SUSA_Music_Moods.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
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    "colab_type": "code",
    "collapsed": true,
    "id": "-FDdcg-BuZcx"
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import spotipy\n",
    "import spotipy.util as util\n",
    "import json\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.axes as axes\n",
    "from tqdm import tqdm_notebook\n",
    "from google.cloud import language_v1\n",
    "from google.cloud.language_v1 import enums\n",
    "import six\n",
    "import os\n",
    "from scipy import optimize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "collapsed": true,
    "id": "kTBBfIYUp8KD"
   },
   "outputs": [],
   "source": [
    "key_file = 'assets/keys.json'\n",
    "keys = json.load(open(key_file))\n",
    "\n",
    "SPOTIPY_CLIENT_ID= keys[\"client_id\"]\n",
    "SPOTIPY_CLIENT_SECRET= keys[\"client_secret\"]\n",
    "SPOTIPY_REDIRECT_URI= keys[\"redirect_url\"]\n",
    "\n",
    "os.environ[\"GOOGLE_APPLICATION_CREDENTIALS\"]=\"/Users/carlosortega/Documents/GitHub/SUSA-Research-MusicMoods/assets/google_keys.json\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 292
    },
    "colab_type": "code",
    "collapsed": true,
    "id": "XZTKo-o4q8T1",
    "outputId": "ae0e6ca8-7cf0-43be-9926-a595ac34b14b"
   },
   "outputs": [],
   "source": [
    "token = util.prompt_for_user_token(\"1274418332\", \n",
    "                                   scope = \"user-library-read\", \n",
    "                                   client_id=SPOTIPY_CLIENT_ID, \n",
    "                                   client_secret=SPOTIPY_CLIENT_SECRET, \n",
    "                                   redirect_uri = SPOTIPY_REDIRECT_URI)\n",
    "spotify = spotipy.Spotify(auth=token)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
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    },
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    "id": "w2XyvyiNRoVZ",
    "outputId": "561f6a61-07ce-47c1-d92e-e72d7285103e"
   },
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Rank</th>\n",
       "      <th>Song</th>\n",
       "      <th>Artist</th>\n",
       "      <th>Year</th>\n",
       "      <th>Lyrics</th>\n",
       "      <th>Source</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>wooly bully</td>\n",
       "      <td>sam the sham and the pharaohs</td>\n",
       "      <td>1965</td>\n",
       "      <td>sam the sham miscellaneous wooly bully wooly b...</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>i cant help myself sugar pie honey bunch</td>\n",
       "      <td>four tops</td>\n",
       "      <td>1965</td>\n",
       "      <td>sugar pie honey bunch you know that i love yo...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>i cant get no satisfaction</td>\n",
       "      <td>the rolling stones</td>\n",
       "      <td>1965</td>\n",
       "      <td></td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>you were on my mind</td>\n",
       "      <td>we five</td>\n",
       "      <td>1965</td>\n",
       "      <td>when i woke up this morning you were on my mi...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>youve lost that lovin feelin</td>\n",
       "      <td>the righteous brothers</td>\n",
       "      <td>1965</td>\n",
       "      <td>you never close your eyes anymore when i kiss...</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "   Rank                                      Song  \\\n",
       "0     1                               wooly bully   \n",
       "1     2  i cant help myself sugar pie honey bunch   \n",
       "2     3                i cant get no satisfaction   \n",
       "3     4                       you were on my mind   \n",
       "4     5              youve lost that lovin feelin   \n",
       "\n",
       "                          Artist  Year  \\\n",
       "0  sam the sham and the pharaohs  1965   \n",
       "1                      four tops  1965   \n",
       "2             the rolling stones  1965   \n",
       "3                        we five  1965   \n",
       "4         the righteous brothers  1965   \n",
       "\n",
       "                                              Lyrics  Source  \n",
       "0  sam the sham miscellaneous wooly bully wooly b...     3.0  \n",
       "1   sugar pie honey bunch you know that i love yo...     1.0  \n",
       "2                                                        1.0  \n",
       "3   when i woke up this morning you were on my mi...     1.0  \n",
       "4   you never close your eyes anymore when i kiss...     1.0  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "billboard = pd.read_csv(\"data/billboard_lyrics_1964-2015.csv\")\n",
    "billboard['Query'] = 'artist: ' + billboard['Artist'] + ', track: ' + billboard['Song']\n",
    "billboard.drop(columns=['Query'], inplace=True)\n",
    "billboard.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "E0O2e6P724y5"
   },
   "outputs": [
    {
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     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "valences = []\n",
    "durations = []\n",
    "for index, row in tqdm_notebook(billboard.iterrows()):\n",
    "    try:\n",
    "        curr_song = spotify.search(row['Query'])['tracks']['items'][0]['id']\n",
    "        valence = spotify.audio_features(curr_song)[0]['valence']\n",
    "        duration = spotify.audio_features(curr_song)[0]['duration_ms']\n",
    "        durations.append(duration)\n",
    "        valences.append(float(valence))\n",
    "    except:\n",
    "        valences.append(np.nan)\n",
    "        durations.append(np.nan)\n",
    "\n",
    "billboard['Valence'] = valences\n",
    "billboard['Duration_ms'] = durations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Rank</th>\n",
       "      <th>Song</th>\n",
       "      <th>Artist</th>\n",
       "      <th>Year</th>\n",
       "      <th>Lyrics</th>\n",
       "      <th>Source</th>\n",
       "      <th>Valence</th>\n",
       "      <th>Duration_ms</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>wooly bully</td>\n",
       "      <td>sam the sham and the pharaohs</td>\n",
       "      <td>1965</td>\n",
       "      <td>sam the sham miscellaneous wooly bully wooly b...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>i cant help myself sugar pie honey bunch</td>\n",
       "      <td>four tops</td>\n",
       "      <td>1965</td>\n",
       "      <td>sugar pie honey bunch you know that i love yo...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>i cant get no satisfaction</td>\n",
       "      <td>the rolling stones</td>\n",
       "      <td>1965</td>\n",
       "      <td></td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>you were on my mind</td>\n",
       "      <td>we five</td>\n",
       "      <td>1965</td>\n",
       "      <td>when i woke up this morning you were on my mi...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>youve lost that lovin feelin</td>\n",
       "      <td>the righteous brothers</td>\n",
       "      <td>1965</td>\n",
       "      <td>you never close your eyes anymore when i kiss...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Rank                                      Song  \\\n",
       "0     1                               wooly bully   \n",
       "1     2  i cant help myself sugar pie honey bunch   \n",
       "2     3                i cant get no satisfaction   \n",
       "3     4                       you were on my mind   \n",
       "4     5              youve lost that lovin feelin   \n",
       "\n",
       "                          Artist  Year  \\\n",
       "0  sam the sham and the pharaohs  1965   \n",
       "1                      four tops  1965   \n",
       "2             the rolling stones  1965   \n",
       "3                        we five  1965   \n",
       "4         the righteous brothers  1965   \n",
       "\n",
       "                                              Lyrics  Source  Valence  \\\n",
       "0  sam the sham miscellaneous wooly bully wooly b...     3.0      NaN   \n",
       "1   sugar pie honey bunch you know that i love yo...     1.0      NaN   \n",
       "2                                                        1.0      NaN   \n",
       "3   when i woke up this morning you were on my mi...     1.0      NaN   \n",
       "4   you never close your eyes anymore when i kiss...     1.0      NaN   \n",
       "\n",
       "   Duration_ms  \n",
       "0          NaN  \n",
       "1          NaN  \n",
       "2          NaN  \n",
       "3          NaN  \n",
       "4          NaN  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "billboard.to_csv(\"data/billboard_with_data.csv\", index=False)\n",
    "billboard.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Rank</th>\n",
       "      <th>Song</th>\n",
       "      <th>Artist</th>\n",
       "      <th>Year</th>\n",
       "      <th>Lyrics</th>\n",
       "      <th>Source</th>\n",
       "      <th>Valence</th>\n",
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       "Empty DataFrame\n",
       "Columns: [Rank, Song, Artist, Year, Lyrics, Source, Valence, Duration_ms]\n",
       "Index: []"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "billboard_updated = pd.read_csv(\"data/billboard_with_data.csv\")\n",
    "billboard_updated['Lyrics'].replace('  ', np.nan, inplace=True)\n",
    "billboard_updated.dropna(axis=0,inplace=True)\n",
    "billboard_updated.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def authenticate():\n",
    "    from google.cloud import storage\n",
    "\n",
    "    storage_client = storage.Client()\n",
    "\n",
    "    # Make an authenticated API request\n",
    "    buckets = list(storage_client.list_buckets())\n",
    "\n",
    "authenticate()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "lyrics = []\n",
    "for index, row in tqdm_notebook(billboard_updated.iterrows()):\n",
    "    lyric = row['Lyrics']\n",
    "    if isinstance(lyric, six.binary_type):\n",
    "        lyric = lyric.decode('utf-8')\n",
    "    lyrics.append(lyric)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "model_id": "e282c5f92b1b42c5b4c03072bbefdb5e",
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       "HBox(children=(IntProgress(value=1, bar_style='info', max=1), HTML(value='')))"
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "client = language_v1.LanguageServiceClient()\n",
    "\n",
    "type_ = enums.Document.Type.PLAIN_TEXT\n",
    "\n",
    "sentiments = []\n",
    "for i in tqdm_notebook(range(len(lyrics))):\n",
    "    document = {'type': type_, 'content': lyrics[i]}\n",
    "    \n",
    "    try:\n",
    "        response = client.analyze_sentiment(document)\n",
    "    except:\n",
    "        sentiments.append(np.nan)\n",
    "        continue\n",
    "    \n",
    "    sentiment = response.document_sentiment\n",
    "    \n",
    "    sentiments.append(sentiment.score)\n",
    "\n",
    "billboard_updated['Sentiment'] = sentiments\n",
    "billboard_updated.dropna(axis=0,inplace=True)\n",
    "billboard_updated.to_csv(\"data/billboard_with_data.csv\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\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>Rank</th>\n",
       "      <th>Song</th>\n",
       "      <th>Artist</th>\n",
       "      <th>Year</th>\n",
       "      <th>Lyrics</th>\n",
       "      <th>Source</th>\n",
       "      <th>Valence</th>\n",
       "      <th>Duration_ms</th>\n",
       "      <th>Sentiment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [Rank, Song, Artist, Year, Lyrics, Source, Valence, Duration_ms, Sentiment]\n",
       "Index: []"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "billboard_updated = pd.read_csv(\"data/billboard_with_data.csv\")\n",
    "billboard_updated.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Valence</th>\n",
       "      <th>Sentiment</th>\n",
       "      <th>Duration_ms</th>\n",
       "      <th>Word Count</th>\n",
       "      <th>Lyrical Density</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [Year, Valence, Sentiment, Duration_ms, Word Count, Lyrical Density]\n",
       "Index: []"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#New Table with Only Necessary Info\n",
    "stats = billboard_updated[['Year', 'Valence', 'Sentiment', 'Duration_ms']]\n",
    "stats['Word Count'] = billboard_updated['Lyrics'].apply(len) \n",
    "stats['Lyrical Density'] = stats['Word Count'] / stats['Duration_ms'] * 1000\n",
    "stats.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "min() arg is an empty sequence",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-25-bf4f673034f4>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mgloom_index\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mstats\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Valence'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mstats\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Sentiment'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mstats\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Lyrical Density'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mstats\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Gloom Index'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgloom_index\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mstats\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Normalized Gloom Index'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mgloom_index\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mmin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgloom_index\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mmax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgloom_index\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mmin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgloom_index\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m \u001b[0mstats\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhead\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: min() arg is an empty sequence"
     ]
    }
   ],
   "source": [
    "gloom_index = ((1 - stats['Valence']) + (stats['Sentiment'] * (1 + stats['Lyrical Density']))) / 2\n",
    "stats['Gloom Index'] = gloom_index\n",
    "stats['Normalized Gloom Index'] = (gloom_index - min(gloom_index)) / (max(gloom_index) - min(gloom_index))\n",
    "stats.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "\"['Normalized Gloom Index'] not in index\"",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-26-e0c7d651bf38>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mgloom_by_year\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mstats\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Year'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'Normalized Gloom Index'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgloom_by_year\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Year'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgloom_by_year\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Normalized Gloom Index'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m','\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/carlosortega/anaconda/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   2932\u001b[0m                 \u001b[0mkey\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2933\u001b[0m             indexer = self.loc._convert_to_indexer(key, axis=1,\n\u001b[0;32m-> 2934\u001b[0;31m                                                    raise_missing=True)\n\u001b[0m\u001b[1;32m   2935\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2936\u001b[0m         \u001b[0;31m# take() does not accept boolean indexers\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/carlosortega/anaconda/lib/python3.6/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_convert_to_indexer\u001b[0;34m(self, obj, axis, is_setter, raise_missing)\u001b[0m\n\u001b[1;32m   1352\u001b[0m                 kwargs = {'raise_missing': True if is_setter else\n\u001b[1;32m   1353\u001b[0m                           raise_missing}\n\u001b[0;32m-> 1354\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_listlike_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1355\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1356\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/carlosortega/anaconda/lib/python3.6/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_get_listlike_indexer\u001b[0;34m(self, key, axis, raise_missing)\u001b[0m\n\u001b[1;32m   1159\u001b[0m         self._validate_read_indexer(keyarr, indexer,\n\u001b[1;32m   1160\u001b[0m                                     \u001b[0mo\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_axis_number\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1161\u001b[0;31m                                     raise_missing=raise_missing)\n\u001b[0m\u001b[1;32m   1162\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mkeyarr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1163\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/carlosortega/anaconda/lib/python3.6/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_validate_read_indexer\u001b[0;34m(self, key, indexer, axis, raise_missing)\u001b[0m\n\u001b[1;32m   1250\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'loc'\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mraise_missing\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1251\u001b[0m                 \u001b[0mnot_found\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1252\u001b[0;31m                 \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"{} not in index\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnot_found\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1253\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1254\u001b[0m             \u001b[0;31m# we skip the warning on Categorical/Interval\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: \"['Normalized Gloom Index'] not in index\""
     ]
    }
   ],
   "source": [
    "gloom_by_year = stats[['Year', 'Normalized Gloom Index']]\n",
    "plt.plot(gloom_by_year['Year'], gloom_by_year['Normalized Gloom Index'], ',')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'gloom_by_year' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-27-30b1f079912c>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmeans\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgloom_by_year\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgroupby\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mby\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"Year\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmean\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreset_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mmeans\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Year\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"Normalized Gloom Index\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'gloom_by_year' is not defined"
     ]
    }
   ],
   "source": [
    "means = gloom_by_year.groupby(by=\"Year\").mean().reset_index()\n",
    "means.plot(\"Year\", \"Normalized Gloom Index\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'Normalized Gloom Index'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m/Users/carlosortega/anaconda/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   2656\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2657\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2658\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'Normalized Gloom Index'",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-28-35beb7dcf1aa>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mn60\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstats\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mstats\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Year'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;36m1970\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Normalized Gloom Index'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mn70\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstats\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstats\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Year'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m>=\u001b[0m \u001b[0;36m1970\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m&\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mstats\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Year'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;36m1980\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Normalized Gloom Index'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mn80\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstats\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstats\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Year'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m>=\u001b[0m \u001b[0;36m1980\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m&\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mstats\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Year'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;36m1990\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Normalized Gloom Index'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mn90\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstats\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstats\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Year'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m>=\u001b[0m \u001b[0;36m1990\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m&\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mstats\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Year'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;36m2000\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Normalized Gloom Index'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mn20\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstats\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstats\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Year'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m>=\u001b[0m \u001b[0;36m2000\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m&\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mstats\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Year'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;36m2010\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Normalized Gloom Index'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/carlosortega/anaconda/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   2925\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnlevels\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2926\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2927\u001b[0;31m             \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2928\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mis_integer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2929\u001b[0m                 \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/carlosortega/anaconda/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   2657\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2658\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2659\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_maybe_cast_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2660\u001b[0m         \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtolerance\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2661\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msize\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'Normalized Gloom Index'"
     ]
    }
   ],
   "source": [
    "n60 = list(stats[stats['Year'] < 1970]['Normalized Gloom Index'])\n",
    "n70 = list(stats[(stats['Year'] >= 1970) & (stats['Year'] < 1980)]['Normalized Gloom Index'])\n",
    "n80 = list(stats[(stats['Year'] >= 1980) & (stats['Year'] < 1990)]['Normalized Gloom Index'])\n",
    "n90 = list(stats[(stats['Year'] >= 1990) & (stats['Year'] < 2000)]['Normalized Gloom Index'])\n",
    "n20 = list(stats[(stats['Year'] >= 2000) & (stats['Year'] < 2010)]['Normalized Gloom Index'])\n",
    "n2_1 = list(stats[(stats['Year'] >= 2010)]['Normalized Gloom Index'])\n",
    "\n",
    "labels = ['1960s', '1970s', '1980s', '1990s', '2000s', '2010s']\n",
    "\n",
    "plt.boxplot([n60, n70, n80, n90, n20, n2_1], showfliers=False, labels=labels)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ingIeBs4tjh+MiEeL8+6h8UFgZjVSpdFsVVWpOqib4N8GnClpZbE4uxbYPOuc+4GLJS2Q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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x15094726d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(means['Year'], means['Normalized Gloom Index'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "years = means[\"Year\"]\n",
    "gloom_index = means['Normalized Gloom Index']\n",
    "z = np.polyfit(x=years, y=gloom_index, deg=3)\n",
    "p = np.poly1d(z)\n",
    "xp = range(1965, 2016)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AcUG/JXAC8B+x49uB7Yk1Q0QkizVtBYefE27u8NFKWDkbVr4cvg0se/arsi07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\nBX4RkYhR4BcRiZj/B8aNFH2MmZY5AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1509bbf9b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = plt.plot(years, gloom_index, '.', xp, p(xp), '-')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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g5QGHdczCsg2PbT3KjvoOvv7RZaytymf9/HwefaduyjpCsE694Rm/2Wsapv9n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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1513df6fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "means = gloom_by_year.groupby(by=\"Year\").mean().reset_index()\n",
    "means.plot(\"Year\", \"Normalized Gloom Index\", legend=False)\n",
    "\n",
    "#MLK Assassination\n",
    "plt.axvline(x=1968, color='r', linewidth=1, linestyle='--')\n",
    "\n",
    "#Moon Landing\n",
    "plt.axvline(x=1969, color='b', linewidth=1, linestyle='--')\n",
    "\n",
    "#End of Vietnam War\n",
    "plt.axvline(x=1975, color='r', linewidth=1, linestyle='--')\n",
    "\n",
    "#Iran Hostage Crisis\n",
    "plt.axvline(x=1979, color='r', linewidth=1, linestyle='--')\n",
    "\n",
    "#End of Cold War and the Fall of the Berlin Wall\n",
    "plt.axvline(x=1989, color='r', linewidth=1, linestyle='--')\n",
    "\n",
    "#End of Gulf War\n",
    "plt.axvline(x=1991, color='r', linewidth=1, linestyle='--')\n",
    "\n",
    "#Centennial Olympic Park Bombing\n",
    "plt.axvline(x=1996, color='r', linewidth=1, linestyle='--')\n",
    "\n",
    "#President Clinton Impeachment\n",
    "plt.axvline(x=1998, color='r', linewidth=1, linestyle='--')\n",
    "\n",
    "#9/11 Attacks\n",
    "plt.axvline(x=2001, color='r', linewidth=1, linestyle='--')\n",
    "\n",
    "#Obama Election Assassination\n",
    "plt.axvline(x=2008, color='r', linewidth=1, linestyle='--')\n",
    "\n",
    "#Osama Bin Laden \n",
    "plt.axvline(x=2011, color='b', linewidth=1, linestyle='--')\n",
    "\n",
    "plt.xticks([1968, 1969, 1975, 1979, 1989, 1991, 1996, 1998, 2001, 2008, 2011], ('MLK Assassination' , 'Moon Landing',\n",
    "                                                        'End of Vietnam War',\n",
    "                                                        'Iran Hostage Crisis', 'End of Cold War', 'End of Gulf War', \n",
    "                                                        'Centennial Olympic Park Bombing', 'President Clinton Impeached',\n",
    "                                                        '9/11 Attacks', 'Obama Elected', 'Osama Bin Laden Assassination')\n",
    "           , rotation=90 )\n",
    "\n",
    "\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Rank</th>\n",
       "      <th>Song</th>\n",
       "      <th>Artist</th>\n",
       "      <th>Year</th>\n",
       "      <th>Lyrics</th>\n",
       "      <th>Source</th>\n",
       "      <th>Valence</th>\n",
       "      <th>Duration_ms</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>wooly bully</td>\n",
       "      <td>sam the sham and the pharaohs</td>\n",
       "      <td>1965</td>\n",
       "      <td>sam the sham miscellaneous wooly bully wooly b...</td>\n",
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       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>i cant help myself sugar pie honey bunch</td>\n",
       "      <td>four tops</td>\n",
       "      <td>1965</td>\n",
       "      <td>sugar pie honey bunch you know that i love yo...</td>\n",
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       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>i cant get no satisfaction</td>\n",
       "      <td>the rolling stones</td>\n",
       "      <td>1965</td>\n",
       "      <td></td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>you were on my mind</td>\n",
       "      <td>we five</td>\n",
       "      <td>1965</td>\n",
       "      <td>when i woke up this morning you were on my mi...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>youve lost that lovin feelin</td>\n",
       "      <td>the righteous brothers</td>\n",
       "      <td>1965</td>\n",
       "      <td>you never close your eyes anymore when i kiss...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>downtown</td>\n",
       "      <td>petula clark</td>\n",
       "      <td>1965</td>\n",
       "      <td>when youre alone and life is making you lonel...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>help</td>\n",
       "      <td>the beatles</td>\n",
       "      <td>1965</td>\n",
       "      <td>help i need somebody help not just anybody hel...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>cant you hear my heart beat</td>\n",
       "      <td>hermans hermits</td>\n",
       "      <td>1965</td>\n",
       "      <td>carterlewis every time i see you lookin my way...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>crying in the chapel</td>\n",
       "      <td>elvis presley</td>\n",
       "      <td>1965</td>\n",
       "      <td>you saw me crying in the chapel the tears i s...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>my girl</td>\n",
       "      <td>the temptations</td>\n",
       "      <td>1965</td>\n",
       "      <td>ive got sunshine on a cloudy day when its cold...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>help me rhonda</td>\n",
       "      <td>the beach boys</td>\n",
       "      <td>1965</td>\n",
       "      <td>well since she put me down i ve been out doin ...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>king of the road</td>\n",
       "      <td>roger miller</td>\n",
       "      <td>1965</td>\n",
       "      <td>trailer for sale or rent rooms to let fifty c...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>the birds and the bees</td>\n",
       "      <td>jewel akens</td>\n",
       "      <td>1965</td>\n",
       "      <td>let me tell ya bout the birds and the bees and...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>hold me thrill me kiss me</td>\n",
       "      <td>mel carter</td>\n",
       "      <td>1965</td>\n",
       "      <td>hold me hold me never let me go until youve t...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>shotgun</td>\n",
       "      <td>junior walker  the all stars</td>\n",
       "      <td>1965</td>\n",
       "      <td>i said Ã¢shotgun shoot em for he runs now do t...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>i got you babe</td>\n",
       "      <td>sonny  cher</td>\n",
       "      <td>1965</td>\n",
       "      <td>they say were young and we dont know we wont f...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>this diamond ring</td>\n",
       "      <td>gary lewis  the playboys</td>\n",
       "      <td>1965</td>\n",
       "      <td>who wants to buy this diamond ring she took it...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>the in crowd</td>\n",
       "      <td>ramsey lewis trio</td>\n",
       "      <td>1965</td>\n",
       "      <td>instrumental</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>mrs brown youve got a lovely daughter</td>\n",
       "      <td>hermans hermits</td>\n",
       "      <td>1965</td>\n",
       "      <td>mrs brown youve got a lovely daughter girls a...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>stop in the name of love</td>\n",
       "      <td>the supremes</td>\n",
       "      <td>1965</td>\n",
       "      <td>stop in the name of love before you break my ...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>unchained melody</td>\n",
       "      <td>the righteous brothers</td>\n",
       "      <td>1965</td>\n",
       "      <td>oh my love my darling ive hungered for your t...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>silhouettes</td>\n",
       "      <td>hermans hermits</td>\n",
       "      <td>1965</td>\n",
       "      <td>slaycrewetook a walk and passed your house la...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>ill never find another you</td>\n",
       "      <td>the seekers</td>\n",
       "      <td>1965</td>\n",
       "      <td>theres a new world somewhere they call the pr...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>cara mia</td>\n",
       "      <td>jay and the americans</td>\n",
       "      <td>1965</td>\n",
       "      <td>mantovani cara mia why must we say goodbye eac...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>mr tambourine man</td>\n",
       "      <td>the byrds</td>\n",
       "      <td>1965</td>\n",
       "      <td>hey mr tambourine man play a song for me im n...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>cast your fate to the wind</td>\n",
       "      <td>sounds orchestral</td>\n",
       "      <td>1965</td>\n",
       "      <td>a month of nights a year of days octobers drif...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>yes im ready</td>\n",
       "      <td>barbara mason</td>\n",
       "      <td>1965</td>\n",
       "      <td>are you ready yes im ready are you ready yes i...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>whats new pussycat</td>\n",
       "      <td>tom jones</td>\n",
       "      <td>1965</td>\n",
       "      <td>whats new pussycat woah woah whats new pussyc...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>eve of destruction</td>\n",
       "      <td>barry mcguire</td>\n",
       "      <td>1965</td>\n",
       "      <td>the eastern world it is explodin violence fla...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>hang on sloopy</td>\n",
       "      <td>the mccoys</td>\n",
       "      <td>1965</td>\n",
       "      <td>hang on sloopy sloopy hang on hang on sloopy s...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5070</th>\n",
       "      <td>71</td>\n",
       "      <td>riptide</td>\n",
       "      <td>vance joy</td>\n",
       "      <td>2015</td>\n",
       "      <td>i was scared of dentists and the dark i was s...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5071</th>\n",
       "      <td>72</td>\n",
       "      <td>classic man</td>\n",
       "      <td>jidenna featuring roman gianarthur</td>\n",
       "      <td>2015</td>\n",
       "      <td>my name calling all night i could pull the wo...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5072</th>\n",
       "      <td>73</td>\n",
       "      <td>exs  ohs</td>\n",
       "      <td>elle king</td>\n",
       "      <td>2015</td>\n",
       "      <td>verse 1 well i had me a boy turned him into a ...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5073</th>\n",
       "      <td>74</td>\n",
       "      <td>dear future husband</td>\n",
       "      <td>meghan trainor</td>\n",
       "      <td>2015</td>\n",
       "      <td>dear future husband heres a few things youll ...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5074</th>\n",
       "      <td>75</td>\n",
       "      <td>marvin gaye</td>\n",
       "      <td>charlie puth featuring meghan trainor</td>\n",
       "      <td>2015</td>\n",
       "      <td>lets marvin gaye and get it on you got the he...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5075</th>\n",
       "      <td>76</td>\n",
       "      <td>like im gonna lose you</td>\n",
       "      <td>meghan trainor featuring john legend</td>\n",
       "      <td>2015</td>\n",
       "      <td>i found myself dreaming in silver and gold li...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5076</th>\n",
       "      <td>77</td>\n",
       "      <td>habits stay high</td>\n",
       "      <td>tove lo</td>\n",
       "      <td>2015</td>\n",
       "      <td>uhuh uhuh uhuh i eat my dinner in my bathtub ...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5077</th>\n",
       "      <td>78</td>\n",
       "      <td>the hanging tree</td>\n",
       "      <td>james newton howard featuring jennifer lawrence</td>\n",
       "      <td>2015</td>\n",
       "      <td>are you are you coming to the tree they strun...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5078</th>\n",
       "      <td>79</td>\n",
       "      <td>coco</td>\n",
       "      <td>ot genasis</td>\n",
       "      <td>2015</td>\n",
       "      <td>im in love with the coco coco coco im in love...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5079</th>\n",
       "      <td>80</td>\n",
       "      <td>bang bang</td>\n",
       "      <td>jessie j ariana grande and nicki minaj</td>\n",
       "      <td>2015</td>\n",
       "      <td>verse 1 jessie j she got a body like an hourgl...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5080</th>\n",
       "      <td>81</td>\n",
       "      <td>lay me down</td>\n",
       "      <td>sam smith</td>\n",
       "      <td>2015</td>\n",
       "      <td>yes i do i believe that one day i will be whe...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5081</th>\n",
       "      <td>82</td>\n",
       "      <td>tuesday</td>\n",
       "      <td>ilovemakonnen featuring drake</td>\n",
       "      <td>2015</td>\n",
       "      <td>hook x4 club goin up on a tuesday got your gir...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5082</th>\n",
       "      <td>83</td>\n",
       "      <td>hit the quan</td>\n",
       "      <td>ilovememphis</td>\n",
       "      <td>2015</td>\n",
       "      <td>yo yo aye im finna aye im finnaim finna show ...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5083</th>\n",
       "      <td>84</td>\n",
       "      <td>downtown</td>\n",
       "      <td>macklemore and ryan lewis featuring eric nally...</td>\n",
       "      <td>2015</td>\n",
       "      <td>i went to the moped store said fuck it salesm...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5084</th>\n",
       "      <td>85</td>\n",
       "      <td>house party</td>\n",
       "      <td>sam hunt</td>\n",
       "      <td>2015</td>\n",
       "      <td>youre on the couch blowing up my phone you do...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5085</th>\n",
       "      <td>86</td>\n",
       "      <td>ayo</td>\n",
       "      <td>chris brown and tyga</td>\n",
       "      <td>2015</td>\n",
       "      <td>i need you i need you i need you i need you i...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5086</th>\n",
       "      <td>87</td>\n",
       "      <td>kick the dust up</td>\n",
       "      <td>luke bryan</td>\n",
       "      <td>2015</td>\n",
       "      <td>all week long its a farmin town theyre makin ...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5087</th>\n",
       "      <td>88</td>\n",
       "      <td>blessings</td>\n",
       "      <td>big sean featuring drake</td>\n",
       "      <td>2015</td>\n",
       "      <td>look i feel blessed way up i feel blessed way...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5088</th>\n",
       "      <td>89</td>\n",
       "      <td>budapest</td>\n",
       "      <td>george ezra</td>\n",
       "      <td>2015</td>\n",
       "      <td>my house in budapest my hidden treasure chest...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5089</th>\n",
       "      <td>90</td>\n",
       "      <td>chandelier</td>\n",
       "      <td>sia</td>\n",
       "      <td>2015</td>\n",
       "      <td>party girls dont get hurt cant feel anything ...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5090</th>\n",
       "      <td>91</td>\n",
       "      <td>heartbeat song</td>\n",
       "      <td>kelly clarkson</td>\n",
       "      <td>2015</td>\n",
       "      <td>this is my heartbeat song and im gonna play i...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5091</th>\n",
       "      <td>92</td>\n",
       "      <td>dont</td>\n",
       "      <td>ed sheeran</td>\n",
       "      <td>2015</td>\n",
       "      <td>i met this girl late last year she said dont ...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5092</th>\n",
       "      <td>93</td>\n",
       "      <td>ghost</td>\n",
       "      <td>ella henderson</td>\n",
       "      <td>2015</td>\n",
       "      <td>i keep going to the river to pray cause i nee...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5093</th>\n",
       "      <td>94</td>\n",
       "      <td>here</td>\n",
       "      <td>alessia cara</td>\n",
       "      <td>2015</td>\n",
       "      <td>i guess right now youve got the last laughim ...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5094</th>\n",
       "      <td>95</td>\n",
       "      <td>waves</td>\n",
       "      <td>mr probz</td>\n",
       "      <td>2015</td>\n",
       "      <td>my face above the water my feet cant touch th...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5095</th>\n",
       "      <td>96</td>\n",
       "      <td>el perdon</td>\n",
       "      <td>nicky jam and enrique iglesias</td>\n",
       "      <td>2015</td>\n",
       "      <td>enrique iglesias dime si es verdad me dijeron ...</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5096</th>\n",
       "      <td>97</td>\n",
       "      <td>she knows</td>\n",
       "      <td>neyo featuring juicy j</td>\n",
       "      <td>2015</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5097</th>\n",
       "      <td>98</td>\n",
       "      <td>night changes</td>\n",
       "      <td>one direction</td>\n",
       "      <td>2015</td>\n",
       "      <td>going out tonight changes into something red ...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5098</th>\n",
       "      <td>99</td>\n",
       "      <td>back to back</td>\n",
       "      <td>drake</td>\n",
       "      <td>2015</td>\n",
       "      <td>oh man oh man oh man not againyeah i learned ...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5099</th>\n",
       "      <td>100</td>\n",
       "      <td>how deep is your love</td>\n",
       "      <td>calvin harris and disciples</td>\n",
       "      <td>2015</td>\n",
       "      <td>i want you to breathe me in let me be your ai...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5100 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Rank                                      Song  \\\n",
       "0        1                               wooly bully   \n",
       "1        2  i cant help myself sugar pie honey bunch   \n",
       "2        3                i cant get no satisfaction   \n",
       "3        4                       you were on my mind   \n",
       "4        5              youve lost that lovin feelin   \n",
       "5        6                                  downtown   \n",
       "6        7                                      help   \n",
       "7        8               cant you hear my heart beat   \n",
       "8        9                      crying in the chapel   \n",
       "9       10                                   my girl   \n",
       "10      11                            help me rhonda   \n",
       "11      12                          king of the road   \n",
       "12      13                    the birds and the bees   \n",
       "13      14                 hold me thrill me kiss me   \n",
       "14      15                                   shotgun   \n",
       "15      16                            i got you babe   \n",
       "16      17                         this diamond ring   \n",
       "17      18                              the in crowd   \n",
       "18      19     mrs brown youve got a lovely daughter   \n",
       "19      20                  stop in the name of love   \n",
       "20      21                          unchained melody   \n",
       "21      22                               silhouettes   \n",
       "22      23                ill never find another you   \n",
       "23      24                                  cara mia   \n",
       "24      25                         mr tambourine man   \n",
       "25      26                cast your fate to the wind   \n",
       "26      27                              yes im ready   \n",
       "27      28                        whats new pussycat   \n",
       "28      29                        eve of destruction   \n",
       "29      30                            hang on sloopy   \n",
       "...    ...                                       ...   \n",
       "5070    71                                   riptide   \n",
       "5071    72                               classic man   \n",
       "5072    73                                  exs  ohs   \n",
       "5073    74                       dear future husband   \n",
       "5074    75                               marvin gaye   \n",
       "5075    76                    like im gonna lose you   \n",
       "5076    77                          habits stay high   \n",
       "5077    78                          the hanging tree   \n",
       "5078    79                                      coco   \n",
       "5079    80                                 bang bang   \n",
       "5080    81                               lay me down   \n",
       "5081    82                                   tuesday   \n",
       "5082    83                              hit the quan   \n",
       "5083    84                                  downtown   \n",
       "5084    85                               house party   \n",
       "5085    86                                       ayo   \n",
       "5086    87                          kick the dust up   \n",
       "5087    88                                 blessings   \n",
       "5088    89                                  budapest   \n",
       "5089    90                                chandelier   \n",
       "5090    91                            heartbeat song   \n",
       "5091    92                                      dont   \n",
       "5092    93                                     ghost   \n",
       "5093    94                                      here   \n",
       "5094    95                                     waves   \n",
       "5095    96                                 el perdon   \n",
       "5096    97                                 she knows   \n",
       "5097    98                             night changes   \n",
       "5098    99                              back to back   \n",
       "5099   100                     how deep is your love   \n",
       "\n",
       "                                                 Artist  Year  \\\n",
       "0                         sam the sham and the pharaohs  1965   \n",
       "1                                             four tops  1965   \n",
       "2                                    the rolling stones  1965   \n",
       "3                                               we five  1965   \n",
       "4                                the righteous brothers  1965   \n",
       "5                                          petula clark  1965   \n",
       "6                                           the beatles  1965   \n",
       "7                                       hermans hermits  1965   \n",
       "8                                         elvis presley  1965   \n",
       "9                                       the temptations  1965   \n",
       "10                                       the beach boys  1965   \n",
       "11                                         roger miller  1965   \n",
       "12                                          jewel akens  1965   \n",
       "13                                           mel carter  1965   \n",
       "14                         junior walker  the all stars  1965   \n",
       "15                                          sonny  cher  1965   \n",
       "16                             gary lewis  the playboys  1965   \n",
       "17                                    ramsey lewis trio  1965   \n",
       "18                                      hermans hermits  1965   \n",
       "19                                         the supremes  1965   \n",
       "20                               the righteous brothers  1965   \n",
       "21                                      hermans hermits  1965   \n",
       "22                                          the seekers  1965   \n",
       "23                                jay and the americans  1965   \n",
       "24                                            the byrds  1965   \n",
       "25                                    sounds orchestral  1965   \n",
       "26                                        barbara mason  1965   \n",
       "27                                            tom jones  1965   \n",
       "28                                        barry mcguire  1965   \n",
       "29                                           the mccoys  1965   \n",
       "...                                                 ...   ...   \n",
       "5070                                          vance joy  2015   \n",
       "5071                 jidenna featuring roman gianarthur  2015   \n",
       "5072                                          elle king  2015   \n",
       "5073                                     meghan trainor  2015   \n",
       "5074              charlie puth featuring meghan trainor  2015   \n",
       "5075               meghan trainor featuring john legend  2015   \n",
       "5076                                            tove lo  2015   \n",
       "5077    james newton howard featuring jennifer lawrence  2015   \n",
       "5078                                         ot genasis  2015   \n",
       "5079             jessie j ariana grande and nicki minaj  2015   \n",
       "5080                                          sam smith  2015   \n",
       "5081                      ilovemakonnen featuring drake  2015   \n",
       "5082                                       ilovememphis  2015   \n",
       "5083  macklemore and ryan lewis featuring eric nally...  2015   \n",
       "5084                                           sam hunt  2015   \n",
       "5085                               chris brown and tyga  2015   \n",
       "5086                                         luke bryan  2015   \n",
       "5087                           big sean featuring drake  2015   \n",
       "5088                                        george ezra  2015   \n",
       "5089                                                sia  2015   \n",
       "5090                                     kelly clarkson  2015   \n",
       "5091                                         ed sheeran  2015   \n",
       "5092                                     ella henderson  2015   \n",
       "5093                                       alessia cara  2015   \n",
       "5094                                           mr probz  2015   \n",
       "5095                     nicky jam and enrique iglesias  2015   \n",
       "5096                             neyo featuring juicy j  2015   \n",
       "5097                                      one direction  2015   \n",
       "5098                                              drake  2015   \n",
       "5099                        calvin harris and disciples  2015   \n",
       "\n",
       "                                                 Lyrics  Source  Valence  \\\n",
       "0     sam the sham miscellaneous wooly bully wooly b...     3.0      NaN   \n",
       "1      sugar pie honey bunch you know that i love yo...     1.0      NaN   \n",
       "2                                                           1.0      NaN   \n",
       "3      when i woke up this morning you were on my mi...     1.0      NaN   \n",
       "4      you never close your eyes anymore when i kiss...     1.0      NaN   \n",
       "5      when youre alone and life is making you lonel...     1.0      NaN   \n",
       "6     help i need somebody help not just anybody hel...     3.0      NaN   \n",
       "7     carterlewis every time i see you lookin my way...     5.0      NaN   \n",
       "8      you saw me crying in the chapel the tears i s...     1.0      NaN   \n",
       "9     ive got sunshine on a cloudy day when its cold...     3.0      NaN   \n",
       "10    well since she put me down i ve been out doin ...     3.0      NaN   \n",
       "11     trailer for sale or rent rooms to let fifty c...     1.0      NaN   \n",
       "12    let me tell ya bout the birds and the bees and...     3.0      NaN   \n",
       "13     hold me hold me never let me go until youve t...     1.0      NaN   \n",
       "14    i said Ã¢shotgun shoot em for he runs now do t...     3.0      NaN   \n",
       "15    they say were young and we dont know we wont f...     3.0      NaN   \n",
       "16    who wants to buy this diamond ring she took it...     3.0      NaN   \n",
       "17                                         instrumental     3.0      NaN   \n",
       "18     mrs brown youve got a lovely daughter girls a...     1.0      NaN   \n",
       "19     stop in the name of love before you break my ...     1.0      NaN   \n",
       "20     oh my love my darling ive hungered for your t...     1.0      NaN   \n",
       "21     slaycrewetook a walk and passed your house la...     1.0      NaN   \n",
       "22     theres a new world somewhere they call the pr...     1.0      NaN   \n",
       "23    mantovani cara mia why must we say goodbye eac...     3.0      NaN   \n",
       "24     hey mr tambourine man play a song for me im n...     1.0      NaN   \n",
       "25    a month of nights a year of days octobers drif...     3.0      NaN   \n",
       "26    are you ready yes im ready are you ready yes i...     5.0      NaN   \n",
       "27     whats new pussycat woah woah whats new pussyc...     1.0      NaN   \n",
       "28     the eastern world it is explodin violence fla...     1.0      NaN   \n",
       "29    hang on sloopy sloopy hang on hang on sloopy s...     3.0      NaN   \n",
       "...                                                 ...     ...      ...   \n",
       "5070   i was scared of dentists and the dark i was s...     1.0      NaN   \n",
       "5071   my name calling all night i could pull the wo...     1.0      NaN   \n",
       "5072  verse 1 well i had me a boy turned him into a ...     5.0      NaN   \n",
       "5073   dear future husband heres a few things youll ...     1.0      NaN   \n",
       "5074   lets marvin gaye and get it on you got the he...     1.0      NaN   \n",
       "5075   i found myself dreaming in silver and gold li...     1.0      NaN   \n",
       "5076   uhuh uhuh uhuh i eat my dinner in my bathtub ...     1.0      NaN   \n",
       "5077   are you are you coming to the tree they strun...     1.0      NaN   \n",
       "5078   im in love with the coco coco coco im in love...     1.0      NaN   \n",
       "5079  verse 1 jessie j she got a body like an hourgl...     3.0      NaN   \n",
       "5080   yes i do i believe that one day i will be whe...     1.0      NaN   \n",
       "5081  hook x4 club goin up on a tuesday got your gir...     3.0      NaN   \n",
       "5082   yo yo aye im finna aye im finnaim finna show ...     1.0      NaN   \n",
       "5083   i went to the moped store said fuck it salesm...     1.0      NaN   \n",
       "5084   youre on the couch blowing up my phone you do...     1.0      NaN   \n",
       "5085   i need you i need you i need you i need you i...     1.0      NaN   \n",
       "5086   all week long its a farmin town theyre makin ...     1.0      NaN   \n",
       "5087   look i feel blessed way up i feel blessed way...     1.0      NaN   \n",
       "5088   my house in budapest my hidden treasure chest...     1.0      NaN   \n",
       "5089   party girls dont get hurt cant feel anything ...     1.0      NaN   \n",
       "5090   this is my heartbeat song and im gonna play i...     1.0      NaN   \n",
       "5091   i met this girl late last year she said dont ...     1.0      NaN   \n",
       "5092   i keep going to the river to pray cause i nee...     1.0      NaN   \n",
       "5093   i guess right now youve got the last laughim ...     1.0      NaN   \n",
       "5094   my face above the water my feet cant touch th...     1.0      NaN   \n",
       "5095  enrique iglesias dime si es verdad me dijeron ...     3.0      NaN   \n",
       "5096                                                NaN     NaN      NaN   \n",
       "5097   going out tonight changes into something red ...     1.0      NaN   \n",
       "5098   oh man oh man oh man not againyeah i learned ...     1.0      NaN   \n",
       "5099   i want you to breathe me in let me be your ai...     1.0      NaN   \n",
       "\n",
       "      Duration_ms  \n",
       "0             NaN  \n",
       "1             NaN  \n",
       "2             NaN  \n",
       "3             NaN  \n",
       "4             NaN  \n",
       "5             NaN  \n",
       "6             NaN  \n",
       "7             NaN  \n",
       "8             NaN  \n",
       "9             NaN  \n",
       "10            NaN  \n",
       "11            NaN  \n",
       "12            NaN  \n",
       "13            NaN  \n",
       "14            NaN  \n",
       "15            NaN  \n",
       "16            NaN  \n",
       "17            NaN  \n",
       "18            NaN  \n",
       "19            NaN  \n",
       "20            NaN  \n",
       "21            NaN  \n",
       "22            NaN  \n",
       "23            NaN  \n",
       "24            NaN  \n",
       "25            NaN  \n",
       "26            NaN  \n",
       "27            NaN  \n",
       "28            NaN  \n",
       "29            NaN  \n",
       "...           ...  \n",
       "5070          NaN  \n",
       "5071          NaN  \n",
       "5072          NaN  \n",
       "5073          NaN  \n",
       "5074          NaN  \n",
       "5075          NaN  \n",
       "5076          NaN  \n",
       "5077          NaN  \n",
       "5078          NaN  \n",
       "5079          NaN  \n",
       "5080          NaN  \n",
       "5081          NaN  \n",
       "5082          NaN  \n",
       "5083          NaN  \n",
       "5084          NaN  \n",
       "5085          NaN  \n",
       "5086          NaN  \n",
       "5087          NaN  \n",
       "5088          NaN  \n",
       "5089          NaN  \n",
       "5090          NaN  \n",
       "5091          NaN  \n",
       "5092          NaN  \n",
       "5093          NaN  \n",
       "5094          NaN  \n",
       "5095          NaN  \n",
       "5096          NaN  \n",
       "5097          NaN  \n",
       "5098          NaN  \n",
       "5099          NaN  \n",
       "\n",
       "[5100 rows x 8 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv(\"data/billboard_with_data.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
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   "name": "SUSA Music Moods.ipynb",
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