spot_to_df.ipynb

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    "import pandas as pd\n",
    "import spotipy\n",
    "from spotipy.oauth2 import SpotifyClientCredentials\n",
    "\n",
    "# Initialize client\n",
    "sp = spotipy.Spotify(auth_manager=SpotifyClientCredentials(client_id='your ID ',\n",
    "                                                           client_secret='your Secret'))\n",
    "\n",
    "def get_album_release_dates(album_ids):\n",
    "    album_details = {}\n",
    "    for album_id in album_ids:\n",
    "        album = sp.album(album_id)\n",
    "        album_details[album_id] = album['release_date']\n",
    "    return album_details\n",
    "\n",
    "def get_audio_features_in_batches(track_ids, batch_size=100):\n",
    "    audio_features = []\n",
    "    for i in range(0, len(track_ids), batch_size):\n",
    "        batch_ids = track_ids[i:i + batch_size]\n",
    "        features = sp.audio_features(batch_ids)\n",
    "        audio_features.extend(features)\n",
    "    return audio_features\n",
    "\n",
    "def get_artist_id(artist_name):\n",
    "    results = sp.search(q=f'artist:{artist_name}', type='artist', limit=1)\n",
    "    artist = results['artists']['items'][0]\n",
    "    return artist['id']\n",
    "\n",
    "def fetch_all_tracks(artist_name):\n",
    "    artist_id = get_artist_id(artist_name)\n",
    "    all_tracks = []\n",
    "    results = sp.artist_albums(artist_id, album_type='album', limit=50)\n",
    "    albums = results['items']\n",
    "    \n",
    "    while results['next']:\n",
    "        results = sp.next(results)\n",
    "        albums.extend(results['items'])\n",
    "    \n",
    "    for album in albums:\n",
    "        album_id = album['id']\n",
    "        tracks = sp.album_tracks(album_id, limit=50)\n",
    "        for track in tracks['items']:\n",
    "            # Fetch track details including popularity\n",
    "            track_details = sp.track(track['id'])\n",
    "            all_tracks.append({\n",
    "                'track_id': track['id'],\n",
    "                'track_name': track['name'],\n",
    "                'album_id': album_id,\n",
    "                'album_name': album['name'],\n",
    "                'popularity': track_details['popularity'], \n",
    "                'track_duration_ms': track_details['duration_ms']  \n",
    "            })\n",
    "    \n",
    "    return all_tracks\n",
    "\n",
    "def create_tracks_dataframe(tracks):\n",
    "    # Extract track IDs and album IDs\n",
    "    track_ids = [track['track_id'] for track in tracks]\n",
    "    album_ids = list(set(track['album_id'] for track in tracks))  \n",
    "\n",
    "    # Get album release dates\n",
    "    album_release_dates = get_album_release_dates(album_ids)\n",
    "    \n",
    "    # Get audio features\n",
    "    audio_features = get_audio_features_in_batches(track_ids)\n",
    "    \n",
    "    # Create a dictionary to map track IDs to audio features\n",
    "    track_features_map = {feature['id']: feature for feature in audio_features if feature}\n",
    "\n",
    "    # Prepare data for DataFrame\n",
    "    data = []\n",
    "    for track in tracks:\n",
    "        track_id = track['track_id']\n",
    "        album_id = track['album_id']\n",
    "        features = track_features_map.get(track_id, {})\n",
    "        \n",
    "        # Get all possible features\n",
    "        tempo = features.get('tempo', 'No data')\n",
    "        duration_ms = features.get('duration_ms', track.get('track_duration_ms', 'No data'))\n",
    "        duration_s = duration_ms / 1000 if isinstance(duration_ms, (int, float)) else 'N/A'\n",
    "        danceability = features.get('danceability', 'No data')\n",
    "        energy = features.get('energy', 'No data')\n",
    "        key = features.get('key', 'No data')\n",
    "        loudness = features.get('loudness', 'No data')\n",
    "        mode = features.get('mode', 'No data')\n",
    "        speechiness = features.get('speechiness', 'No data')\n",
    "        acousticness = features.get('acousticness', 'No data')\n",
    "        instrumentalness = features.get('instrumentalness', 'No data')\n",
    "        liveness = features.get('liveness', 'No data')\n",
    "        valence = features.get('valence', 'No data')\n",
    "        popularity = track.get('popularity', 'No data')  # Add track popularity\n",
    "        \n",
    "        # Deal with missing data\n",
    "        if isinstance(duration_s, str):\n",
    "            duration_s = 'N/A'\n",
    "        \n",
    "        data.append({\n",
    "            'Track Name': track.get('track_name', 'No data'),\n",
    "            'Album Name': track.get('album_name', 'No data'),\n",
    "            'Track ID': track_id,\n",
    "            'Popularity': popularity,\n",
    "            'Tempo (BPM)': tempo,\n",
    "            'Duration (s)': duration_s,\n",
    "            'Danceability': danceability,\n",
    "            'Energy': energy,\n",
    "            'Key': key,\n",
    "            'Loudness': loudness,\n",
    "            'Mode': mode,\n",
    "            'Speechiness': speechiness,\n",
    "            'Acousticness': acousticness,\n",
    "            'Instrumentalness': instrumentalness,\n",
    "            'Liveness': liveness,\n",
    "            'Valence': valence,\n",
    "            'Release Date': album_release_dates.get(album_id, 'No release date available')\n",
    "        })\n",
    "    \n",
    "    # Create DataFrame\n",
    "    df = pd.DataFrame(data)\n",
    "    return df\n",
    "\n",
    "# Get all tracks and create DataFrame\n",
    "artist_id = 'Aphex Twin'\n",
    "all_tracks = fetch_all_tracks(artist_id)\n",
    "df = create_tracks_dataframe(all_tracks)\n",
    "\n",
    "df.head()  "
   ]
  }
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