  \n",
       "2  a57cad45e69c4f6da688d02ec1e0a330  \n",
       "3  a57cad45e69c4f6da688d02ec1e0a330  \n",
       "4  a57cad45e69c4f6da688d02ec1e0a330  "
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#YES! And now...\n",
    "for index, row in competitors.iterrows():\n",
    "    submissions.replace(to_replace = row['ID'], value = row['Name'], inplace=True)\n",
    "submissions.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "2309f12a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Spotify_URI</th>\n",
       "      <th>Submitter_ID</th>\n",
       "      <th>Created</th>\n",
       "      <th>Comment</th>\n",
       "      <th>Round_ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>spotify:track:0wP9okoDWmbeC2w9E8ZzPu</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>2021-06-24T17:00:30Z</td>\n",
       "      <td>I submit for approval of the board, not only i...</td>\n",
       "      <td>Animal Songs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>spotify:track:1ITQbrueGLl581a25XXm9c</td>\n",
       "      <td>Sarah</td>\n",
       "      <td>2021-06-22T00:56:35Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Animal Songs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>spotify:track:3AaiEsiqHO2ylnnOdWninE</td>\n",
       "      <td>Lucy</td>\n",
       "      <td>2021-06-21T22:34:18Z</td>\n",
       "      <td>the animal is obviously shrimp</td>\n",
       "      <td>Animal Songs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>spotify:track:4qn3XK6IW2cKjWjSk37t6p</td>\n",
       "      <td>eestevens0131</td>\n",
       "      <td>2021-06-21T23:29:32Z</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Animal Songs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>spotify:track:53is1DHKuBWeh4Jx9ISKZp</td>\n",
       "      <td>Dean</td>\n",
       "      <td>2021-06-22T02:49:07Z</td>\n",
       "      <td>this is real fucking music</td>\n",
       "      <td>Animal Songs</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Spotify_URI   Submitter_ID               Created  \\\n",
       "0  spotify:track:0wP9okoDWmbeC2w9E8ZzPu  James Cameron  2021-06-24T17:00:30Z   \n",
       "1  spotify:track:1ITQbrueGLl581a25XXm9c          Sarah  2021-06-22T00:56:35Z   \n",
       "2  spotify:track:3AaiEsiqHO2ylnnOdWninE           Lucy  2021-06-21T22:34:18Z   \n",
       "3  spotify:track:4qn3XK6IW2cKjWjSk37t6p  eestevens0131  2021-06-21T23:29:32Z   \n",
       "4  spotify:track:53is1DHKuBWeh4Jx9ISKZp           Dean  2021-06-22T02:49:07Z   \n",
       "\n",
       "                                             Comment      Round_ID  \n",
       "0  I submit for approval of the board, not only i...  Animal Songs  \n",
       "1                                                NaN  Animal Songs  \n",
       "2                     the animal is obviously shrimp  Animal Songs  \n",
       "3                                                NaN  Animal Songs  \n",
       "4                         this is real fucking music  Animal Songs  "
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Awesome awesome, lets do that for the other datasets real quick...\n",
    "for index, row in roundsByID.iterrows():\n",
    "    submissions.replace(to_replace = row['ID'], value = row['Name'], inplace=True)\n",
    "submissions.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "392491dd",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Spotify_URI</th>\n",
       "      <th>Voter_ID</th>\n",
       "      <th>Created</th>\n",
       "      <th>Points_Assigned</th>\n",
       "      <th>Comment</th>\n",
       "      <th>Round ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>spotify:track:0wP9okoDWmbeC2w9E8ZzPu</td>\n",
       "      <td>William Sherwood</td>\n",
       "      <td>2021-06-28T02:38:04Z</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Animal Songs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>spotify:track:3AaiEsiqHO2ylnnOdWninE</td>\n",
       "      <td>William Sherwood</td>\n",
       "      <td>2021-06-28T02:38:04Z</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Animal Songs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>spotify:track:7qErExxM8xsfC1cogPTyLj</td>\n",
       "      <td>William Sherwood</td>\n",
       "      <td>2021-06-28T02:38:04Z</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Animal Songs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>spotify:track:1ITQbrueGLl581a25XXm9c</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>2021-06-28T04:55:14Z</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Animal Songs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>spotify:track:4qn3XK6IW2cKjWjSk37t6p</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>2021-06-28T04:55:14Z</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Animal Songs</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Spotify_URI          Voter_ID  \\\n",
       "0  spotify:track:0wP9okoDWmbeC2w9E8ZzPu  William Sherwood   \n",
       "1  spotify:track:3AaiEsiqHO2ylnnOdWninE  William Sherwood   \n",
       "2  spotify:track:7qErExxM8xsfC1cogPTyLj  William Sherwood   \n",
       "3  spotify:track:1ITQbrueGLl581a25XXm9c     James Cameron   \n",
       "4  spotify:track:4qn3XK6IW2cKjWjSk37t6p     James Cameron   \n",
       "\n",
       "                Created  Points_Assigned Comment      Round ID  \n",
       "0  2021-06-28T02:38:04Z                1     NaN  Animal Songs  \n",
       "1  2021-06-28T02:38:04Z                1     NaN  Animal Songs  \n",
       "2  2021-06-28T02:38:04Z                1     NaN  Animal Songs  \n",
       "3  2021-06-28T04:55:14Z                1     NaN  Animal Songs  \n",
       "4  2021-06-28T04:55:14Z                1     NaN  Animal Songs  "
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#And for votes...\n",
    "for index, row in roundsByID.iterrows():\n",
    "    votes.replace(to_replace = row['ID'], value = row['Name'], inplace=True)\n",
    "for index, row in competitors.iterrows():\n",
    "    votes.replace(to_replace = row['ID'], value = row['Name'], inplace=True)\n",
    "votes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "id": "8f47a14f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Awesome start, let's start thinking of ways to divide this up.\n",
    "#Let's make a function - takes in a Voter's name and outputs all the songs they've voted for\n",
    "def songsVotedFor(voterName, sourceDF):\n",
    "#    cols = ['Spotify_URI', 'Voter_ID']\n",
    "#     newDF = inputDF[cols]\n",
    "#     newDF[newDF.Voter_ID.str.contains(voterName)]\n",
    "    newDF = sourceDF.query('Voter_ID == \"' + voterName + '\"')\n",
    "    returnArr = []\n",
    "    for index, row in newDF.iterrows():\n",
    "        returnArr.append(row['Spotify_URI'])\n",
    "    returnArr = list(set(returnArr))\n",
    "    return returnArr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "id": "12d14d53",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['spotify:track:6VUMlHTs06O4tvQTpuboVR', 'spotify:track:4ylE1Sl2wohbCvToD1fHsl', 'spotify:track:7dUCFnaGSWLH6SdDP08NLP', 'spotify:track:0EodzyGsPuqU6BrW6wkFQE', 'spotify:track:7qErExxM8xsfC1cogPTyLj', 'spotify:track:0HU6iAeBwxODFxkiRMTgF1', 'spotify:track:0owmJNkGcGNq4hb6qt3ufd', 'spotify:track:3Dv1eDb0MEgF93GpLXlucZ', 'spotify:track:0LP2DlqqEH5Lo0ujWdHkUD', 'spotify:track:6UDFkqHY5gLREnSh9jd5th', 'spotify:track:41yIvlFgvGwxq8qTqAR7eG', 'spotify:track:72ysGFB4mZTgQsPqN9PzPS', 'spotify:track:6w4KcqHYBff2CXKtAVigtl', 'spotify:track:2He9deEfdXYWxnTUi0oOb0', 'spotify:track:2iDYHPLh9TOhDpknFZXPjD', 'spotify:track:1KlDcHrlDPUJJPmMup3tUp', 'spotify:track:0Y4xg5612xZ3vAgWEkMjw3', 'spotify:track:5lLiVVtap1z4PoeWe6mNMG', 'spotify:track:3oQomOPRNQ5NVFUmLJHbAV', 'spotify:track:2uzyiRdvfNI5WxUiItv1y9', 'spotify:track:6iOQIQleZKnvWbPu9LZLnY', 'spotify:track:6E4GwulavAVwwMph9ePPh6', 'spotify:track:7etPhiKxGfTihLqeDnvo9w', 'spotify:track:5xrtzzzikpG3BLbo4q1Yul', 'spotify:track:34Iz2YaDtsHzcxKcFYywnz', 'spotify:track:1qxjyEmiKqgcukhqEawmqK', 'spotify:track:2GsiDLDLYa5dvI7FD7OQos', 'spotify:track:4zvJV8Nrbjruyww3vvNI8M', 'spotify:track:2DLrgv7HhJanCuD8L9uJLR', 'spotify:track:4U45aEWtQhrm8A5mxPaFZ7', 'spotify:track:4feXcsElKIVsGwkbnTHAfV', 'spotify:track:2FeVMO6qFT8eYfRaZ7eQge', 'spotify:track:6pxElwU80zhjbCC77Vn8EI', 'spotify:track:5Su5ILFp6U83cnIXwfmlC5', 'spotify:track:20NEld0MhrR4Zpgrf9brq8', 'spotify:track:3FFpGDzfkwJGjfIqM6BNMC', 'spotify:track:4bPMoXv9sfmXiBOx1D23LB', 'spotify:track:3flQv4DNGg31Ic4vBv45Tj', 'spotify:track:4IdQZXMOooaIRoP7N2qCn8', 'spotify:track:3AaiEsiqHO2ylnnOdWninE', 'spotify:track:65EVlEBJkMJCskhQwUUGew', 'spotify:track:2pctwNyXi67NJtzhojYuY0', 'spotify:track:25ran9X0iBOYnxFdP6c28n', 'spotify:track:5tafBbOkBCpvYAFq8OBmBB', 'spotify:track:4xh7W7tlNMIczFhupCPniY', 'spotify:track:0AUyNF6iFxMNQsNx2nhtrw', 'spotify:track:2BY7ALEWdloFHgQZG6VMLA', 'spotify:track:7xNpCuqDKASx2f64nkhzNm', 'spotify:track:2brQo0jABBYPVQxozdpB2j', 'spotify:track:403vzOZN0tETDpvFipkNIL', 'spotify:track:2zFdsAIk9r2Mi7Lmm1w3sM', 'spotify:track:1i5gQ9q9NA42pvRZscaZaG', 'spotify:track:3L1jrlL7DuCaTlBrE7rnDy', 'spotify:track:152lZdxL1OR0ZMW6KquMif', 'spotify:track:73681b7Hc0THHGZrSzl75y', 'spotify:track:2j90unMoDKo5xqR00xV6Oo', 'spotify:track:2MA6YoaFF7fnWqkuOAWjUg', 'spotify:track:4qspyXnt3zrStg50pmDleF', 'spotify:track:0wP9okoDWmbeC2w9E8ZzPu', 'spotify:track:6ta5yavnnEfCE4faU0jebM', 'spotify:track:4RxyIfOAN8HsjBBoKKt0A4', 'spotify:track:6kQ3W5LMxh6ftjEBssYgAd', 'spotify:track:3A4FRzgve9BjfKbvVXRIFO', 'spotify:track:4zP7ADsgJgHGY6VzxbNp1z', 'spotify:track:4R5vsMYHAPXfoNlNB8QgtU', 'spotify:track:3btnA7GWKvQjFlfsrjuWk9', 'spotify:track:7nzsY8vlnKdvGOEE0rjAXZ', 'spotify:track:0PKmDncVOiNQLO6D1P6PXi']\n"
     ]
    }
   ],
   "source": [
    "#And lets try our function out\n",
    "willVotes = songsVotedFor(\"William Sherwood\", votes)\n",
    "print(willVotes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "id": "949ced7c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "68\n",
      "68\n"
     ]
    }
   ],
   "source": [
    "#Lets get some info about this array, something is awry\n",
    "x = len(willVotes)\n",
    "print(x)\n",
    "flag = 0\n",
    "\n",
    "# # Python3 code to demonstrate \n",
    "# # to test all elements in list are unique\n",
    "# # using set() + len()\n",
    "  \n",
    "# # initializing list \n",
    "# test_list = willVotes\n",
    "  \n",
    "# # printing original list \n",
    "# print (\"The original list is : \" + str(test_list))\n",
    "  \n",
    "# flag = 0\n",
    "  \n",
    "# # using set() + len()\n",
    "# # to check all unique list elements\n",
    "# flag = len(set(test_list)) == len(test_list)\n",
    "  \n",
    "  \n",
    "# # printing result\n",
    "# if(flag) :\n",
    "#     print (\"List contains all unique elements\")\n",
    "# else : \n",
    "#     print (\"List contains does not contains all unique elements\")\n",
    "\n",
    "# willVotes = list(set(willVotes))\n",
    "# x = len(willVotes)\n",
    "# print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "id": "2af8cf6b",
   "metadata": {},
   "outputs": [],
   "source": [
    "#LOTS of debugging there but we got something! Now lets make a function that takes an array of songs and returns a dataframe\n",
    "#of who they voted for.\n",
    "def songTally(songArr, searchDF):\n",
    "    countArr = [0] * 14\n",
    "    pplArr = [\"Jeffrey Blitt\", \"Dean\", \"Dalton\", \"Jake Sorscher\", \"eestevens0131\", \"Sam Livermore\", \"James Cameron\", \"Lucy\", \"Annmarie\", \"William Sherwood\", \"Sarah\", \"Kate\", \"Athreya Ramesh\", \"joshy.harvey\"]\n",
    "    ctr = 0\n",
    "    for songID in songArr:\n",
    "        newDF = searchDF.query('Spotify_URI == \"' + songID + '\"')\n",
    "        for index, name in enumerate(pplArr):\n",
    "            if name == newDF.iloc[0]['Submitter_ID']:\n",
    "                countArr[index] += 1\n",
    "    voteDict = dict(zip(pplArr, countArr))\n",
    "    return pd.DataFrame(voteDict.items(), columns=['Person', 'Votes'])\n",
    "    #return voteDict\n",
    "    #return pd.DataFrame.from_dict(voteDict, index=pplArr)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "id": "5d7c7a46",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Person</th>\n",
       "      <th>Votes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Jeffrey Blitt</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Dean</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Dalton</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jake Sorscher</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>eestevens0131</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Person  Votes\n",
       "0  Jeffrey Blitt      7\n",
       "1           Dean      2\n",
       "2         Dalton      9\n",
       "3  Jake Sorscher      6\n",
       "4  eestevens0131     10"
      ]
     },
     "execution_count": 216,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#And the testing block...\n",
    "willDF = songTally(willVotes, submissions)\n",
    "willDF.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "id": "69205270",
   "metadata": {},
   "outputs": [],
   "source": [
    "#my god im insane that was hard okokokokok lets try graphs\n",
    "import matplotlib.pyplot as mpl\n",
    "import seaborn as sbrn\n",
    "# from matplotlib.pyplot import figure\n",
    "\n",
    "# figure(figsize=(16, 6), dpi=80)\n",
    "mpl.rcParams[\"figure.figsize\"] = (20,5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "id": "55ef0eb6",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':\"Will's Music League Votes\"}, xlabel='Person'>"
      ]
     },
     "execution_count": 227,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Simplest graph I could find\n",
    "# keys = willDict.keys()\n",
    "# values = willDict.values()\n",
    "\n",
    "# fig = mpl.bar(keys, values)\n",
    "willDF.groupby(['Person']).median().sort_values(\"Votes\", ascending=False).plot.bar(title=\"Will's Music League Votes\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "240de7aa",
   "metadata": {},
   "outputs": [
    {
     "ename": "UndefinedVariableError",
     "evalue": "name 'Voter_ID' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\pandas\\core\\computation\\scope.py:195\u001b[0m, in \u001b[0;36mScope.resolve\u001b[1;34m(self, key, is_local)\u001b[0m\n\u001b[0;32m    194\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhas_resolvers:\n\u001b[1;32m--> 195\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresolvers\u001b[49m\u001b[43m[\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m]\u001b[49m\n\u001b[0;32m    197\u001b[0m \u001b[38;5;66;03m# if we're here that means that we have no locals and we also have\u001b[39;00m\n\u001b[0;32m    198\u001b[0m \u001b[38;5;66;03m# no resolvers\u001b[39;00m\n",
      "File \u001b[1;32mC:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.752.0_x64__qbz5n2kfra8p0\\lib\\collections\\__init__.py:982\u001b[0m, in \u001b[0;36mChainMap.__getitem__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m    981\u001b[0m         \u001b[38;5;28;01mpass\u001b[39;00m\n\u001b[1;32m--> 982\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;21;43m__missing__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mC:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.10_3.10.752.0_x64__qbz5n2kfra8p0\\lib\\collections\\__init__.py:974\u001b[0m, in \u001b[0;36mChainMap.__missing__\u001b[1;34m(self, key)\u001b[0m\n\u001b[0;32m    973\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__missing__\u001b[39m(\u001b[38;5;28mself\u001b[39m, key):\n\u001b[1;32m--> 974\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(key)\n",
      "\u001b[1;31mKeyError\u001b[0m: 'Voter_ID'",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\pandas\\core\\computation\\scope.py:206\u001b[0m, in \u001b[0;36mScope.resolve\u001b[1;34m(self, key, is_local)\u001b[0m\n\u001b[0;32m    202\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m    203\u001b[0m     \u001b[38;5;66;03m# last ditch effort we look in temporaries\u001b[39;00m\n\u001b[0;32m    204\u001b[0m     \u001b[38;5;66;03m# these are created when parsing indexing expressions\u001b[39;00m\n\u001b[0;32m    205\u001b[0m     \u001b[38;5;66;03m# e.g., df[df > 0]\u001b[39;00m\n\u001b[1;32m--> 206\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtemps\u001b[49m\u001b[43m[\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m]\u001b[49m\n\u001b[0;32m    207\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n\u001b[0;32m    208\u001b[0m     \u001b[38;5;66;03m# runtime import because ops imports from scope\u001b[39;00m\n",
      "\u001b[1;31mKeyError\u001b[0m: 'Voter_ID'",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[1;31mUndefinedVariableError\u001b[0m                    Traceback (most recent call last)",
      "Input \u001b[1;32mIn [1]\u001b[0m, in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m     77\u001b[0m votes\u001b[38;5;241m.\u001b[39mhead()\n\u001b[0;32m     79\u001b[0m \u001b[38;5;66;03m#Create the list of songs that PERSON_SELECTED voted for\u001b[39;00m\n\u001b[1;32m---> 80\u001b[0m songVotes \u001b[38;5;241m=\u001b[39m \u001b[43msongsVotedFor\u001b[49m\u001b[43m(\u001b[49m\u001b[43mPERSON_SELECTED\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvotes\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     82\u001b[0m \u001b[38;5;66;03m#Create the dataframe of tallied votes\u001b[39;00m\n\u001b[0;32m     83\u001b[0m voteDF \u001b[38;5;241m=\u001b[39m tallyVotes(songVotes, submissions)\n",
      "Input \u001b[1;32mIn [1]\u001b[0m, in \u001b[0;36msongsVotedFor\u001b[1;34m(voterName, sourceDF)\u001b[0m\n\u001b[0;32m     28\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21msongsVotedFor\u001b[39m(voterName, sourceDF):\n\u001b[0;32m     29\u001b[0m     \u001b[38;5;66;03m#Create new dataframe withn only rows of voterName\u001b[39;00m\n\u001b[1;32m---> 30\u001b[0m     newDF \u001b[38;5;241m=\u001b[39m \u001b[43msourceDF\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mquery\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mVoter_ID == \u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mvoterName\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[0;32m     31\u001b[0m     songList \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m     32\u001b[0m     \u001b[38;5;66;03m#Add songs from this into array\u001b[39;00m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\pandas\\core\\frame.py:4113\u001b[0m, in \u001b[0;36mDataFrame.query\u001b[1;34m(self, expr, inplace, **kwargs)\u001b[0m\n\u001b[0;32m   4111\u001b[0m kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlevel\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m kwargs\u001b[38;5;241m.\u001b[39mpop(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlevel\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;241m0\u001b[39m) \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[0;32m   4112\u001b[0m kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtarget\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m-> 4113\u001b[0m res \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39meval(expr, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m   4115\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m   4116\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mloc[res]\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\pandas\\core\\frame.py:4242\u001b[0m, in \u001b[0;36mDataFrame.eval\u001b[1;34m(self, expr, inplace, **kwargs)\u001b[0m\n\u001b[0;32m   4239\u001b[0m     kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtarget\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\n\u001b[0;32m   4240\u001b[0m kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mresolvers\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mtuple\u001b[39m(kwargs\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mresolvers\u001b[39m\u001b[38;5;124m\"\u001b[39m, ())) \u001b[38;5;241m+\u001b[39m resolvers\n\u001b[1;32m-> 4242\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _eval(expr, inplace\u001b[38;5;241m=\u001b[39minplace, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\pandas\\core\\computation\\eval.py:350\u001b[0m, in \u001b[0;36meval\u001b[1;34m(expr, parser, engine, truediv, local_dict, global_dict, resolvers, level, target, inplace)\u001b[0m\n\u001b[0;32m    341\u001b[0m \u001b[38;5;66;03m# get our (possibly passed-in) scope\u001b[39;00m\n\u001b[0;32m    342\u001b[0m env \u001b[38;5;241m=\u001b[39m ensure_scope(\n\u001b[0;32m    343\u001b[0m     level \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m,\n\u001b[0;32m    344\u001b[0m     global_dict\u001b[38;5;241m=\u001b[39mglobal_dict,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    347\u001b[0m     target\u001b[38;5;241m=\u001b[39mtarget,\n\u001b[0;32m    348\u001b[0m )\n\u001b[1;32m--> 350\u001b[0m parsed_expr \u001b[38;5;241m=\u001b[39m \u001b[43mExpr\u001b[49m\u001b[43m(\u001b[49m\u001b[43mexpr\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mengine\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mengine\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mparser\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mparser\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43menv\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43menv\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    352\u001b[0m \u001b[38;5;66;03m# construct the engine and evaluate the parsed expression\u001b[39;00m\n\u001b[0;32m    353\u001b[0m eng \u001b[38;5;241m=\u001b[39m ENGINES[engine]\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\pandas\\core\\computation\\expr.py:811\u001b[0m, in \u001b[0;36mExpr.__init__\u001b[1;34m(self, expr, engine, parser, env, level)\u001b[0m\n\u001b[0;32m    809\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mparser \u001b[38;5;241m=\u001b[39m parser\n\u001b[0;32m    810\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_visitor \u001b[38;5;241m=\u001b[39m PARSERS[parser](\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39menv, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mengine, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mparser)\n\u001b[1;32m--> 811\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mterms \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mparse\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\pandas\\core\\computation\\expr.py:830\u001b[0m, in \u001b[0;36mExpr.parse\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    826\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mparse\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[0;32m    827\u001b[0m     \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m    828\u001b[0m \u001b[38;5;124;03m    Parse an expression.\u001b[39;00m\n\u001b[0;32m    829\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[1;32m--> 830\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_visitor\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvisit\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexpr\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\pandas\\core\\computation\\expr.py:415\u001b[0m, in \u001b[0;36mBaseExprVisitor.visit\u001b[1;34m(self, node, **kwargs)\u001b[0m\n\u001b[0;32m    413\u001b[0m method \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvisit_\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m+\u001b[39m \u001b[38;5;28mtype\u001b[39m(node)\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\n\u001b[0;32m    414\u001b[0m visitor \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mgetattr\u001b[39m(\u001b[38;5;28mself\u001b[39m, method)\n\u001b[1;32m--> 415\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m visitor(node, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\pandas\\core\\computation\\expr.py:421\u001b[0m, in \u001b[0;36mBaseExprVisitor.visit_Module\u001b[1;34m(self, node, **kwargs)\u001b[0m\n\u001b[0;32m    419\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mSyntaxError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124monly a single expression is allowed\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m    420\u001b[0m expr \u001b[38;5;241m=\u001b[39m node\u001b[38;5;241m.\u001b[39mbody[\u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m--> 421\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mvisit(expr, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\pandas\\core\\computation\\expr.py:415\u001b[0m, in \u001b[0;36mBaseExprVisitor.visit\u001b[1;34m(self, node, **kwargs)\u001b[0m\n\u001b[0;32m    413\u001b[0m method \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvisit_\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m+\u001b[39m \u001b[38;5;28mtype\u001b[39m(node)\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\n\u001b[0;32m    414\u001b[0m visitor \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mgetattr\u001b[39m(\u001b[38;5;28mself\u001b[39m, method)\n\u001b[1;32m--> 415\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m visitor(node, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\pandas\\core\\computation\\expr.py:424\u001b[0m, in \u001b[0;36mBaseExprVisitor.visit_Expr\u001b[1;34m(self, node, **kwargs)\u001b[0m\n\u001b[0;32m    423\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mvisit_Expr\u001b[39m(\u001b[38;5;28mself\u001b[39m, node, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m--> 424\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mvisit(node\u001b[38;5;241m.\u001b[39mvalue, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\pandas\\core\\computation\\expr.py:415\u001b[0m, in \u001b[0;36mBaseExprVisitor.visit\u001b[1;34m(self, node, **kwargs)\u001b[0m\n\u001b[0;32m    413\u001b[0m method \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvisit_\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m+\u001b[39m \u001b[38;5;28mtype\u001b[39m(node)\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\n\u001b[0;32m    414\u001b[0m visitor \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mgetattr\u001b[39m(\u001b[38;5;28mself\u001b[39m, method)\n\u001b[1;32m--> 415\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m visitor(node, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\pandas\\core\\computation\\expr.py:723\u001b[0m, in \u001b[0;36mBaseExprVisitor.visit_Compare\u001b[1;34m(self, node, **kwargs)\u001b[0m\n\u001b[0;32m    721\u001b[0m     op \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtranslate_In(ops[\u001b[38;5;241m0\u001b[39m])\n\u001b[0;32m    722\u001b[0m     binop \u001b[38;5;241m=\u001b[39m ast\u001b[38;5;241m.\u001b[39mBinOp(op\u001b[38;5;241m=\u001b[39mop, left\u001b[38;5;241m=\u001b[39mnode\u001b[38;5;241m.\u001b[39mleft, right\u001b[38;5;241m=\u001b[39mcomps[\u001b[38;5;241m0\u001b[39m])\n\u001b[1;32m--> 723\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvisit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbinop\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    725\u001b[0m \u001b[38;5;66;03m# recursive case: we have a chained comparison, a CMP b CMP c, etc.\u001b[39;00m\n\u001b[0;32m    726\u001b[0m left \u001b[38;5;241m=\u001b[39m node\u001b[38;5;241m.\u001b[39mleft\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\pandas\\core\\computation\\expr.py:415\u001b[0m, in \u001b[0;36mBaseExprVisitor.visit\u001b[1;34m(self, node, **kwargs)\u001b[0m\n\u001b[0;32m    413\u001b[0m method \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvisit_\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m+\u001b[39m \u001b[38;5;28mtype\u001b[39m(node)\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\n\u001b[0;32m    414\u001b[0m visitor \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mgetattr\u001b[39m(\u001b[38;5;28mself\u001b[39m, method)\n\u001b[1;32m--> 415\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m visitor(node, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\pandas\\core\\computation\\expr.py:536\u001b[0m, in \u001b[0;36mBaseExprVisitor.visit_BinOp\u001b[1;34m(self, node, **kwargs)\u001b[0m\n\u001b[0;32m    535\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mvisit_BinOp\u001b[39m(\u001b[38;5;28mself\u001b[39m, node, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m--> 536\u001b[0m     op, op_class, left, right \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_maybe_transform_eq_ne\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnode\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    537\u001b[0m     left, right \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_maybe_downcast_constants(left, right)\n\u001b[0;32m    538\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_maybe_evaluate_binop(op, op_class, left, right)\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\pandas\\core\\computation\\expr.py:456\u001b[0m, in \u001b[0;36mBaseExprVisitor._maybe_transform_eq_ne\u001b[1;34m(self, node, left, right)\u001b[0m\n\u001b[0;32m    454\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_maybe_transform_eq_ne\u001b[39m(\u001b[38;5;28mself\u001b[39m, node, left\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, right\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[0;32m    455\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m left \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m--> 456\u001b[0m         left \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvisit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnode\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mleft\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mside\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mleft\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[0;32m    457\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m right \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m    458\u001b[0m         right \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mvisit(node\u001b[38;5;241m.\u001b[39mright, side\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mright\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\pandas\\core\\computation\\expr.py:415\u001b[0m, in \u001b[0;36mBaseExprVisitor.visit\u001b[1;34m(self, node, **kwargs)\u001b[0m\n\u001b[0;32m    413\u001b[0m method \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvisit_\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m+\u001b[39m \u001b[38;5;28mtype\u001b[39m(node)\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\n\u001b[0;32m    414\u001b[0m visitor \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mgetattr\u001b[39m(\u001b[38;5;28mself\u001b[39m, method)\n\u001b[1;32m--> 415\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m visitor(node, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\pandas\\core\\computation\\expr.py:549\u001b[0m, in \u001b[0;36mBaseExprVisitor.visit_Name\u001b[1;34m(self, node, **kwargs)\u001b[0m\n\u001b[0;32m    548\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mvisit_Name\u001b[39m(\u001b[38;5;28mself\u001b[39m, node, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m--> 549\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mterm_type(node\u001b[38;5;241m.\u001b[39mid, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39menv, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\pandas\\core\\computation\\ops.py:98\u001b[0m, in \u001b[0;36mTerm.__init__\u001b[1;34m(self, name, env, side, encoding)\u001b[0m\n\u001b[0;32m     96\u001b[0m tname \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mstr\u001b[39m(name)\n\u001b[0;32m     97\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mis_local \u001b[38;5;241m=\u001b[39m tname\u001b[38;5;241m.\u001b[39mstartswith(LOCAL_TAG) \u001b[38;5;129;01mor\u001b[39;00m tname \u001b[38;5;129;01min\u001b[39;00m DEFAULT_GLOBALS\n\u001b[1;32m---> 98\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_value \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_resolve_name\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     99\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mencoding \u001b[38;5;241m=\u001b[39m encoding\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\pandas\\core\\computation\\ops.py:115\u001b[0m, in \u001b[0;36mTerm._resolve_name\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    114\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_resolve_name\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m--> 115\u001b[0m     res \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43menv\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresolve\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlocal_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mis_local\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mis_local\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    116\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mupdate(res)\n\u001b[0;32m    118\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(res, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mndim\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;129;01mand\u001b[39;00m res\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m2\u001b[39m:\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.10_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python310\\site-packages\\pandas\\core\\computation\\scope.py:211\u001b[0m, in \u001b[0;36mScope.resolve\u001b[1;34m(self, key, is_local)\u001b[0m\n\u001b[0;32m    207\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n\u001b[0;32m    208\u001b[0m     \u001b[38;5;66;03m# runtime import because ops imports from scope\u001b[39;00m\n\u001b[0;32m    209\u001b[0m     \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mpandas\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcore\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mcomputation\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mops\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m UndefinedVariableError\n\u001b[1;32m--> 211\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m UndefinedVariableError(key, is_local) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n",
      "\u001b[1;31mUndefinedVariableError\u001b[0m: name 'Voter_ID' is not defined"
     ]
    }
   ],
   "source": [
    "#Import necessary libraries (and have them installed too)\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as mpl\n",
    "import seaborn as sbrn\n",
    "import zipfile\n",
    "\n",
    "#Adjust figure size so graph produced is readable\n",
    "mpl.rcParams[\"figure.figsize\"] = (20,5)\n",
    "\n",
    "#Unzip new Music League data\n",
    "with zipfile.ZipFile('export.zip', 'r') as zip_ref:\n",
    "    zip_ref.extractall()\n",
    "\n",
    "#Import CSV files\n",
    "competitors = pd.read_csv('competitors.csv')\n",
    "rounds = pd.read_csv('rounds.csv')\n",
    "submissions = pd.read_csv('submissions.csv')\n",
    "votes = pd.read_csv('votes.csv')\n",
    "\n",
    "#Change column names to be more code-friendly\n",
    "competitors.columns = competitors.columns.str.replace(' ','_')\n",
    "rounds.columns = rounds.columns.str.replace(' ','_')\n",
    "submissions.columns = submissions.columns.str.replace(' ','_')\n",
    "votes.columns = votes.columns.str.replace(' ','_')\n",
    "\n",
    "#Global Vars\n",
    "pplArr = [\"Jeffrey Blitt\", \"Dean\", \"Dalton\", \"Jake Sorscher\", \"eestevens0131\", \"Sam Livermore\", \"James Cameron\", \"Lucy\", \"Annmarie\", \"William Sherwood\", \"Sarah\", \"Kate\", \"Athreya Ramesh\", \"joshy.harvey\"]\n",
    "    #Array of competitor names for the \"Rat King\" music league, use to input into songsVotedFor\n",
    "    \n",
    "###LOOK HERE LOOK HERE###\n",
    "\n",
    "PERSON_SELECTED = \"James Cameron\"\n",
    "    #String, input one of the above into it to create their graph\n",
    "\n",
    "#Function: songsVotedFor\n",
    "#Returns: list\n",
    "#Input: voterName (str, name of competitor), sourceDF (dataframe, created from votes.csv)\n",
    "#Contract: Uses sourceDF to create a string of every song voted for by voterName\n",
    "\n",
    "def songsVotedFor(voterName, sourceDF):\n",
    "    #Create new dataframe withn only rows of voterName\n",
    "    queryString = 'Voter_ID == \"' + voterName + '\" and Points_Assigned != 0'\n",
    "    newDF = sourceDF.query(queryString)\n",
    "    songList = []\n",
    "    #Add songs from this into array\n",
    "    for index, row in newDF.iterrows():\n",
    "        songList.append(row['Spotify_URI'])\n",
    "    songList = list(set(songList))\n",
    "    return songList\n",
    "\n",
    "#Function: tallyVotes\n",
    "#Returns: dataframe\n",
    "#Input: songArr (array of Spotify URI strings), searchDF (dataframe, created from submissions.csv), voterName (to exclude)\n",
    "#Contract: Searches song submissions in searchDF, crossreferencing with songArr to count how many votes were given to which person\n",
    "\n",
    "def tallyVotes(songArr, searchDF, voterName):\n",
    "    #Create a counter that tracks votes for each person\n",
    "    countArr = [0] * 14\n",
    "    for songID in songArr:\n",
    "        #Extracts songs matching entries in songArr from searchDF\n",
    "        newDF = searchDF.query('Spotify_URI == \"' + songID + '\"')\n",
    "        #If the submitter for a given song is in pplArr, increment their counter\n",
    "        for index, name in enumerate(pplArr):\n",
    "            if name == newDF.iloc[0]['Submitter_ID'] and name != voterName:\n",
    "                countArr[index] += 1\n",
    "    #Aligns the peron's counters with their names\n",
    "    voteDict = dict(zip(pplArr, countArr))\n",
    "    return pd.DataFrame(voteDict.items(), columns=['Person', 'Votes'])\n",
    "\n",
    "\n",
    "#----------------------------------------------------------------------------------------------------------------\n",
    "\n",
    "#Create a new dataframe that contains a mapping of internal Round IDs to Round Names\n",
    "roundsByID = rounds[[\"ID\", \"Name\"]]\n",
    "\n",
    "#Replace internal ids with names in the 'submissions' dataset\n",
    "for index, row in competitors.iterrows():\n",
    "    submissions.replace(to_replace = row['ID'], value = row['Name'], inplace=True)\n",
    "for index, row in roundsByID.iterrows():\n",
    "    submissions.replace(to_replace = row['ID'], value = row['Name'], inplace=True)\n",
    "\n",
    "#Replace internal ids with names in the 'votes' dataset    \n",
    "for index, row in roundsByID.iterrows():\n",
    "    votes.replace(to_replace = row['ID'], value = row['Name'], inplace=True)\n",
    "for index, row in competitors.iterrows():\n",
    "    votes.replace(to_replace = row['ID'], value = row['Name'], inplace=True)\n",
    "    \n",
    "#Create the list of songs that PERSON_SELECTED voted for\n",
    "songVotes = songsVotedFor(PERSON_SELECTED, votes)\n",
    "\n",
    "#Create the dataframe of tallied votes\n",
    "voteDF = tallyVotes(songVotes, submissions, PERSON_SELECTED)\n",
    "\n",
    "#Create list of vote numbers for labeling\n",
    "voteList = voteDF['Votes'].tolist()\n",
    "\n",
    "#Create graph from this dataframe\n",
    "voteGraph = voteDF.groupby(['Person']).median().sort_values(\"Votes\", ascending=False).plot.bar(title=PERSON_SELECTED + \"'s Music League Votes\")\n",
    "\n",
    "null = voteGraph.bar_label(voteGraph.containers[0])"
   ]
  }
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