final_project_data_cleaning.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Cleaning the data:*\n",
    "\n",
    "Here we work with 2 data sources:\n",
    "1. 1 Million Playlist Dataset\n",
    "2. Spotify API (must be accessed with credentials; not posted here)\n",
    "\n",
    "We downloaded and saved the 1,000,000 playlists as 1000 files in the folder 'Songs'\n",
    "\n",
    "How we cleaned the data has been explained as we do it in the notebook.\n",
    "\n",
    "The final dataset we work with contains playlist data taken from data source (1) and then song features for each song in those playlists from data source (2). We the data we prepared as csv for easy downloading.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import json\n",
    "\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.utils import resample\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.ensemble import AdaBoostClassifier\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics.pairwise import cosine_similarity \n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "import seaborn as sns\n",
    "sns.set(style='whitegrid')\n",
    "pd.set_option('display.width', 1500)\n",
    "pd.set_option('display.max_columns', 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# The 1 million playlist data lives in 1000 separate files\n",
    "# That amount of data will take a lot of time to work with\n",
    "# Thus we randomly subset 10 files to work with 10000 playlists\n",
    "\n",
    "np.random.seed(seed = 19)\n",
    "numbers = np.arange(0,1000,1)\n",
    "sample = np.random.choice(numbers, size=10, replace=True)\n",
    "sample_pathname = ['Songs/songs'] * 10 \n",
    "for number in range(10):\n",
    "    string = 'Songs/songs' + str(sample[number]) + '.csv'\n",
    "    sample_pathname[number] = string\n",
    "\n",
    "print(\"Playlist files we will use by random selection:\")\n",
    "print(\"10 files should give us 10,000 playlists\")\n",
    "sample_pathname\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Saving those 10 playlist file path in a list\n",
    "# They are saved in a folder named Songs\n",
    "# There are 1000 files with 1000 playlists in each\n",
    "playlist_list = []\n",
    "for path in sample_pathname:\n",
    "    df = pd.read_csv(path)\n",
    "    playlist_list.append(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We want to get a dataframe with 10,000 playlists\n",
    "# Making sure the 10,000 playlists have a different  or playlist id\n",
    "for i in range(10):\n",
    "    playlist_list[i]['pid'] = playlist_list[i]['pid'] + 1000*i\n",
    "    \n",
    "# Combining the 10,000 playlist into a single df\n",
    "df = playlist_list[0]\n",
    "for i in range(1,10):\n",
    "    df = df.append(playlist_list[i], ignore_index=True)\n",
    "df.tail(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Saving as csv file\n",
    "df.to_csv(\"data/Sample_from_Million_Playlist.csv\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Getting data from Spotify api\n",
    "import spotipy\n",
    "from spotipy.oauth2 import SpotifyClientCredentials\n",
    "\n",
    "client_credentials_manager = SpotifyClientCredentials('', '', None)\n",
    "sp = spotipy.Spotify(client_credentials_manager=client_credentials_manager)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We have 10,000 playlists\n",
    "\n",
    "# It's hard time consuming to bring data from spotify for over 663,000 songs\n",
    "# I tried 1000 playlists and spotify didn't allow me to get that much data\n",
    "# Let's choose a small subset, 100 playlists in random and bring spotify data for those songs\n",
    "\n",
    "np.random.seed(seed = 10)\n",
    "numbers2 = np.arange(0,10000,1)\n",
    "sample2 = np.random.choice(numbers, size=200, replace=True)\n",
    "small_df = df[df['pid'].isin(sample2)]\n",
    "\n",
    "# Removing 28 songs such that we can send larger requests (100 requests at a time) to spotify \n",
    "small_df = small_df.iloc[:12100,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Got track info on 12,100 songs\n",
    "track_info = []\n",
    "mah_tracks_uri = list(small_df['track_uri'])\n",
    "counts = list(np.arange(0,12100,100))\n",
    "for count in counts:\n",
    "    \n",
    "    # This is the part we get data from Spotify\n",
    "    # Usually takes a long time to implement\n",
    "    for x in mah_tracks_uri[count:count+100]:\n",
    "        song = sp.audio_features(tracks= x)[0]\n",
    "        track_info.append(song)\n",
    "        \n",
    "# We have a dataframe with info on each track\n",
    "track_info_df = pd.DataFrame(track_info)\n",
    "track_info_df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Merging the two dataframes\n",
    "df_spotify = pd.concat([small_df.reset_index(), track_info_df], axis=1)\n",
    "df_spotify.head(10)\n",
    "\n",
    "# Saving as csv file\n",
    "# This file below will be used in our analysis files\n",
    "df_spotify.to_csv(\"data/100_Sample_MilPlay_Spotify.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
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       "      <th>artist_name</th>\n",
       "      <th>track_uri</th>\n",
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       "      <th>energy</th>\n",
       "      <th>key</th>\n",
       "      <th>loudness</th>\n",
       "      <th>mode</th>\n",
       "      <th>speechiness</th>\n",
       "      <th>acousticness</th>\n",
       "      <th>instrumentalness</th>\n",
       "      <th>liveness</th>\n",
       "      <th>valence</th>\n",
       "      <th>tempo</th>\n",
       "      <th>type</th>\n",
       "      <th>id</th>\n",
       "      <th>uri</th>\n",
       "      <th>track_href</th>\n",
       "      <th>analysis_url</th>\n",
       "      <th>duration_ms.1</th>\n",
       "      <th>time_signature</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <td>Alessia Cara</td>\n",
       "      <td>spotify:track:1wYZZtamWTQAoj8B812uKQ</td>\n",
       "      <td>spotify:artist:2wUjUUtkb5lvLKcGKsKqsR</td>\n",
       "      <td>Here</td>\n",
       "      <td>spotify:album:3rDbA12I5duZnlwakqDdZa</td>\n",
       "      <td>199453</td>\n",
       "      <td>Know-It-All</td>\n",
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       "      <td>0</td>\n",
       "      <td>-3.974</td>\n",
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       "      <td>audio_features</td>\n",
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       "      <td>spotify:track:1wYZZtamWTQAoj8B812uKQ</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/1wYZZtamWTQA...</td>\n",
       "      <td>https://api.spotify.com/v1/audio-analysis/1wYZ...</td>\n",
       "      <td>199453</td>\n",
       "      <td>4</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>The Weeknd</td>\n",
       "      <td>spotify:track:0Gi17qCJh9e9RJxLaYkm9l</td>\n",
       "      <td>spotify:artist:1Xyo4u8uXC1ZmMpatF05PJ</td>\n",
       "      <td>Dark Times</td>\n",
       "      <td>spotify:album:28ZKQMoNBB0etKXZ97G2SN</td>\n",
       "      <td>260640</td>\n",
       "      <td>Beauty Behind The Madness</td>\n",
       "      <td>0.585</td>\n",
       "      <td>0.421</td>\n",
       "      <td>7</td>\n",
       "      <td>-9.593</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0707</td>\n",
       "      <td>0.1060</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.240</td>\n",
       "      <td>132.986</td>\n",
       "      <td>audio_features</td>\n",
       "      <td>0Gi17qCJh9e9RJxLaYkm9l</td>\n",
       "      <td>spotify:track:0Gi17qCJh9e9RJxLaYkm9l</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/0Gi17qCJh9e9...</td>\n",
       "      <td>https://api.spotify.com/v1/audio-analysis/0Gi1...</td>\n",
       "      <td>260640</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>J. Cole</td>\n",
       "      <td>spotify:track:6Ius4TC0L3cN74HT7ENE6e</td>\n",
       "      <td>spotify:artist:6l3HvQ5sa6mXTsMTB19rO5</td>\n",
       "      <td>Wet Dreamz</td>\n",
       "      <td>spotify:album:7viNUmZZ8ztn2UB4XB3jIL</td>\n",
       "      <td>239320</td>\n",
       "      <td>2014 Forest Hills Drive</td>\n",
       "      <td>0.504</td>\n",
       "      <td>0.705</td>\n",
       "      <td>6</td>\n",
       "      <td>-8.205</td>\n",
       "      <td>0</td>\n",
       "      <td>0.3640</td>\n",
       "      <td>0.0752</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.1280</td>\n",
       "      <td>0.584</td>\n",
       "      <td>175.483</td>\n",
       "      <td>audio_features</td>\n",
       "      <td>6Ius4TC0L3cN74HT7ENE6e</td>\n",
       "      <td>spotify:track:6Ius4TC0L3cN74HT7ENE6e</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/6Ius4TC0L3cN...</td>\n",
       "      <td>https://api.spotify.com/v1/audio-analysis/6Ius...</td>\n",
       "      <td>239320</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>Chance The Rapper</td>\n",
       "      <td>spotify:track:0jx8zY5JQsS4YEQcfkoc5C</td>\n",
       "      <td>spotify:artist:1anyVhU62p31KFi8MEzkbf</td>\n",
       "      <td>Angels (feat. Saba)</td>\n",
       "      <td>spotify:album:71QyofYesSsRMwFOTafnhB</td>\n",
       "      <td>206240</td>\n",
       "      <td>Coloring Book</td>\n",
       "      <td>0.771</td>\n",
       "      <td>0.647</td>\n",
       "      <td>5</td>\n",
       "      <td>-5.127</td>\n",
       "      <td>0</td>\n",
       "      <td>0.3760</td>\n",
       "      <td>0.2940</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.3700</td>\n",
       "      <td>0.678</td>\n",
       "      <td>155.914</td>\n",
       "      <td>audio_features</td>\n",
       "      <td>0jx8zY5JQsS4YEQcfkoc5C</td>\n",
       "      <td>spotify:track:0jx8zY5JQsS4YEQcfkoc5C</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/0jx8zY5JQsS4...</td>\n",
       "      <td>https://api.spotify.com/v1/audio-analysis/0jx8...</td>\n",
       "      <td>206240</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>The Weeknd</td>\n",
       "      <td>spotify:track:7fPHfBCyKE3aVCBjE4DAvl</td>\n",
       "      <td>spotify:artist:1Xyo4u8uXC1ZmMpatF05PJ</td>\n",
       "      <td>In The Night</td>\n",
       "      <td>spotify:album:28ZKQMoNBB0etKXZ97G2SN</td>\n",
       "      <td>235653</td>\n",
       "      <td>Beauty Behind The Madness</td>\n",
       "      <td>0.480</td>\n",
       "      <td>0.682</td>\n",
       "      <td>7</td>\n",
       "      <td>-4.940</td>\n",
       "      <td>1</td>\n",
       "      <td>0.1300</td>\n",
       "      <td>0.0696</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0463</td>\n",
       "      <td>0.506</td>\n",
       "      <td>167.939</td>\n",
       "      <td>audio_features</td>\n",
       "      <td>7fPHfBCyKE3aVCBjE4DAvl</td>\n",
       "      <td>spotify:track:7fPHfBCyKE3aVCBjE4DAvl</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/7fPHfBCyKE3a...</td>\n",
       "      <td>https://api.spotify.com/v1/audio-analysis/7fPH...</td>\n",
       "      <td>235653</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>Donnie Trumpet &amp; The Social Experiment</td>\n",
       "      <td>spotify:track:6fTdcGsjxlAD9PSkoPaLMX</td>\n",
       "      <td>spotify:artist:0ojcq9LJQWMawQdFDw3M0L</td>\n",
       "      <td>Sunday Candy</td>\n",
       "      <td>spotify:album:3eM1KTKmpqrQOvuvYY42cr</td>\n",
       "      <td>226013</td>\n",
       "      <td>Surf</td>\n",
       "      <td>0.511</td>\n",
       "      <td>0.596</td>\n",
       "      <td>0</td>\n",
       "      <td>-6.560</td>\n",
       "      <td>1</td>\n",
       "      <td>0.2240</td>\n",
       "      <td>0.5300</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0798</td>\n",
       "      <td>0.554</td>\n",
       "      <td>158.063</td>\n",
       "      <td>audio_features</td>\n",
       "      <td>6fTdcGsjxlAD9PSkoPaLMX</td>\n",
       "      <td>spotify:track:6fTdcGsjxlAD9PSkoPaLMX</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/6fTdcGsjxlAD...</td>\n",
       "      <td>https://api.spotify.com/v1/audio-analysis/6fTd...</td>\n",
       "      <td>226014</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>Beyoncé</td>\n",
       "      <td>spotify:track:2CvOqDpQIMw69cCzWqr5yr</td>\n",
       "      <td>spotify:artist:6vWDO969PvNqNYHIOW5v0m</td>\n",
       "      <td>Halo</td>\n",
       "      <td>spotify:album:3ROfBX6lJLnCmaw1NrP5K9</td>\n",
       "      <td>261160</td>\n",
       "      <td>I AM...SASHA FIERCE - Platinum Edition</td>\n",
       "      <td>0.422</td>\n",
       "      <td>0.712</td>\n",
       "      <td>11</td>\n",
       "      <td>-5.907</td>\n",
       "      <td>0</td>\n",
       "      <td>0.1000</td>\n",
       "      <td>0.2730</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0510</td>\n",
       "      <td>0.471</td>\n",
       "      <td>78.454</td>\n",
       "      <td>audio_features</td>\n",
       "      <td>2CvOqDpQIMw69cCzWqr5yr</td>\n",
       "      <td>spotify:track:2CvOqDpQIMw69cCzWqr5yr</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/2CvOqDpQIMw6...</td>\n",
       "      <td>https://api.spotify.com/v1/audio-analysis/2CvO...</td>\n",
       "      <td>261160</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>4</td>\n",
       "      <td>7</td>\n",
       "      <td>Hozier</td>\n",
       "      <td>spotify:track:1ivHxaGL5ld9VS1zsYc4YN</td>\n",
       "      <td>spotify:artist:2FXC3k01G6Gw61bmprjgqS</td>\n",
       "      <td>Cherry Wine - Live</td>\n",
       "      <td>spotify:album:36k5aXpxffjVGcNce12GLZ</td>\n",
       "      <td>240147</td>\n",
       "      <td>Hozier</td>\n",
       "      <td>0.418</td>\n",
       "      <td>0.111</td>\n",
       "      <td>1</td>\n",
       "      <td>-14.848</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0389</td>\n",
       "      <td>0.9530</td>\n",
       "      <td>0.003420</td>\n",
       "      <td>0.0982</td>\n",
       "      <td>0.228</td>\n",
       "      <td>82.508</td>\n",
       "      <td>audio_features</td>\n",
       "      <td>1ivHxaGL5ld9VS1zsYc4YN</td>\n",
       "      <td>spotify:track:1ivHxaGL5ld9VS1zsYc4YN</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/1ivHxaGL5ld9...</td>\n",
       "      <td>https://api.spotify.com/v1/audio-analysis/1ivH...</td>\n",
       "      <td>240147</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>Hozier</td>\n",
       "      <td>spotify:track:1TGimSbipZ3XZ7q3eszBRV</td>\n",
       "      <td>spotify:artist:2FXC3k01G6Gw61bmprjgqS</td>\n",
       "      <td>Angel Of Small Death &amp; The Codeine Scene</td>\n",
       "      <td>spotify:album:36k5aXpxffjVGcNce12GLZ</td>\n",
       "      <td>219214</td>\n",
       "      <td>Hozier</td>\n",
       "      <td>0.377</td>\n",
       "      <td>0.638</td>\n",
       "      <td>4</td>\n",
       "      <td>-5.754</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0545</td>\n",
       "      <td>0.2130</td>\n",
       "      <td>0.000080</td>\n",
       "      <td>0.1200</td>\n",
       "      <td>0.369</td>\n",
       "      <td>92.644</td>\n",
       "      <td>audio_features</td>\n",
       "      <td>1TGimSbipZ3XZ7q3eszBRV</td>\n",
       "      <td>spotify:track:1TGimSbipZ3XZ7q3eszBRV</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/1TGimSbipZ3X...</td>\n",
       "      <td>https://api.spotify.com/v1/audio-analysis/1TGi...</td>\n",
       "      <td>219214</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>4</td>\n",
       "      <td>9</td>\n",
       "      <td>Hozier</td>\n",
       "      <td>spotify:track:2Tjlq3aGhg3dIZFvSfsnyc</td>\n",
       "      <td>spotify:artist:2FXC3k01G6Gw61bmprjgqS</td>\n",
       "      <td>From Eden</td>\n",
       "      <td>spotify:album:36k5aXpxffjVGcNce12GLZ</td>\n",
       "      <td>283466</td>\n",
       "      <td>Hozier</td>\n",
       "      <td>0.395</td>\n",
       "      <td>0.676</td>\n",
       "      <td>0</td>\n",
       "      <td>-5.460</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0498</td>\n",
       "      <td>0.6080</td>\n",
       "      <td>0.000049</td>\n",
       "      <td>0.1170</td>\n",
       "      <td>0.315</td>\n",
       "      <td>142.929</td>\n",
       "      <td>audio_features</td>\n",
       "      <td>2Tjlq3aGhg3dIZFvSfsnyc</td>\n",
       "      <td>spotify:track:2Tjlq3aGhg3dIZFvSfsnyc</td>\n",
       "      <td>https://api.spotify.com/v1/tracks/2Tjlq3aGhg3d...</td>\n",
       "      <td>https://api.spotify.com/v1/audio-analysis/2Tjl...</td>\n",
       "      <td>283467</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   pid  pos                             artist_name                             track_uri                             artist_uri                                track_name                             album_uri  duration_ms                              album_name  danceability  energy  key  loudness  mode  speechiness  acousticness  instrumentalness  liveness  valence    tempo            type                      id                                   uri                                         track_href                                       analysis_url  duration_ms.1  time_signature\n",
       "0    4    0                            Alessia Cara  spotify:track:1wYZZtamWTQAoj8B812uKQ  spotify:artist:2wUjUUtkb5lvLKcGKsKqsR                                      Here  spotify:album:3rDbA12I5duZnlwakqDdZa       199453                             Know-It-All         0.376   0.821    0    -3.974     1       0.1040        0.0785          0.000000    0.0823    0.331  120.462  audio_features  1wYZZtamWTQAoj8B812uKQ  spotify:track:1wYZZtamWTQAoj8B812uKQ  https://api.spotify.com/v1/tracks/1wYZZtamWTQA...  https://api.spotify.com/v1/audio-analysis/1wYZ...         199453               4\n",
       "1    4    1                              The Weeknd  spotify:track:0Gi17qCJh9e9RJxLaYkm9l  spotify:artist:1Xyo4u8uXC1ZmMpatF05PJ                                Dark Times  spotify:album:28ZKQMoNBB0etKXZ97G2SN       260640               Beauty Behind The Madness         0.585   0.421    7    -9.593     1       0.0707        0.1060          0.000010    0.1400    0.240  132.986  audio_features  0Gi17qCJh9e9RJxLaYkm9l  spotify:track:0Gi17qCJh9e9RJxLaYkm9l  https://api.spotify.com/v1/tracks/0Gi17qCJh9e9...  https://api.spotify.com/v1/audio-analysis/0Gi1...         260640               3\n",
       "2    4    2                                 J. Cole  spotify:track:6Ius4TC0L3cN74HT7ENE6e  spotify:artist:6l3HvQ5sa6mXTsMTB19rO5                                Wet Dreamz  spotify:album:7viNUmZZ8ztn2UB4XB3jIL       239320                 2014 Forest Hills Drive         0.504   0.705    6    -8.205     0       0.3640        0.0752          0.000000    0.1280    0.584  175.483  audio_features  6Ius4TC0L3cN74HT7ENE6e  spotify:track:6Ius4TC0L3cN74HT7ENE6e  https://api.spotify.com/v1/tracks/6Ius4TC0L3cN...  https://api.spotify.com/v1/audio-analysis/6Ius...         239320               4\n",
       "3    4    3                       Chance The Rapper  spotify:track:0jx8zY5JQsS4YEQcfkoc5C  spotify:artist:1anyVhU62p31KFi8MEzkbf                       Angels (feat. Saba)  spotify:album:71QyofYesSsRMwFOTafnhB       206240                           Coloring Book         0.771   0.647    5    -5.127     0       0.3760        0.2940          0.000000    0.3700    0.678  155.914  audio_features  0jx8zY5JQsS4YEQcfkoc5C  spotify:track:0jx8zY5JQsS4YEQcfkoc5C  https://api.spotify.com/v1/tracks/0jx8zY5JQsS4...  https://api.spotify.com/v1/audio-analysis/0jx8...         206240               4\n",
       "4    4    4                              The Weeknd  spotify:track:7fPHfBCyKE3aVCBjE4DAvl  spotify:artist:1Xyo4u8uXC1ZmMpatF05PJ                              In The Night  spotify:album:28ZKQMoNBB0etKXZ97G2SN       235653               Beauty Behind The Madness         0.480   0.682    7    -4.940     1       0.1300        0.0696          0.000000    0.0463    0.506  167.939  audio_features  7fPHfBCyKE3aVCBjE4DAvl  spotify:track:7fPHfBCyKE3aVCBjE4DAvl  https://api.spotify.com/v1/tracks/7fPHfBCyKE3a...  https://api.spotify.com/v1/audio-analysis/7fPH...         235653               3\n",
       "5    4    5  Donnie Trumpet & The Social Experiment  spotify:track:6fTdcGsjxlAD9PSkoPaLMX  spotify:artist:0ojcq9LJQWMawQdFDw3M0L                              Sunday Candy  spotify:album:3eM1KTKmpqrQOvuvYY42cr       226013                                    Surf         0.511   0.596    0    -6.560     1       0.2240        0.5300          0.000000    0.0798    0.554  158.063  audio_features  6fTdcGsjxlAD9PSkoPaLMX  spotify:track:6fTdcGsjxlAD9PSkoPaLMX  https://api.spotify.com/v1/tracks/6fTdcGsjxlAD...  https://api.spotify.com/v1/audio-analysis/6fTd...         226014               4\n",
       "6    4    6                                 Beyoncé  spotify:track:2CvOqDpQIMw69cCzWqr5yr  spotify:artist:6vWDO969PvNqNYHIOW5v0m                                      Halo  spotify:album:3ROfBX6lJLnCmaw1NrP5K9       261160  I AM...SASHA FIERCE - Platinum Edition         0.422   0.712   11    -5.907     0       0.1000        0.2730          0.000000    0.0510    0.471   78.454  audio_features  2CvOqDpQIMw69cCzWqr5yr  spotify:track:2CvOqDpQIMw69cCzWqr5yr  https://api.spotify.com/v1/tracks/2CvOqDpQIMw6...  https://api.spotify.com/v1/audio-analysis/2CvO...         261160               4\n",
       "7    4    7                                  Hozier  spotify:track:1ivHxaGL5ld9VS1zsYc4YN  spotify:artist:2FXC3k01G6Gw61bmprjgqS                        Cherry Wine - Live  spotify:album:36k5aXpxffjVGcNce12GLZ       240147                                  Hozier         0.418   0.111    1   -14.848     1       0.0389        0.9530          0.003420    0.0982    0.228   82.508  audio_features  1ivHxaGL5ld9VS1zsYc4YN  spotify:track:1ivHxaGL5ld9VS1zsYc4YN  https://api.spotify.com/v1/tracks/1ivHxaGL5ld9...  https://api.spotify.com/v1/audio-analysis/1ivH...         240147               4\n",
       "8    4    8                                  Hozier  spotify:track:1TGimSbipZ3XZ7q3eszBRV  spotify:artist:2FXC3k01G6Gw61bmprjgqS  Angel Of Small Death & The Codeine Scene  spotify:album:36k5aXpxffjVGcNce12GLZ       219214                                  Hozier         0.377   0.638    4    -5.754     1       0.0545        0.2130          0.000080    0.1200    0.369   92.644  audio_features  1TGimSbipZ3XZ7q3eszBRV  spotify:track:1TGimSbipZ3XZ7q3eszBRV  https://api.spotify.com/v1/tracks/1TGimSbipZ3X...  https://api.spotify.com/v1/audio-analysis/1TGi...         219214               4\n",
       "9    4    9                                  Hozier  spotify:track:2Tjlq3aGhg3dIZFvSfsnyc  spotify:artist:2FXC3k01G6Gw61bmprjgqS                                 From Eden  spotify:album:36k5aXpxffjVGcNce12GLZ       283466                                  Hozier         0.395   0.676    0    -5.460     1       0.0498        0.6080          0.000049    0.1170    0.315  142.929  audio_features  2Tjlq3aGhg3dIZFvSfsnyc  spotify:track:2Tjlq3aGhg3dIZFvSfsnyc  https://api.spotify.com/v1/tracks/2Tjlq3aGhg3d...  https://api.spotify.com/v1/audio-analysis/2Tjl...         283467               5"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Reading the dataframe to start working\n",
    "df = pd.read_csv(\"data/Sample_from_Million_Playlist.csv\")\n",
    "# Reading the data from saved file\n",
    "# This is the dataframe we will implement our mode\n",
    "df_spotify = pd.read_csv(\"data/100_Sample_MilPlay_Spotify.csv\")\n",
    "df_spotify.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Note:**\n",
    "Before we use this data for all our analysis, it is crucial to see that the data is indeed random and that our selected playlists display strong variety"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(df_spotify['pid'].value_counts())\n",
    "plt.title(\"Distribution of number of songs in our 100 Playlists\")\n",
    "plt.ylabel(\"Count\")\n",
    "plt.ylabel(\"Number of songs in a playlist\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(df_spotify['artist_name'].value_counts())\n",
    "plt.title(\"No artists dominate our 100 Playlists\")\n",
    "plt.ylabel(\"Count\")\n",
    "plt.xlabel(\"Number of songs an artist has\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Total songs across playlists')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Checking which artists are featured most across all playlists\n",
    "values = list(df_spotify['artist_name'].value_counts())\n",
    "names = df_spotify['artist_name'].value_counts().index.tolist()\n",
    "\n",
    "ax = sns.barplot(y=names[0:10], x=values[0:10])\n",
    "ax.set_title('Artists with most featured songs across all playlists')\n",
    "ax.set_xlabel('Total songs across playlists')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(df_spotify['danceability'])\n",
    "plt.title(\"Danceability seems well distributed in our 100 Playlists\")\n",
    "plt.ylabel(\"Songs Count\")\n",
    "plt.xlabel(\"Danceability\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(df_spotify['energy'])\n",
    "plt.title(\"Energy seems well distributed in our 100 Playlists\")\n",
    "plt.ylabel(\"Songs Count\")\n",
    "plt.xlabel(\"Energy\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(df_spotify['valence'])\n",
    "plt.title(\"Valence seems well distributed in our 100 Playlists\")\n",
    "plt.ylabel(\"Songs Count\")\n",
    "plt.xlabel(\"Valence\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(df_spotify['duration_ms']/1000)\n",
    "plt.title(\"Duration seems well distributed in our 100 Playlists\")\n",
    "plt.ylabel(\"Songs Count\")\n",
    "plt.xlabel(\"Duration (sec)\")\n",
    "plt.xlim(60,500)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}