{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "e519803e-2949-4584-857b-7e0d0995d1a6",
   "metadata": {},
   "source": [
    "### Finding similar artists using content-based approach\n",
    "This notebook contains experiments with different approaches.<br>\n",
    "To view the latest version of similarity work, view notebook <b>\"Similar Orchard artists algos\"</b>."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03aadbd2-6d4f-4808-816d-dee7783205b1",
   "metadata": {},
   "source": [
    "* <a id='just_genre'>Calculate similarity using Spotify artist genres from Chartmetric</a>\n",
    "* <a id='just_description'> Calculate similarity using Spotify artist descriptions from Chartmetric</a>\n",
    "* <a id='genre_description'>Calculate similarity using  Spotify artist genre and descriptions from Chartmetric</a>\n",
    "* <a id='genre_locations'>Calculate similarity using Spotify artist genres and top streaming locations from Chartmetric</a>\n",
    "* <a id='comparison'>Compare pure genre approach with genre + location approach</a><br>\n",
    "* <a id='playlist_tags'>Find similar artists using genre + location data + playlist tags data</a><br>\n",
    "* <a id='knn'>Find similar artists using genre + location data with KNN approach</a><br>\n",
    "* <a id='topic'>Find similar artists by finding common topics their description matches to. Using Negative Matrix Factorization</a><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16880457-e164-408a-b4b7-ce5ad2d0eed3",
   "metadata": {},
   "source": [
    "TODO: try other similarity functions beside cosine<br>\n",
    "TODO: try cleaning genres further<br>\n",
    "TODO: Think about performance when matrix and vectors are much larger<br>\n",
    "TODO: When using top streamed countried, think about weighting them<br>\n",
    "TODO: Try LDA instead of NMF for topic modelling<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e822bb9-7374-42e3-a593-532bd31e117d",
   "metadata": {},
   "source": [
    "<b>Import packages and functions</b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f6644522-a3ed-4612-8920-2a03118c140a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The autoreload extension is already loaded. To reload it, use:\n",
      "  %reload_ext autoreload\n"
     ]
    }
   ],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "50500ca8-d494-46fc-81b6-b4e1b2d637ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "from snowflake.connector.pandas_tools import write_pandas\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "from sklearn.metrics.pairwise import cosine_similarity\n",
    "from sklearn.neighbors import NearestNeighbors\n",
    "from sklearn.decomposition import NMF\n",
    "\n",
    "from matplotlib import pyplot as plt\n",
    "from IPython.display import HTML\n",
    "\n",
    "# enable multiple outputs from single cell\n",
    "from IPython.core.interactiveshell import InteractiveShell\n",
    "InteractiveShell.ast_node_interactivity = \"all\"\n",
    "\n",
    "%matplotlib inline\n",
    "plt.style.use('bmh')\n",
    "\n",
    "# set display options\n",
    "pd.set_option('display.max_columns', 20) # default 20\n",
    "pd.set_option('display.max_colwidth', 150) # default 50"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b680a754-a5c0-4fb1-8aa4-4fb21ebd2f29",
   "metadata": {},
   "source": [
    "Include custom functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3004e3bb-b8b8-4e27-80e3-a8326824dc3b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package stopwords to\n",
      "[nltk_data]     /Users/rbomberg/nltk_data...\n",
      "[nltk_data]   Package stopwords is already up-to-date!\n",
      "[nltk_data] Downloading package punkt to /Users/rbomberg/nltk_data...\n",
      "[nltk_data]   Package punkt is already up-to-date!\n",
      "[nltk_data] Downloading package omw-1.4 to\n",
      "[nltk_data]     /Users/rbomberg/nltk_data...\n",
      "[nltk_data]   Package omw-1.4 is already up-to-date!\n"
     ]
    }
   ],
   "source": [
    "from utils.functions import *\n",
    "from utils.sim_functions import *"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c89384c4-6500-4805-8143-4c87f554fe0d",
   "metadata": {},
   "source": [
    "<b>Get data</b>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73957a84-3622-4409-8da4-03ab0b821531",
   "metadata": {},
   "source": [
    "First we will be working with data received from Chartmetric. This means genres, description and other data used in similarity scoring is dependant on what and how Chartmetric has collected."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "f693daad-6522-465a-ac54-2c38cc55f19e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# initiate connection\n",
    "from utils.snowflake_connection import * # check the content of this file to match your profile\n",
    "ctx, cur = snowflake_key_pair_connect()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c2cff5ad-da38-4831-9aa0-ee5aa6d8e763",
   "metadata": {},
   "source": [
    "<i>Here it's important to limit artists to use because similarity calculations in this notebook are not using\n",
    "most efficient and time saving approaches.</i>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7ddb2711-c943-486a-8499-fc4818581fd1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<snowflake.connector.cursor.SnowflakeCursor at 0x7f97b292a160>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "(72334, 10)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 72334 entries, 0 to 72333\n",
      "Columns: 10 entries, SPOTIFY_ARTIST_ID to C_TAG_NAME\n",
      "dtypes: int8(1), object(9)\n",
      "memory usage: 5.0+ MB\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SPOTIFY_ARTIST_ID</th>\n",
       "      <th>C_FAN_COUNTRY_CODE</th>\n",
       "      <th>C_POPULARITY</th>\n",
       "      <th>C_ARTIST_NAME</th>\n",
       "      <th>C_IS_BAND</th>\n",
       "      <th>C_GLOBAL_PARTICIPANT_ID</th>\n",
       "      <th>C_GENRES</th>\n",
       "      <th>C_PRONOUN</th>\n",
       "      <th>C_DESCRIPTION</th>\n",
       "      <th>C_TAG_NAME</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6TfJcKCr5hFsYZkq2k1Pac</td>\n",
       "      <td>NL|US|GB</td>\n",
       "      <td>32</td>\n",
       "      <td>Jayd Ink</td>\n",
       "      <td>False</td>\n",
       "      <td>27541f6b-43c3-4998-adb9-a203a6a74d34</td>\n",
       "      <td>deep pop r&amp;b</td>\n",
       "      <td>she/her</td>\n",
       "      <td>jayd ink singer songwriter global sound rooted hip hop reggae dancehall seasoned classic soul rb as continues navigate independent artist remains ...</td>\n",
       "      <td>r&amp;b/soul|hiphop/rap|uk contemporary r&amp;b|alternative r&amp;b|electronic|hip-hop/rap|world|alternative|dutch pop|tropical house|indie r&amp;b|nigerian pop|r...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        SPOTIFY_ARTIST_ID C_FAN_COUNTRY_CODE  C_POPULARITY C_ARTIST_NAME  \\\n",
       "0  6TfJcKCr5hFsYZkq2k1Pac           NL|US|GB            32      Jayd Ink   \n",
       "\n",
       "  C_IS_BAND               C_GLOBAL_PARTICIPANT_ID      C_GENRES C_PRONOUN  \\\n",
       "0     False  27541f6b-43c3-4998-adb9-a203a6a74d34  deep pop r&b   she/her   \n",
       "\n",
       "                                                                                                                                           C_DESCRIPTION  \\\n",
       "0  jayd ink singer songwriter global sound rooted hip hop reggae dancehall seasoned classic soul rb as continues navigate independent artist remains ...   \n",
       "\n",
       "                                                                                                                                              C_TAG_NAME  \n",
       "0  r&b/soul|hiphop/rap|uk contemporary r&b|alternative r&b|electronic|hip-hop/rap|world|alternative|dutch pop|tropical house|indie r&b|nigerian pop|r...  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# query table created with Notebook \"Similar Orchard artists.ipynb\"\n",
    "sql = \"\"\"select * from DEV_ENGINEERING.RBOMBERG_DBT.CHARTMERTIC_INPUT_FOR_REC limit 50000\n",
    "\"\"\"\n",
    "cur.execute(sql)\n",
    "chartmetric_df = cur.fetch_pandas_all()\n",
    "chartmetric_df.shape\n",
    "chartmetric_df.info(verbose=False, memory_usage=True)\n",
    "chartmetric_df.head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eafdda5b-51dd-42d9-a9a5-c30e57432018",
   "metadata": {},
   "source": [
    "### Prepate dataset for finding Spotify's most similar artists"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "91dbdca3-2e71-4d2a-bbd7-a38d8bb1142c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# query table created with Notebook \"Similar Orchard artists.ipynb\"\n",
    "sql = \"\"\"select MAIN_ARTIST, ARTIST_NAME, RELATED_ARTIST_ID, to_number(FOLLOWERS_LATEST) as FOLLOWERS_LATEST\n",
    "from DEV_ENGINEERING.RBOMBERG_DBT.RELATED_ARTISTS\n",
    "\"\"\"\n",
    "cur.execute(sql)\n",
    "related_artists_df = cur.fetch_pandas_all()\n",
    "related_artists_df.shape\n",
    "related_artists_df['FOLLOWERS_LATEST'].fillna(0, inplace=True)\n",
    "related_artists_df.info(verbose=False, memory_usage=True)\n",
    "# related_artists_df['display_value'] = related_artists_df['ARTIST_NAME'] + '- ' + \\\n",
    "#                related_artists_df['FOLLOWERS_LATEST'].map(str)\n",
    "related_artists_df.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "0bf30c5b-fd28-41ec-a7f2-86386275f294",
   "metadata": {},
   "outputs": [],
   "source": [
    "# prepare data for Streamlit\n",
    "# related_artists_df.to_pickle('pickles/related_artists_df.pkl')\n",
    "related_artists_df.to_parquet('pickles/related_artists_df.parquet', compression='brotli')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d1498a9-5ab9-4ae2-b34c-431a5ea0693f",
   "metadata": {},
   "source": [
    "### Calculate similarity using  Spotify artist genres from Chartmetric"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7cb04b1a-2430-4d96-b97b-73fff4859ab0",
   "metadata": {},
   "source": [
    "<b>Data exploration</b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "79d18d9f-b9e5-4729-9575-1bffb6e19642",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculating the genre word count\n",
    "chartmetric_df['genre_word_count'] = chartmetric_df['C_GENRES'].apply(lambda x: len(str(x).split('|')))\n",
    "max_words = chartmetric_df['genre_word_count'].max()\n",
    "\n",
    "# Plotting the genre word count\n",
    "chartmetric_df['genre_word_count'].plot(\n",
    "    kind='hist',\n",
    "    color = '#A60628',\n",
    "    bins = max_words-1,\n",
    "    figsize = (8,4),title='Word count distribution for genre terms')\n",
    "plt.xticks(np.arange(0, max_words, 1));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "a0af9b0d-f070-4609-a921-70f07189c737",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Some examples of artists who has 6 different genres:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>SPOTIFY_ARTIST_ID</th>\n",
       "      <th>C_GENRES</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>6U0uBUKWYZKZYFGL00hMsp</td>\n",
       "      <td>bubblegum dance|eurodance|europop|german dance|hands up|partyschlager</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6UfoTQXaV3DuqtDVjZIxwZ</td>\n",
       "      <td>disco|funk|minneapolis sound|post-disco|quiet storm|urban contemporary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6VJZYivuYJGCrPuOAnI7Qo</td>\n",
       "      <td>art pop|chamber psych|escape room|experimental pop|metropopolis|transpop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6VX2R9L0O0d6qPvqGuIH7b</td>\n",
       "      <td>dance pop|electropop|eurodance|europop|swedish electropop|swedish pop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6VXZCpbkwm0W0aPjQR1t4K</td>\n",
       "      <td>indie pop|indie poptimism|indietronica|la indie|modern rock|shimmer pop</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "examples = 6\n",
    "print(f\"Some examples of artists who has {examples} different genres:\")\n",
    "HTML(chartmetric_df[chartmetric_df['genre_word_count']==examples][['SPOTIFY_ARTIST_ID', 'C_GENRES']].\\\n",
    "     head().to_html(index=False))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "774dae4e-1c0a-4aac-a4ac-32062d458d2b",
   "metadata": {},
   "source": [
    "<b>Draw Wordcloud</b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "0e7edf9d-9bb0-4e4f-ac89-9a642ae58ac8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "genres_for_wcloud=\" \".join(chartmetric_df.C_GENRES.to_list())\n",
    "draw_word_cloud(genres_for_wcloud)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "7165df70-9f97-456e-9f38-7f2495d7f103",
   "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": [
    "chartmetric_df['C_IS_BAND'].value_counts().\\\n",
    "        plot.bar(title=f\"How many artists are defined as bands out of  {chartmetric_df.shape[0]} artists.\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "fea1ea67-4272-41c0-a657-f298db6a2d10",
   "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": [
    "chartmetric_df['C_PRONOUN'].value_counts().\\\n",
    "    plot.bar(title=f\"Distribution of known artist pronouns out of {chartmetric_df.shape[0]} artists.\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5fc5fa5a-6e1c-4ecc-a8e2-edf7577c021f",
   "metadata": {},
   "source": [
    "Prepare TFID"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "177823b4-b51d-4f1b-a9b0-ea42831e67a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(72334, 33912)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Matrix memory usage: 3.43684 megabytes.\n",
      "Matrix dype: <class 'scipy.sparse._csr.csr_matrix'>\n",
      "Nr of TF IDF features: 33912.\n",
      "First 10 TF IDF features: ['150' '150 bpm' '21st' '21st century' '21st century classical' '432hz'\n",
      " '48g' '8' '8 bit' '8d'].\n"
     ]
    }
   ],
   "source": [
    "tfidf = TfidfVectorizer(analyzer='word',\n",
    "                      token_pattern=r'\\w{1,}',\n",
    "                      ngram_range=(1, 3), \n",
    "                      stop_words = 'english')\n",
    "\n",
    "algo_input_df = chartmetric_df.copy()\n",
    "algo_input_df['C_GENRES'] =  algo_input_df['C_GENRES'].fillna('')\n",
    "algo_input_df['C_GENRES'] = algo_input_df['C_GENRES'].apply(replace_straight_with_space)\n",
    "# Fitting the TF-IDF on the genres\n",
    "tfidf_matrix = tfidf.fit_transform(algo_input_df['C_GENRES'])\n",
    "\n",
    "tfidf_matrix.shape\n",
    "print(f\"Matrix memory usage: {tfidf_matrix.data.nbytes / 1000000} megabytes.\")\n",
    "print(f\"Matrix dype: {type(tfidf_matrix)}\")\n",
    "print(f\"Nr of TF IDF features: {len(tfidf.get_feature_names_out())}.\")\n",
    "print(f\"First 10 TF IDF features: {tfidf.get_feature_names_out()[0:10]}.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "21a22798-ae9f-4c0a-b42f-34fd7bd033dd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Similarity matrix memory usage: 41857.660448 megabytes.\n",
      "Similarity matrix with float16 memory usage: 10464.415112 megabytes.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(72334, 72334)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Matrix data dype: float16\n",
      "Similarity matrix memory usage: 10464.415112 megabytes.\n"
     ]
    }
   ],
   "source": [
    "# Compute the Cosine Similarity\n",
    "similarity_matrix = cosine_similarity(tfidf_matrix, tfidf_matrix)\n",
    "print(f\"Similarity matrix memory usage: {similarity_matrix.data.nbytes / 1000000} megabytes.\")\n",
    "#similarity_matrix[0]\n",
    "\n",
    "# convert to float16\n",
    "similarity_matrix = np.round_(similarity_matrix, decimals = 3)\n",
    "similarity_matrix = similarity_matrix.astype(np.float16)\n",
    "print(f\"Similarity matrix with float16 memory usage: {similarity_matrix.data.nbytes / 1000000} megabytes.\")\n",
    "#similarity_matrix[0]\n",
    "similarity_matrix.shape\n",
    "\n",
    "print(f\"Matrix data dype: {similarity_matrix.dtype}\")\n",
    "print(f\"Similarity matrix memory usage: {similarity_matrix.data.nbytes / 1000000} megabytes.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f0d74084-4109-4538-b8b4-ad75a37ad63d",
   "metadata": {},
   "source": [
    "<b><i>Use next steps if you want to include only top X artists based on similarity matrix. This will greatly reduce\n",
    "file sizes required to move to the Streamlit server</i></b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "a57d5082-7039-41ea-9b79-bcef168d952d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(72334, 10)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "array([54921, 34119, 60546, 21672,  6250, 32577, 12861, 62830,   191,\n",
       "           0])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "(72334, 10)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1.], dtype=float16)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "top x only matrix memory usage: 5.78672 megabytes.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(72334, 10)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "top x  only matrix values memory usage: 1.44668 megabytes.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(72334, 10)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n = 10 # nr of artists to keep\n",
    "indices_ = pd.Series(algo_input_df.index, index=algo_input_df['SPOTIFY_ARTIST_ID']).drop_duplicates()\n",
    "\n",
    "# compression\n",
    "top_matches_array = np.argsort(similarity_matrix)[:, -n:]\n",
    "top_matches_array.shape\n",
    "top_matches_array[0]\n",
    "\n",
    "top_matches_scores = similarity_matrix[np.expand_dims(np.arange(similarity_matrix.shape[0]), -1), top_matches_array]\n",
    "top_matches_scores.shape\n",
    "top_matches_scores[0]\n",
    "\n",
    "print(f\"top x only matrix memory usage: {top_matches_array.data.nbytes / 1000000} megabytes.\")\n",
    "top_matches_array.shape\n",
    "print(f\"top x  only matrix values memory usage: {top_matches_scores.data.nbytes / 1000000} megabytes.\")\n",
    "top_matches_scores.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "603a38bd-bd24-4369-866c-3cc50abd433b",
   "metadata": {},
   "outputs": [],
   "source": [
    "np.save('pickles/top_matches_array.npy', top_matches_array)\n",
    "np.save('pickles/top_matches_scores.npy', top_matches_scores)\n",
    "indices_.to_pickle('pickles/indices_.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "fb122ff5-4158-4e35-9584-44f6ae48c42a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Spotify id: 6iTD167bhyfYwEd7fd2bGn.\n",
      "artist name: Sugar Minott.\n",
      "top streaming countries: GB|NZ|AU.\n",
      "genres: dub lovers rock old school dancehall reggae rock steady roots reggae\n",
      "------------\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>score</th>\n",
       "      <th>name</th>\n",
       "      <th>popularity</th>\n",
       "      <th>spotify_id</th>\n",
       "      <th>streaming_country</th>\n",
       "      <th>spotify_genre</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>63482</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>Johnny Osbourne</td>\n",
       "      <td>44</td>\n",
       "      <td>5TUTGRG0FlRoYTZ4GEdOVO</td>\n",
       "      <td>GB|US|BR</td>\n",
       "      <td>dub lovers rock old school dancehall reggae rock steady roots reggae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4165</td>\n",
       "      <td>0.754883</td>\n",
       "      <td>Yellowman</td>\n",
       "      <td>47</td>\n",
       "      <td>6yTNMMqumesCWhMJ47HB2a</td>\n",
       "      <td>US|GB|MX</td>\n",
       "      <td>dub lovers rock old school dancehall reggae roots reggae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>38184</td>\n",
       "      <td>0.754883</td>\n",
       "      <td>Michael Prophet</td>\n",
       "      <td>29</td>\n",
       "      <td>2qUfyLUGgzdl230mYZsu82</td>\n",
       "      <td>GB|US|BR</td>\n",
       "      <td>dub lovers rock old school dancehall reggae roots reggae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>45017</td>\n",
       "      <td>0.676758</td>\n",
       "      <td>Bunny Wailer</td>\n",
       "      <td>52</td>\n",
       "      <td>389zc5Rwe0MPcE6mSF4AjC</td>\n",
       "      <td>US|BR|GB</td>\n",
       "      <td>dub lovers rock reggae rock steady roots reggae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>52734</td>\n",
       "      <td>0.676758</td>\n",
       "      <td>Culture</td>\n",
       "      <td>47</td>\n",
       "      <td>4DbtUTi2WsBNdruAZL2pNz</td>\n",
       "      <td>US|BR|GB</td>\n",
       "      <td>dub lovers rock reggae rock steady roots reggae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>41999</td>\n",
       "      <td>0.676758</td>\n",
       "      <td>Freddie McGregor</td>\n",
       "      <td>46</td>\n",
       "      <td>30R9paG1c5BGtNGle59VPq</td>\n",
       "      <td>US|GB|CA</td>\n",
       "      <td>dub lovers rock reggae rock steady roots reggae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>55329</td>\n",
       "      <td>0.676758</td>\n",
       "      <td>U-Roy</td>\n",
       "      <td>46</td>\n",
       "      <td>4aCH6cwaYahrWfJWqfEfra</td>\n",
       "      <td>US|GB|BR</td>\n",
       "      <td>dub lovers rock reggae rock steady roots reggae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>29879</td>\n",
       "      <td>0.676758</td>\n",
       "      <td>Big Youth</td>\n",
       "      <td>42</td>\n",
       "      <td>2TdzGitZtbe3Zw3BB4SFEH</td>\n",
       "      <td>US|GB|BR</td>\n",
       "      <td>dub lovers rock reggae rock steady roots reggae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>21733</td>\n",
       "      <td>0.655762</td>\n",
       "      <td>Frankie Paul</td>\n",
       "      <td>37</td>\n",
       "      <td>1J4CDjVHn8ummXVmJ7Q73u</td>\n",
       "      <td>GB|US|CA</td>\n",
       "      <td>deep ragga dub lovers rock old school dancehall reggae roots reggae</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index     score              name  popularity              spotify_id  \\\n",
       "0  63482  1.000000   Johnny Osbourne          44  5TUTGRG0FlRoYTZ4GEdOVO   \n",
       "0   4165  0.754883         Yellowman          47  6yTNMMqumesCWhMJ47HB2a   \n",
       "0  38184  0.754883   Michael Prophet          29  2qUfyLUGgzdl230mYZsu82   \n",
       "0  45017  0.676758      Bunny Wailer          52  389zc5Rwe0MPcE6mSF4AjC   \n",
       "0  52734  0.676758           Culture          47  4DbtUTi2WsBNdruAZL2pNz   \n",
       "0  41999  0.676758  Freddie McGregor          46  30R9paG1c5BGtNGle59VPq   \n",
       "0  55329  0.676758             U-Roy          46  4aCH6cwaYahrWfJWqfEfra   \n",
       "0  29879  0.676758         Big Youth          42  2TdzGitZtbe3Zw3BB4SFEH   \n",
       "0  21733  0.655762      Frankie Paul          37  1J4CDjVHn8ummXVmJ7Q73u   \n",
       "\n",
       "  streaming_country  \\\n",
       "0          GB|US|BR   \n",
       "0          US|GB|MX   \n",
       "0          GB|US|BR   \n",
       "0          US|BR|GB   \n",
       "0          US|BR|GB   \n",
       "0          US|GB|CA   \n",
       "0          US|GB|BR   \n",
       "0          US|GB|BR   \n",
       "0          GB|US|CA   \n",
       "\n",
       "                                                          spotify_genre  \n",
       "0  dub lovers rock old school dancehall reggae rock steady roots reggae  \n",
       "0              dub lovers rock old school dancehall reggae roots reggae  \n",
       "0              dub lovers rock old school dancehall reggae roots reggae  \n",
       "0                       dub lovers rock reggae rock steady roots reggae  \n",
       "0                       dub lovers rock reggae rock steady roots reggae  \n",
       "0                       dub lovers rock reggae rock steady roots reggae  \n",
       "0                       dub lovers rock reggae rock steady roots reggae  \n",
       "0                       dub lovers rock reggae rock steady roots reggae  \n",
       "0   deep ragga dub lovers rock old school dancehall reggae roots reggae  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spotify_id = '6Tg5wgFNHcQhNPK5zrFC34'\n",
    "spotify_id = '6iTD167bhyfYwEd7fd2bGn'\n",
    "#spotify_id = '6TfJcKCr5hFsYZkq2k1Pac'\n",
    "#spotify_id = '7N026dv4AShbedLUEwAQkN'\n",
    "\n",
    "get_limited_similarity(algo_input_df, top_matches_array, top_matches_scores, indices_, spotify_id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "cd51d915-ea95-4acd-8aac-b7987c0023a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "#np.save('pickles/similarity_matrix.npy', similarity_matrix)\n",
    "#np.savez_compressed(\"pickles/similarity_matrix33.npz\", a=similarity_matrix33)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "c0af5350-7699-4165-8ddc-dcfa14b94a3b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Similarity matrix indice memory usage: 1.157344 megabytes.\n"
     ]
    }
   ],
   "source": [
    "# Create a pandas series with spotify artist id as indices and indices as series values \n",
    "indices = pd.Series(algo_input_df.index, index=algo_input_df['SPOTIFY_ARTIST_ID']).drop_duplicates()\n",
    "print(f\"Similarity matrix indice memory usage: {indices.memory_usage() / 1000000} megabytes.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6843aecc-d6c5-4d60-9eed-d27d68073d5b",
   "metadata": {},
   "source": [
    "Prepare objects for usage in Streamlit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "9506c914-3140-4eea-8531-fc519c27ff06",
   "metadata": {},
   "outputs": [],
   "source": [
    "algo_input_df.to_parquet('pickles/algo_input_df_for_pickle.parquet', compression='brotli') # creates file with size: 19.9 MB\n",
    "np.save('pickles/similarity_matrix_for_pickle.npy', similarity_matrix) # creates file with size: 19.35 GB\n",
    "#np.save('pickles/similarity_matrix_for_pickle2.npy', similarity_matrix2)# creates file with size: 4.84 GB\n",
    "indices.to_pickle('pickles/indices_for_pickle.pkl') # creates file with size: 1.9 MB"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "3169c73f-eaab-49f3-8eee-f297a0b09cf1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "What artist are you looking for: Cobbs\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cobbs\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>SPOTIFY_ARTIST_ID</th>\n",
       "      <th>C_ARTIST_NAME</th>\n",
       "      <th>C_POPULARITY</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>7N026dv4AShbedLUEwAQkN</td>\n",
       "      <td>Tasha Cobbs Leonard</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Use this function to find artists by name for testing similarity\n",
    "while True:\n",
    "    artist_name = input(\"What artist are you looking for:\")\n",
    "    artist_name = artist_name.lower()\n",
    "    print(artist_name)\n",
    "    chartmetric_df['search_string'] = chartmetric_df['C_ARTIST_NAME'].str.lower()\n",
    "    HTML(chartmetric_df[chartmetric_df['search_string'].str.contains(artist_name)][['SPOTIFY_ARTIST_ID', 'C_ARTIST_NAME', 'C_POPULARITY']].sort_values(by=['C_POPULARITY'],ascending=False).head().to_html(index=False))\n",
    "    chartmetric_df = chartmetric_df.drop(['search_string'], axis=1)\n",
    "    break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "f336c5b5-5a2b-477c-a8dd-120ffcf870a1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "artist index: 7396.\n",
      "artist name: Tasha Cobbs Leonard.\n",
      "playlist tag: música cristiana y góspel|contemporary gospel|christian music|pretos no topo|cristã|christian & gospel|gospel|urban contemporary|naija worship|worship|christian christmas|christian|gospel r&b|adoracao|pop rap|brazilian gospel|world worship|ccm|r&b|praise|louvor.\n",
      "top streaming countries:           US|GB|ZA.\n",
      "genres: gospel naija worship\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>score</th>\n",
       "      <th>name</th>\n",
       "      <th>popularity</th>\n",
       "      <th>spotify_id</th>\n",
       "      <th>streaming_country</th>\n",
       "      <th>spotify_genre</th>\n",
       "      <th>playlist_tags</th>\n",
       "      <th>spotify_description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5301</td>\n",
       "      <td>0.696777</td>\n",
       "      <td>Israel &amp; New Breed</td>\n",
       "      <td>49</td>\n",
       "      <td>77HU1Zb1VDIFvWKteJii0E</td>\n",
       "      <td>US|GT|ID</td>\n",
       "      <td>gospel naija worship world worship worship</td>\n",
       "      <td>pop|singer/songwriter|adoracion|gospel|jazz|christian|contemporary gospel|música cristiana y góspel|anthem worship|worship|hip hop|world worship|l...</td>\n",
       "      <td>worship leader recording artist songwriter producer israel houghton became involved full time worship ministry 1989 from start looked overcome cul...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>36973</td>\n",
       "      <td>0.667969</td>\n",
       "      <td>Uche Agu</td>\n",
       "      <td>34</td>\n",
       "      <td>2nSP3Ap7hxf4m4o5F5RXVj</td>\n",
       "      <td>NG|GB|US</td>\n",
       "      <td>naija worship</td>\n",
       "      <td>ghanaian gospel|naija worship|musique chrétienne et gospel|afro soul|gospel|christian &amp; gospel|zambian pop|azontobeats|afropop|christian afrobeat|...</td>\n",
       "      <td>songwriter worship leader christian gospel recording artist started singing 4 years old since travelled world bringing people presence god n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>41049</td>\n",
       "      <td>0.667969</td>\n",
       "      <td>Mike Abdul</td>\n",
       "      <td>28</td>\n",
       "      <td>2xsK8uSdgTzy65SicS3LzK</td>\n",
       "      <td>NG|US|GB</td>\n",
       "      <td>naija worship</td>\n",
       "      <td>danish pop|rock|classic danish pop|world|christian &amp; gospel|naija worship|coverchill|highlife|zambian pop|contemporary gospel|christian|gospel|dan...</td>\n",
       "      <td>mike abduls style appeals average person turns street church draws souls christ helps wean energetic christian youth blesses teaches entertains se...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>32250</td>\n",
       "      <td>0.667969</td>\n",
       "      <td>Evans Ogboi</td>\n",
       "      <td>27</td>\n",
       "      <td>2atv3xZ8TKAZoDUWES3ho0</td>\n",
       "      <td>NG|GB|US</td>\n",
       "      <td>naija worship</td>\n",
       "      <td>gospel|gospel r&amp;b|south african gospel|christian|afro soul|christian &amp; gospel|south african pop|contemporary gospel</td>\n",
       "      <td>evans ogboi multi award winning singer songwriter music producer gospel recording artiste motivational speaker nin 2007 launched music career rele...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>14110</td>\n",
       "      <td>0.667969</td>\n",
       "      <td>Infinity</td>\n",
       "      <td>26</td>\n",
       "      <td>0Fh2E4lCLZzOMS6EC4Ue6U</td>\n",
       "      <td>NG|DE|GB</td>\n",
       "      <td>naija worship</td>\n",
       "      <td>pop|trance|gangster rap|rap rock|kansas city hip hop|holiday|dance|dirty texas rap|hip hop|children's music|naija worship|rap|hip-hop/rap</td>\n",
       "      <td>infinity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>57127</td>\n",
       "      <td>0.667969</td>\n",
       "      <td>Fimba Onyekachi</td>\n",
       "      <td>2</td>\n",
       "      <td>4onWLzy51eqiX05UnLbbGi</td>\n",
       "      <td>US|NG|GB</td>\n",
       "      <td>naija worship</td>\n",
       "      <td>None</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>56971</td>\n",
       "      <td>0.667969</td>\n",
       "      <td>Ibitayo</td>\n",
       "      <td>0</td>\n",
       "      <td>4nZ2zAALigeLVTrNIF7XBd</td>\n",
       "      <td>US|GB|NG</td>\n",
       "      <td>naija worship</td>\n",
       "      <td>None</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index     score                name  popularity              spotify_id  \\\n",
       "0   5301  0.696777  Israel & New Breed          49  77HU1Zb1VDIFvWKteJii0E   \n",
       "0  36973  0.667969            Uche Agu          34  2nSP3Ap7hxf4m4o5F5RXVj   \n",
       "0  41049  0.667969          Mike Abdul          28  2xsK8uSdgTzy65SicS3LzK   \n",
       "0  32250  0.667969         Evans Ogboi          27  2atv3xZ8TKAZoDUWES3ho0   \n",
       "0  14110  0.667969            Infinity          26  0Fh2E4lCLZzOMS6EC4Ue6U   \n",
       "0  57127  0.667969     Fimba Onyekachi           2  4onWLzy51eqiX05UnLbbGi   \n",
       "0  56971  0.667969             Ibitayo           0  4nZ2zAALigeLVTrNIF7XBd   \n",
       "\n",
       "  streaming_country                               spotify_genre  \\\n",
       "0          US|GT|ID  gospel naija worship world worship worship   \n",
       "0          NG|GB|US                               naija worship   \n",
       "0          NG|US|GB                               naija worship   \n",
       "0          NG|GB|US                               naija worship   \n",
       "0          NG|DE|GB                               naija worship   \n",
       "0          US|NG|GB                               naija worship   \n",
       "0          US|GB|NG                               naija worship   \n",
       "\n",
       "                                                                                                                                           playlist_tags  \\\n",
       "0  pop|singer/songwriter|adoracion|gospel|jazz|christian|contemporary gospel|música cristiana y góspel|anthem worship|worship|hip hop|world worship|l...   \n",
       "0  ghanaian gospel|naija worship|musique chrétienne et gospel|afro soul|gospel|christian & gospel|zambian pop|azontobeats|afropop|christian afrobeat|...   \n",
       "0  danish pop|rock|classic danish pop|world|christian & gospel|naija worship|coverchill|highlife|zambian pop|contemporary gospel|christian|gospel|dan...   \n",
       "0                                    gospel|gospel r&b|south african gospel|christian|afro soul|christian & gospel|south african pop|contemporary gospel   \n",
       "0              pop|trance|gangster rap|rap rock|kansas city hip hop|holiday|dance|dirty texas rap|hip hop|children's music|naija worship|rap|hip-hop/rap   \n",
       "0                                                                                                                                                   None   \n",
       "0                                                                                                                                                   None   \n",
       "\n",
       "                                                                                                                                     spotify_description  \n",
       "0  worship leader recording artist songwriter producer israel houghton became involved full time worship ministry 1989 from start looked overcome cul...  \n",
       "0           songwriter worship leader christian gospel recording artist started singing 4 years old since travelled world bringing people presence god n  \n",
       "0  mike abduls style appeals average person turns street church draws souls christ helps wean energetic christian youth blesses teaches entertains se...  \n",
       "0  evans ogboi multi award winning singer songwriter music producer gospel recording artiste motivational speaker nin 2007 launched music career rele...  \n",
       "0                                                                                                                                               infinity  \n",
       "0                                                                                                                                                         \n",
       "0                                                                                                                                                         "
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#spotify_id='7zpktFUPT54c6O46zTgmgh'\n",
    "#spotify_id='7zqFsB8lPDwJI5mNV8c8Qr'\n",
    "#spotify_id = '7zq77JpGaaWnMC9Ff3vOqt'\n",
    "spotify_id = '7zYOs83aBa0MGKTXjcqeIc'\n",
    "spotify_id = '7ztX3VdsQ5LGaTp22jN9Gu'\n",
    "spotify_id = '05RHLROZlMHyLOOzOVwiBJ'\n",
    "# spotify_id = '5G3Tk9bNgXmBpMnUCesqQx' # Sia\n",
    "spotify_id = '03zMprDSi8xGJbXYayx6ly'\n",
    "# spotify_id = '0YIq6I0CdBgPOUKHVyZU1k' # DJ Snake \t\n",
    "spotify_id = '0wcwd9rVgYgvbSBOlxZRc9' # tiesto\n",
    "spotify_id = '7N026dv4AShbedLUEwAQkN'\n",
    "\n",
    "response = get_similarity(algo_input_df, similarity_matrix, indices, spotify_id, 7)\n",
    "response"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b918d99d-0f1f-4137-9b85-7a350790b589",
   "metadata": {},
   "source": [
    "-----"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d45984fb-9eef-44a9-bd07-0131d73c5cde",
   "metadata": {},
   "source": [
    "<a id=’section_1’></a>\n",
    "### Calculate similarity using  Spotify artist descriptions from Chartmetric"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "348a998f-528e-4ba1-83a7-2b7a02d07d6d",
   "metadata": {},
   "source": [
    "We need to apply several text processing steps to clean artist description."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57f4dd0b-d4bd-4931-98d4-4cec152237ed",
   "metadata": {},
   "source": [
    "<b>Stemmer and/or lemmatizer</b><br>\n",
    "Stemming just removes or stems the last few characters of a word, often leading to incorrect meanings and spellings. Lemmatization\n",
    "cosndiers the context and converts the word to its meaningful base form, which is called Lemma. Sometimes, the same word can have\n",
    "multiple different lemmas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "e42ee288-d67d-49f0-a05e-dc1cfbb78647",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SPOTIFY_ARTIST_ID</th>\n",
       "      <th>C_FAN_COUNTRY_CODE</th>\n",
       "      <th>C_POPULARITY</th>\n",
       "      <th>C_ARTIST_NAME</th>\n",
       "      <th>IS_BAND</th>\n",
       "      <th>C_GLOBAL_PARTICIPANT_ID</th>\n",
       "      <th>C_GENRES</th>\n",
       "      <th>C_PRONOUN</th>\n",
       "      <th>C_DESCRIPTION</th>\n",
       "      <th>CLEANED_TAG_NAME</th>\n",
       "      <th>genre_word_count</th>\n",
       "      <th>tokens</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>00045gNg7mLEf9UY9yhD0t</td>\n",
       "      <td>NL|BE|DE</td>\n",
       "      <td>8</td>\n",
       "      <td>Kubus &amp; BangBang</td>\n",
       "      <td>NaN</td>\n",
       "      <td>78ece065-c562-4910-a003-a2d28b932a29</td>\n",
       "      <td>dutch hip hop</td>\n",
       "      <td>None</td>\n",
       "      <td></td>\n",
       "      <td>None</td>\n",
       "      <td>1</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>000Dq0VqTZpxOP6jQMscVL</td>\n",
       "      <td>US|CO|PE</td>\n",
       "      <td>8</td>\n",
       "      <td>Thug Brothers</td>\n",
       "      <td>NaN</td>\n",
       "      <td>400da8b4-e44d-4cd3-81be-be46e7686837</td>\n",
       "      <td>baton rouge rap|deep southern trap</td>\n",
       "      <td>None</td>\n",
       "      <td>thug brothers</td>\n",
       "      <td>None</td>\n",
       "      <td>2</td>\n",
       "      <td>[thug, brothers]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>004TazQx2Apn4Ynnti4Jf5</td>\n",
       "      <td>ES|US|FR</td>\n",
       "      <td>8</td>\n",
       "      <td>Forma Antiqva</td>\n",
       "      <td>1.0</td>\n",
       "      <td>d0ed35ce-d812-45eb-a571-15d1b4240ace</td>\n",
       "      <td>musica antigua</td>\n",
       "      <td>they/them</td>\n",
       "      <td>centrado en los hermanos pablo daniel aarn zapico forma antiqva es un conjunto de msica barroca de formacin variable que rene los intrpretes ms br...</td>\n",
       "      <td>contemporary jazz|audiophile vocal|classical</td>\n",
       "      <td>1</td>\n",
       "      <td>[centrado, en, los, hermanos, pablo, daniel, aarn, zapico, forma, antiqva, es, un, conjunto, de, msica, barroca, de, formacin, variable, que, rene...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>00GU50OzuFhMY8WQ1RjdrR</td>\n",
       "      <td>US|RU|UA</td>\n",
       "      <td>6</td>\n",
       "      <td>Elijah Kelly</td>\n",
       "      <td>NaN</td>\n",
       "      <td>273e9f56-bbde-48f8-b305-015e9298ce99</td>\n",
       "      <td>hollywood</td>\n",
       "      <td>None</td>\n",
       "      <td></td>\n",
       "      <td>None</td>\n",
       "      <td>1</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        SPOTIFY_ARTIST_ID C_FAN_COUNTRY_CODE  C_POPULARITY     C_ARTIST_NAME  \\\n",
       "0  00045gNg7mLEf9UY9yhD0t           NL|BE|DE             8  Kubus & BangBang   \n",
       "1  000Dq0VqTZpxOP6jQMscVL           US|CO|PE             8     Thug Brothers   \n",
       "2  004TazQx2Apn4Ynnti4Jf5           ES|US|FR             8     Forma Antiqva   \n",
       "3  00GU50OzuFhMY8WQ1RjdrR           US|RU|UA             6      Elijah Kelly   \n",
       "\n",
       "   IS_BAND               C_GLOBAL_PARTICIPANT_ID  \\\n",
       "0      NaN  78ece065-c562-4910-a003-a2d28b932a29   \n",
       "1      NaN  400da8b4-e44d-4cd3-81be-be46e7686837   \n",
       "2      1.0  d0ed35ce-d812-45eb-a571-15d1b4240ace   \n",
       "3      NaN  273e9f56-bbde-48f8-b305-015e9298ce99   \n",
       "\n",
       "                             C_GENRES  C_PRONOUN  \\\n",
       "0                       dutch hip hop       None   \n",
       "1  baton rouge rap|deep southern trap       None   \n",
       "2                      musica antigua  they/them   \n",
       "3                           hollywood       None   \n",
       "\n",
       "                                                                                                                                           C_DESCRIPTION  \\\n",
       "0                                                                                                                                                          \n",
       "1                                                                                                                                          thug brothers   \n",
       "2  centrado en los hermanos pablo daniel aarn zapico forma antiqva es un conjunto de msica barroca de formacin variable que rene los intrpretes ms br...   \n",
       "3                                                                                                                                                          \n",
       "\n",
       "                               CLEANED_TAG_NAME  genre_word_count  \\\n",
       "0                                          None                 1   \n",
       "1                                          None                 2   \n",
       "2  contemporary jazz|audiophile vocal|classical                 1   \n",
       "3                                          None                 1   \n",
       "\n",
       "                                                                                                                                                  tokens  \n",
       "0                                                                                                                                                     []  \n",
       "1                                                                                                                                       [thug, brothers]  \n",
       "2  [centrado, en, los, hermanos, pablo, daniel, aarn, zapico, forma, antiqva, es, un, conjunto, de, msica, barroca, de, formacin, variable, que, rene...  \n",
       "3                                                                                                                                                     []  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "algo_input_desc_df = chartmetric_df.copy()\n",
    "algo_input_desc_df['C_DESCRIPTION'] = algo_input_desc_df['C_DESCRIPTION'].\\\n",
    "            str.replace('href', '').str.replace('spotify', '') # get rid of some noise\n",
    "algo_input_desc_df['tokens'] = algo_input_desc_df['C_DESCRIPTION'].map(tokenize)\n",
    "algo_input_desc_df.head(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "501ac5d9-3643-4ca6-844d-7900589a072d",
   "metadata": {},
   "outputs": [],
   "source": [
    "algo_input_desc_df['lem'] = algo_input_desc_df['tokens'].map(lemmatize)\n",
    "algo_input_desc_df['stem'] = algo_input_desc_df['tokens'].map(stemmer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "654a1171-b31f-4af9-8f28-746282b46198",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cloud_input_desc=\" \".join(algo_input_desc_df.lem)\n",
    "draw_word_cloud(cloud_input_desc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "2e353606-d450-4b07-8db5-1629cf1f6cce",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of artists with missing Spotify description that we need to exclude:\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "2343"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Number of artists with missing Spotify description that we need to exclude:\")\n",
    "algo_input_desc_df[algo_input_desc_df['C_DESCRIPTION']=='']['C_DESCRIPTION'].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "f89a0ca7-2c8a-4814-b778-38c9367d44b5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2845, 5000)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Matrix memory usage: 0.183632 megabytes.\n",
      "Nr of TF IDF features: 5000.\n",
      "First 10 TF IDF features: ['000 copy' '1 000' '1 2' '1 3' '1 album' '1 hit' '1 n' '10 aos' '10 year'\n",
      " '100 000'].\n"
     ]
    }
   ],
   "source": [
    "tfidf_desc = TfidfVectorizer(analyzer='word',\n",
    "                      token_pattern=r'\\w{1,}',\n",
    "                      ngram_range=(2, 3),\n",
    "                      max_features=5000, # possible parameter to apply\n",
    "                      smooth_idf = True,\n",
    "                      stop_words = 'english')\n",
    "\n",
    "algo_input_desc_df2 = algo_input_desc_df[algo_input_desc_df['C_DESCRIPTION']!=''].copy().reset_index()\n",
    "# Fitting the TF-IDF on the 'description' column\n",
    "tfidf_matrix_desc = tfidf_desc.fit_transform(algo_input_desc_df2['lem'])\n",
    "\n",
    "tfidf_matrix_desc.shape\n",
    "print(f\"Matrix memory usage: {tfidf_matrix_desc.data.nbytes / 1000000} megabytes.\")\n",
    "print(f\"Nr of TF IDF features: {len(tfidf_desc.get_feature_names_out())}.\")\n",
    "print(f\"First 10 TF IDF features: {tfidf_desc.get_feature_names_out()[0:10]}.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "0e74337c-a57d-4b47-861c-66e888dda676",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Compute the Cosine Similarity\n",
    "similarity_matrix_desc = cosine_similarity(tfidf_matrix_desc, tfidf_matrix_desc)\n",
    "\n",
    "# Create a pandas series with spotify artist id as indices and indices as series values \n",
    "indices_desc = pd.Series(algo_input_desc_df2.index, index=algo_input_desc_df2['SPOTIFY_ARTIST_ID']).drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "3326c58e-34f1-47b5-8307-9097a72047e3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "What artist are you looking for? Romeo\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "romeo\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>SPOTIFY_ARTIST_ID</th>\n",
       "      <th>C_ARTIST_NAME</th>\n",
       "      <th>C_POPULARITY</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>7z7qWp4KfPONqlpiT2HRau</td>\n",
       "      <td>Romeo Santos</td>\n",
       "      <td>78</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "while True:\n",
    "    artist_name = input(\"What artist are you looking for?\")\n",
    "    artist_name = artist_name.lower()\n",
    "    print(artist_name)\n",
    "    algo_input_desc_df2['search_string'] = algo_input_desc_df2['C_ARTIST_NAME'].str.lower()\n",
    "    HTML(algo_input_desc_df2[algo_input_desc_df2['search_string'].str.contains(artist_name)][['SPOTIFY_ARTIST_ID', 'C_ARTIST_NAME', 'C_POPULARITY']].sort_values(by=['C_POPULARITY'],ascending=False).head().to_html(index=False))\n",
    "    algo_input_desc_df2 = algo_input_desc_df2.drop(['search_string'], axis=1)\n",
    "    break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "45c3ab08-13aa-414d-8a3c-a79951ba5a4c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "artist index: 1785.\n",
      "artist name: Omar Varela.\n",
      "playlist tag: trap latino|hip-hop|emo rap|tropical|latin urban|latin pop|folklore argentino|pop argentino|pop reggaeton|rock catala|tokio|decades|reggaeton flow|vapor trap|argentine hip hop|perreo|hip-hop/rap|latin|rap latina|trap chileno|latin viral pop|rap espanol|miami hip hop|israeli pop|musique latine|underground hip hop|summer|italian pop|cumbia villera|dominican pop|drill espanol|trap argentino|electronic|mood|trap|italian underground hip hop|mexican hip hop|italian arena pop|argentine rock|pop rap|rock|reggaeton chileno|trap italiana|rap|tquio|dance/electrnica|venezuelan hip hop|hyperpop en espanol|latin hip hop|edm|rap chileno|mizrahi|trap catala|trending|rock en espanol|rap dominicano|flamenco urbano|cumbia 420|tokyo|trap triste|dance pop|deep german hip hop|electronic trap|pop|reggaeton|latino|italian hip hop|tropical house|spanish hip hop|otacore|latin rap|urbano espanol|reggaeton mexicano|rkt|party|regional mexican|msica latina|rap uruguayo|rap napoletano|hip hop|trap espanol|german hip hop|dance|cumbia paraguaya|pop dance|italian adult pop|r&b en espanol|chamame|dance/electronic|chilean indie|cumbia pop|dubstep|tendencias|gaming dubstep|dark trap|mexican pop.\n",
      "top streaming countries:           AR|PY|CO.\n",
      "genres: zapstep\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>score</th>\n",
       "      <th>name</th>\n",
       "      <th>popularity</th>\n",
       "      <th>spotify_id</th>\n",
       "      <th>streaming_country</th>\n",
       "      <th>spotify_genre</th>\n",
       "      <th>playlist_tags</th>\n",
       "      <th>spotify_description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2469</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>West.K</td>\n",
       "      <td>31</td>\n",
       "      <td>78I7kZBeZ01Y1oy6MwyZtT</td>\n",
       "      <td>BR|MX|DE</td>\n",
       "      <td>groove room</td>\n",
       "      <td>pop|turkish pop|dance|turkish deep house|house|electronic|nu disco|swiss hip hop|groove room|turkish trap pop|brazilian edm|deep uplifting trance|...</td>\n",
       "      <td>french dj producer making electronic stuff passion</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1827</td>\n",
       "      <td>0.689373</td>\n",
       "      <td>Toryn D</td>\n",
       "      <td>1</td>\n",
       "      <td>617xLhecSzV7J0ePCzaDkf</td>\n",
       "      <td>AU|GB|NL</td>\n",
       "      <td>hard trance</td>\n",
       "      <td>None</td>\n",
       "      <td>intergalactic dj producer npart lunatic response unit the edison factor acidanimal thunderc nts effect nowner mental health records ltd n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2753</td>\n",
       "      <td>0.495105</td>\n",
       "      <td>Dr Carlvader</td>\n",
       "      <td>0</td>\n",
       "      <td>7qxDNvmecLP9gKR72jHplK</td>\n",
       "      <td>ES|IT|US</td>\n",
       "      <td>musica andorra</td>\n",
       "      <td>None</td>\n",
       "      <td>as dj producer always trying looking sound style make feel music first single published f me 1997 whole allegation intentions dance floor trance s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2128</td>\n",
       "      <td>0.320534</td>\n",
       "      <td>Kingswell</td>\n",
       "      <td>1</td>\n",
       "      <td>6XTTwEGdZmtIayxqMjYh41</td>\n",
       "      <td>MX|GT|US</td>\n",
       "      <td>mexican edm</td>\n",
       "      <td>None</td>\n",
       "      <td>francisco reyes mexican dj producer young age played best nightclubs mexico city he working debut upcoming album working singles coming soon</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index     score          name  popularity              spotify_id  \\\n",
       "0   2469  1.000000        West.K          31  78I7kZBeZ01Y1oy6MwyZtT   \n",
       "0   1827  0.689373       Toryn D           1  617xLhecSzV7J0ePCzaDkf   \n",
       "0   2753  0.495105  Dr Carlvader           0  7qxDNvmecLP9gKR72jHplK   \n",
       "0   2128  0.320534     Kingswell           1  6XTTwEGdZmtIayxqMjYh41   \n",
       "\n",
       "  streaming_country   spotify_genre  \\\n",
       "0          BR|MX|DE     groove room   \n",
       "0          AU|GB|NL     hard trance   \n",
       "0          ES|IT|US  musica andorra   \n",
       "0          MX|GT|US     mexican edm   \n",
       "\n",
       "                                                                                                                                           playlist_tags  \\\n",
       "0  pop|turkish pop|dance|turkish deep house|house|electronic|nu disco|swiss hip hop|groove room|turkish trap pop|brazilian edm|deep uplifting trance|...   \n",
       "0                                                                                                                                                   None   \n",
       "0                                                                                                                                                   None   \n",
       "0                                                                                                                                                   None   \n",
       "\n",
       "                                                                                                                                     spotify_description  \n",
       "0                                                                                                     french dj producer making electronic stuff passion  \n",
       "0              intergalactic dj producer npart lunatic response unit the edison factor acidanimal thunderc nts effect nowner mental health records ltd n  \n",
       "0  as dj producer always trying looking sound style make feel music first single published f me 1997 whole allegation intentions dance floor trance s...  \n",
       "0           francisco reyes mexican dj producer young age played best nightclubs mexico city he working debut upcoming album working singles coming soon  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# spotify_id='7zYOs83aBa0MGKTXjcqeIc'\n",
    "# spotify_id='7zvSBSbWbPBR71rieCbHo0'\n",
    "spotify_id='08zDtD8xQDP3tDApCnxrvY'\n",
    "# spotify_id ='0Cd6nHYwecCNM1sVEXKlYr'\n",
    "spotify_id = '5ivnFTODQHvL7qQ6EqM0rq'\n",
    "# spotify_id = '6SEIIArKE5ncnZ0okl9cZr'\n",
    "spotify_id = '5xIOUIBQhGFX7HIj8lhdyU'\n",
    "\n",
    "\n",
    "response_desc = get_similarity(algo_input_desc_df2, similarity_matrix_desc, indices_desc, spotify_id, top_n=5)\n",
    "response_desc"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74be803c-a195-47bb-9ca3-418199025a49",
   "metadata": {},
   "source": [
    "----"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f73476ef-5724-4b24-bd8c-f17e2a3e60c5",
   "metadata": {},
   "source": [
    "###  Calculate similarity using  Spotify artist genre and descriptions from Chartmetric"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "feb8d631-56db-4b80-b47b-c9836e9c90d0",
   "metadata": {},
   "source": [
    "We take advantage of already cleaned dataframe from previous step"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "2eda7931-51ab-4082-8e93-ec4c7012bce1",
   "metadata": {},
   "outputs": [],
   "source": [
    "algo_input_genr_desc_df = algo_input_desc_df2.copy()\n",
    "algo_input_genr_desc_df['COMBINED'] = algo_input_genr_desc_df['C_GENRES'] + algo_input_genr_desc_df['C_DESCRIPTION']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "f0b98a1d-d518-489f-afac-405c523473d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2845, 327810)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Matrix memory usage: 3.600472 megabytes.\n",
      "Nr of TF IDF features: 327810.\n",
      "First 10 TF IDF features: ['0' '0 following' '0 following 2020' '0 garcia' '0 garcia board'\n",
      " '0 include' '0 include biggest' '0 mayhem' '0 mayhem tormentor' '00'].\n"
     ]
    }
   ],
   "source": [
    "tfidf_genr_desc = TfidfVectorizer(analyzer='word',\n",
    "                      token_pattern=r'\\w{1,}',\n",
    "                      ngram_range=(1, 3), \n",
    "                      smooth_idf = True,\n",
    "                      # max_features = 5000,\n",
    "                      stop_words = 'english')\n",
    "\n",
    "\n",
    "# Fitting the TF-IDF on the 'combo' column\n",
    "tfidf_matrix_genr_desc = tfidf_genr_desc.fit_transform(algo_input_genr_desc_df['COMBINED'])\n",
    "\n",
    "tfidf_matrix_genr_desc.shape\n",
    "print(f\"Matrix memory usage: {tfidf_matrix_genr_desc.data.nbytes / 1000000} megabytes.\")\n",
    "print(f\"Nr of TF IDF features: {len(tfidf_genr_desc.get_feature_names_out())}.\")\n",
    "print(f\"First 10 TF IDF features: {tfidf_genr_desc.get_feature_names_out()[0:10]}.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "ad5f2f64-cc60-4ee5-a496-03c1063bbb80",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Compute the Cosine Similarity\n",
    "similarity_matrix_genr_desc = cosine_similarity(tfidf_matrix_genr_desc, tfidf_matrix_genr_desc)\n",
    "\n",
    "# Create a pandas series with spotify artist id as indices and indices as series values \n",
    "indices_genr_desc = pd.Series(algo_input_genr_desc_df.index, index=algo_input_genr_desc_df['SPOTIFY_ARTIST_ID']).drop_duplicates()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc28f775-95e1-4f58-86bd-0d80d0523c61",
   "metadata": {},
   "source": [
    "Let's pick some generally popular artists for testing."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "f624d188-d8ee-48ea-928c-095f451dc097",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SPOTIFY_ARTIST_ID</th>\n",
       "      <th>C_ARTIST_NAME</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>0gJa9KGO7RabjKfdcgWAOY</td>\n",
       "      <td>Lil Wayne</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1610</th>\n",
       "      <td>5bHCKYEoMjn2KyBDPCZY6y</td>\n",
       "      <td>JAY-Z</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2836</th>\n",
       "      <td>7z7qWp4KfPONqlpiT2HRau</td>\n",
       "      <td>Romeo Santos</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           SPOTIFY_ARTIST_ID C_ARTIST_NAME\n",
       "190   0gJa9KGO7RabjKfdcgWAOY     Lil Wayne\n",
       "1610  5bHCKYEoMjn2KyBDPCZY6y         JAY-Z\n",
       "2836  7z7qWp4KfPONqlpiT2HRau  Romeo Santos"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "algo_input_genr_desc_df[algo_input_genr_desc_df['C_POPULARITY']>75][['SPOTIFY_ARTIST_ID', 'C_ARTIST_NAME']].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "aa98ab6a-5c3d-463a-bdf1-055033dcb7d7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "artist index: 2836.\n",
      "artist name: Romeo Santos.\n",
      "playlist tag: None.\n",
      "top streaming countries:           MX|CL|PE.\n",
      "genres: bachata|latin|tropical\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>score</th>\n",
       "      <th>name</th>\n",
       "      <th>popularity</th>\n",
       "      <th>spotify_id</th>\n",
       "      <th>streaming_country</th>\n",
       "      <th>spotify_genre</th>\n",
       "      <th>playlist_tags</th>\n",
       "      <th>spotify_description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2729</td>\n",
       "      <td>0.101334</td>\n",
       "      <td>Aicelle Santos</td>\n",
       "      <td>29</td>\n",
       "      <td>7oPLWcZnvyxxIrHKC9nbMp</td>\n",
       "      <td>PH|HK|SG</td>\n",
       "      <td>pinoy praise</td>\n",
       "      <td>pop|pop rock|classic opm|para relajarse|mood|r&amp;b/soul|pinoy r&amp;b|pinoy alternative|tagalog worship|dance pop|pinoy rock|pinoy singer-songwriter|seu...</td>\n",
       "      <td>aicelle santos</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1141</td>\n",
       "      <td>0.098331</td>\n",
       "      <td>Isaque Santos</td>\n",
       "      <td>14</td>\n",
       "      <td>3DIWtE6yxan2S4DRgOmRix</td>\n",
       "      <td>BR|US|DE</td>\n",
       "      <td>hinos ccb</td>\n",
       "      <td>musica evangelica instrumental|instrumental|christian</td>\n",
       "      <td>isaque santos</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>190</td>\n",
       "      <td>0.073520</td>\n",
       "      <td>Lil Wayne</td>\n",
       "      <td>84</td>\n",
       "      <td>0gJa9KGO7RabjKfdcgWAOY</td>\n",
       "      <td>US</td>\n",
       "      <td>hip hop|new orleans rap|pop|pop rap|rap|trap music</td>\n",
       "      <td>None</td>\n",
       "      <td>lil wayne began career near novelty preteen delivering hardcore southern hip hop through years maturation prolific output delivery humorous wordpl...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>798</td>\n",
       "      <td>0.072496</td>\n",
       "      <td>Ricky Martin</td>\n",
       "      <td>73</td>\n",
       "      <td>1ldgVwiqlcZRD7OF8pTAgT</td>\n",
       "      <td>MX|CL|AR</td>\n",
       "      <td>dance pop|latin|latin pop|mexican pop|tropical</td>\n",
       "      <td>None</td>\n",
       "      <td>one biggest latin artists time ricky martin globally recognized singer actor known sophisticated high energy brand pop martin initially gained fam...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1636</td>\n",
       "      <td>0.072215</td>\n",
       "      <td>Cosculluela</td>\n",
       "      <td>70</td>\n",
       "      <td>5ggGbZcS14aEMQdv8MrEFP</td>\n",
       "      <td>CL|MX|AR</td>\n",
       "      <td>latin|latin hip hop|reggaeton|reggaeton flow|tropical</td>\n",
       "      <td>None</td>\n",
       "      <td>puerto rico s cosculluela rapper known infectious blend latin trap hip hop reggaeton sounds he broke 2009 debut el principe topped billboard latin...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index     score            name  popularity              spotify_id  \\\n",
       "0   2729  0.101334  Aicelle Santos          29  7oPLWcZnvyxxIrHKC9nbMp   \n",
       "0   1141  0.098331   Isaque Santos          14  3DIWtE6yxan2S4DRgOmRix   \n",
       "0    190  0.073520       Lil Wayne          84  0gJa9KGO7RabjKfdcgWAOY   \n",
       "0    798  0.072496    Ricky Martin          73  1ldgVwiqlcZRD7OF8pTAgT   \n",
       "0   1636  0.072215     Cosculluela          70  5ggGbZcS14aEMQdv8MrEFP   \n",
       "\n",
       "  streaming_country                                          spotify_genre  \\\n",
       "0          PH|HK|SG                                           pinoy praise   \n",
       "0          BR|US|DE                                              hinos ccb   \n",
       "0                US     hip hop|new orleans rap|pop|pop rap|rap|trap music   \n",
       "0          MX|CL|AR         dance pop|latin|latin pop|mexican pop|tropical   \n",
       "0          CL|MX|AR  latin|latin hip hop|reggaeton|reggaeton flow|tropical   \n",
       "\n",
       "                                                                                                                                           playlist_tags  \\\n",
       "0  pop|pop rock|classic opm|para relajarse|mood|r&b/soul|pinoy r&b|pinoy alternative|tagalog worship|dance pop|pinoy rock|pinoy singer-songwriter|seu...   \n",
       "0                                                                                                  musica evangelica instrumental|instrumental|christian   \n",
       "0                                                                                                                                                   None   \n",
       "0                                                                                                                                                   None   \n",
       "0                                                                                                                                                   None   \n",
       "\n",
       "                                                                                                                                     spotify_description  \n",
       "0                                                                                                                                         aicelle santos  \n",
       "0                                                                                                                                          isaque santos  \n",
       "0  lil wayne began career near novelty preteen delivering hardcore southern hip hop through years maturation prolific output delivery humorous wordpl...  \n",
       "0  one biggest latin artists time ricky martin globally recognized singer actor known sophisticated high energy brand pop martin initially gained fam...  \n",
       "0  puerto rico s cosculluela rapper known infectious blend latin trap hip hop reggaeton sounds he broke 2009 debut el principe topped billboard latin...  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spotify_id='5wW7idUzEz5cMhYnkLBaXM' # Eric Clapton\n",
    "spotify_id='2N7QoTe9hOcnrxgcmid4cm' # U2\n",
    "spotify_id='7z7qWp4KfPONqlpiT2HRau' # Romeo Santos\n",
    "# spotify_id='0wcwd9rVgYgvbSBOlxZRc9' # Tiësto\n",
    "\n",
    "response_genr_genr_desc = get_similarity(algo_input_genr_desc_df, similarity_matrix_genr_desc, indices_genr_desc, \\\n",
    "                                         spotify_id, top_n=5)\n",
    "response_genr_genr_desc"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b6bc5a9-bb8b-4ce5-92db-f22b111ce368",
   "metadata": {},
   "source": [
    "It seems that variation is not good enough as similar names pop up although using artists from different genres."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dffae91d-53a8-433f-87b8-a167fd7c5e99",
   "metadata": {},
   "source": [
    "### Calculate similarity using  Spotify artist genres and top streaming locations from Chartmetric"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "6c601510-f3fb-476c-abdd-9d1a831b9c35",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 2160x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "chartmetric_df.groupby(['C_FAN_COUNTRY_CODE'])['SPOTIFY_ARTIST_ID'].count()[lambda x: x>300].\\\n",
    "                                        sort_values(ascending=False).plot.bar(color = '#A60628',\n",
    "                                        figsize = (30,6),title='Most popular country combinations');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3a96d603-6662-4764-be80-ba60f37dc448",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/0s/dzb0jp112ps6m353xzh_67br0000gn/T/ipykernel_78711/3250598070.py:3: FutureWarning: The default value of regex will change from True to False in a future version. In addition, single character regular expressions will *not* be treated as literal strings when regex=True.\n",
      "  tfidf_matrix = tf.fit_transform(chartmetric_df['C_FAN_COUNTRY_CODE'].str.replace(\"|\", \" \"))\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Converting text descriptions into vectors using TF-IDF using Bigram\n",
    "tf = TfidfVectorizer(ngram_range=(1, 1), stop_words='english', lowercase = False)\n",
    "tfidf_matrix = tf.fit_transform(chartmetric_df['C_FAN_COUNTRY_CODE'].str.replace(\"|\", \" \"))\n",
    "total_words = tfidf_matrix.sum(axis=0) \n",
    "#Finding the word frequency\n",
    "freq = [(word, total_words[0, idx]) for word, idx in tf.vocabulary_.items()]\n",
    "freq =sorted(freq, key = lambda x: x[1], reverse=True)\n",
    "#converting into dataframe \n",
    "bigram = pd.DataFrame(freq)\n",
    "bigram.rename(columns = {0:'bigram', 1: 'count'}, inplace = True) \n",
    "#Taking first 20 records\n",
    "bigram = bigram.head(20)\n",
    "\n",
    "#Plotting the bigram distribution\n",
    "bigram.plot(x ='bigram', y='count', kind = 'bar', \n",
    "            title = \"Top 20 countries fan come from\", figsize = (15,7), );"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f62c40c5-2022-4bee-a255-5ece0bb9cfb7",
   "metadata": {},
   "source": [
    "Combine genre and countries together"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "43b2c2b5-6c16-4440-b602-fbc8319f9389",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    deep pop r&b NL US GB\n",
       "1           drama AU GR DE\n",
       "Name: COMBINED, dtype: object"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "(72334, 77240)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Matrix memory usage: 6.264624 megabytes.\n",
      "Nr of TF IDF features: 77240.\n",
      "First 10 TF IDF features: ['150' '150 bpm' '150 bpm br' '21st' '21st century'\n",
      " '21st century classical' '432hz' '432hz au' '432hz au br' '432hz au ca'].\n"
     ]
    }
   ],
   "source": [
    "tfidf_location = TfidfVectorizer(analyzer='word',\n",
    "                      token_pattern=r'\\w{1,}',\n",
    "                      ngram_range=(1, 3), \n",
    "                      stop_words = 'english')\n",
    "\n",
    "algo_input_loc_df = chartmetric_df.copy()\n",
    "algo_input_loc_df['C_GENRES'] =  algo_input_loc_df['C_GENRES'].fillna('')\n",
    "algo_input_loc_df['C_GENRES'] = algo_input_loc_df['C_GENRES'].apply(replace_straight_with_space)\n",
    "algo_input_loc_df['C_FAN_COUNTRY_CODE'] = algo_input_loc_df['C_FAN_COUNTRY_CODE'].apply(replace_straight_with_space)\n",
    "algo_input_loc_df['COMBINED'] = algo_input_loc_df['C_GENRES'] + ' ' + algo_input_loc_df['C_FAN_COUNTRY_CODE']\n",
    "algo_input_loc_df['COMBINED'].head(2)\n",
    "\n",
    "# Fitting the TF-IDF on the 'genre and streaming countries' columns\n",
    "tfidf_matrix_loc = tfidf_location.fit_transform(algo_input_loc_df['COMBINED'])\n",
    "\n",
    "tfidf_matrix_loc.shape\n",
    "print(f\"Matrix memory usage: {tfidf_matrix_loc.data.nbytes / 1000000} megabytes.\")\n",
    "print(f\"Nr of TF IDF features: {len(tfidf_location.get_feature_names_out())}.\")\n",
    "print(f\"First 10 TF IDF features: {tfidf_location.get_feature_names_out()[0:10]}.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "16a25e62-ebf6-4570-a6aa-522d8227592d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.        , 0.        , 0.        , ..., 0.02102725, 0.01285819,\n",
       "       0.01212227])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Similarity matrix with float16 memory usage: 10464.415112 megabytes.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([1.   , 0.   , 0.   , ..., 0.021, 0.013, 0.012], dtype=float16)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Similarity matrix memory usage: 10464.415112 megabytes.\n"
     ]
    }
   ],
   "source": [
    "# Compute the Cosine Similarity\n",
    "similarity_matrix_loc = cosine_similarity(tfidf_matrix_loc, tfidf_matrix_loc)\n",
    "similarity_matrix_loc[0]\n",
    "# convert to float16\n",
    "similarity_matrix_loc = np.round_(similarity_matrix_loc, decimals = 3)\n",
    "similarity_matrix_loc = similarity_matrix_loc.astype(np.float16)\n",
    "print(f\"Similarity matrix with float16 memory usage: {similarity_matrix_loc.data.nbytes / 1000000} megabytes.\")\n",
    "similarity_matrix_loc[0]\n",
    "print(f\"Similarity matrix memory usage: {similarity_matrix_loc.data.nbytes / 1000000} megabytes.\")\n",
    "\n",
    "# Create a pandas series with spotify artist id as indices and indices as series values \n",
    "indices_loc = pd.Series(algo_input_loc_df.index, index=algo_input_loc_df['SPOTIFY_ARTIST_ID']).drop_duplicates()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9c33576-a644-46a3-a408-edde62add863",
   "metadata": {},
   "source": [
    "<b><i>Use next steps if you want to include only top X artists based on similarity matrix. This will greatly reduce\n",
    "file sizes required to move to the Streamlit server</i></b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "53607647-eb0c-4d17-9c5c-65e3b9a948b3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(72334, 10)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "array([50739, 62830,  6250, 21672, 18748, 12861, 69278, 35312, 34119,\n",
       "           0])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "(72334, 10)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "array([0.589, 0.614, 0.614, 0.614, 0.614, 0.614, 0.614, 0.684, 0.722,\n",
       "       1.   ], dtype=float16)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "top x only matrix memory usage: 5.78672 megabytes.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(72334, 10)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "top x  only matrix values memory usage: 1.44668 megabytes.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(72334, 10)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n = 10 # nr of artists to keep\n",
    "indices_loc_ = pd.Series(algo_input_loc_df.index, index=algo_input_loc_df['SPOTIFY_ARTIST_ID']).drop_duplicates()\n",
    "\n",
    "# compression\n",
    "top_matches_loc_array = np.argsort(similarity_matrix_loc)[:, -n:]\n",
    "top_matches_loc_array.shape\n",
    "top_matches_loc_array[0]\n",
    "\n",
    "top_matches_loc_scores = similarity_matrix_loc[np.expand_dims(np.arange(similarity_matrix_loc.shape[0]), -1), top_matches_loc_array]\n",
    "top_matches_loc_scores.shape\n",
    "top_matches_loc_scores[0]\n",
    "\n",
    "print(f\"top x only matrix memory usage: {top_matches_loc_array.data.nbytes / 1000000} megabytes.\")\n",
    "top_matches_loc_array.shape\n",
    "print(f\"top x  only matrix values memory usage: {top_matches_loc_scores.data.nbytes / 1000000} megabytes.\")\n",
    "top_matches_loc_scores.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "5055d22e-e10d-4d75-a273-2513e0ecd981",
   "metadata": {},
   "outputs": [],
   "source": [
    "np.save('pickles/top_matches_loc_array.npy', top_matches_loc_array)\n",
    "np.save('pickles/top_matches_loc_scores.npy', top_matches_loc_scores)\n",
    "indices_loc_.to_pickle('pickles/indices_loc_.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "a7ddbc38-b63d-4f25-b89c-996ce3693659",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Spotify id: 6iTD167bhyfYwEd7fd2bGn.\n",
      "artist name: Sugar Minott.\n",
      "top streaming countries: GB NZ AU.\n",
      "genres: dub lovers rock old school dancehall reggae rock steady roots reggae\n",
      "------------\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>score</th>\n",
       "      <th>name</th>\n",
       "      <th>popularity</th>\n",
       "      <th>spotify_id</th>\n",
       "      <th>streaming_country</th>\n",
       "      <th>spotify_genre</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>63482</td>\n",
       "      <td>0.911133</td>\n",
       "      <td>Johnny Osbourne</td>\n",
       "      <td>44</td>\n",
       "      <td>5TUTGRG0FlRoYTZ4GEdOVO</td>\n",
       "      <td>GB US BR</td>\n",
       "      <td>dub lovers rock old school dancehall reggae rock steady roots reggae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>38184</td>\n",
       "      <td>0.698242</td>\n",
       "      <td>Michael Prophet</td>\n",
       "      <td>29</td>\n",
       "      <td>2qUfyLUGgzdl230mYZsu82</td>\n",
       "      <td>GB US BR</td>\n",
       "      <td>dub lovers rock old school dancehall reggae roots reggae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4165</td>\n",
       "      <td>0.695801</td>\n",
       "      <td>Yellowman</td>\n",
       "      <td>47</td>\n",
       "      <td>6yTNMMqumesCWhMJ47HB2a</td>\n",
       "      <td>US GB MX</td>\n",
       "      <td>dub lovers rock old school dancehall reggae roots reggae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>41999</td>\n",
       "      <td>0.633789</td>\n",
       "      <td>Freddie McGregor</td>\n",
       "      <td>46</td>\n",
       "      <td>30R9paG1c5BGtNGle59VPq</td>\n",
       "      <td>US GB CA</td>\n",
       "      <td>dub lovers rock reggae rock steady roots reggae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>55329</td>\n",
       "      <td>0.628906</td>\n",
       "      <td>U-Roy</td>\n",
       "      <td>46</td>\n",
       "      <td>4aCH6cwaYahrWfJWqfEfra</td>\n",
       "      <td>US GB BR</td>\n",
       "      <td>dub lovers rock reggae rock steady roots reggae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>29879</td>\n",
       "      <td>0.628906</td>\n",
       "      <td>Big Youth</td>\n",
       "      <td>42</td>\n",
       "      <td>2TdzGitZtbe3Zw3BB4SFEH</td>\n",
       "      <td>US GB BR</td>\n",
       "      <td>dub lovers rock reggae rock steady roots reggae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>21733</td>\n",
       "      <td>0.620117</td>\n",
       "      <td>Frankie Paul</td>\n",
       "      <td>37</td>\n",
       "      <td>1J4CDjVHn8ummXVmJ7Q73u</td>\n",
       "      <td>GB US CA</td>\n",
       "      <td>deep ragga dub lovers rock old school dancehall reggae roots reggae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8356</td>\n",
       "      <td>0.567871</td>\n",
       "      <td>Super Cat</td>\n",
       "      <td>41</td>\n",
       "      <td>7hHDN8REbPLpv46ROortOM</td>\n",
       "      <td>US GB CA</td>\n",
       "      <td>dancehall lovers rock old school dancehall reggae fusion roots reggae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>45017</td>\n",
       "      <td>0.563965</td>\n",
       "      <td>Bunny Wailer</td>\n",
       "      <td>52</td>\n",
       "      <td>389zc5Rwe0MPcE6mSF4AjC</td>\n",
       "      <td>US BR GB</td>\n",
       "      <td>dub lovers rock reggae rock steady roots reggae</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index     score              name  popularity              spotify_id  \\\n",
       "0  63482  0.911133   Johnny Osbourne          44  5TUTGRG0FlRoYTZ4GEdOVO   \n",
       "0  38184  0.698242   Michael Prophet          29  2qUfyLUGgzdl230mYZsu82   \n",
       "0   4165  0.695801         Yellowman          47  6yTNMMqumesCWhMJ47HB2a   \n",
       "0  41999  0.633789  Freddie McGregor          46  30R9paG1c5BGtNGle59VPq   \n",
       "0  55329  0.628906             U-Roy          46  4aCH6cwaYahrWfJWqfEfra   \n",
       "0  29879  0.628906         Big Youth          42  2TdzGitZtbe3Zw3BB4SFEH   \n",
       "0  21733  0.620117      Frankie Paul          37  1J4CDjVHn8ummXVmJ7Q73u   \n",
       "0   8356  0.567871         Super Cat          41  7hHDN8REbPLpv46ROortOM   \n",
       "0  45017  0.563965      Bunny Wailer          52  389zc5Rwe0MPcE6mSF4AjC   \n",
       "\n",
       "  streaming_country  \\\n",
       "0          GB US BR   \n",
       "0          GB US BR   \n",
       "0          US GB MX   \n",
       "0          US GB CA   \n",
       "0          US GB BR   \n",
       "0          US GB BR   \n",
       "0          GB US CA   \n",
       "0          US GB CA   \n",
       "0          US BR GB   \n",
       "\n",
       "                                                           spotify_genre  \n",
       "0   dub lovers rock old school dancehall reggae rock steady roots reggae  \n",
       "0               dub lovers rock old school dancehall reggae roots reggae  \n",
       "0               dub lovers rock old school dancehall reggae roots reggae  \n",
       "0                        dub lovers rock reggae rock steady roots reggae  \n",
       "0                        dub lovers rock reggae rock steady roots reggae  \n",
       "0                        dub lovers rock reggae rock steady roots reggae  \n",
       "0    deep ragga dub lovers rock old school dancehall reggae roots reggae  \n",
       "0  dancehall lovers rock old school dancehall reggae fusion roots reggae  \n",
       "0                        dub lovers rock reggae rock steady roots reggae  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spotify_id = '6Tg5wgFNHcQhNPK5zrFC34'\n",
    "spotify_id = '6iTD167bhyfYwEd7fd2bGn'\n",
    "#spotify_id = '6TfJcKCr5hFsYZkq2k1Pac'\n",
    "#spotify_id = '7N026dv4AShbedLUEwAQkN'\n",
    "\n",
    "get_limited_similarity(algo_input_loc_df, top_matches_loc_array, top_matches_loc_scores, indices_loc_, spotify_id)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d862f55d-44ba-45e1-9ba1-a2fb6a7bb041",
   "metadata": {},
   "source": [
    "Prepare objects for usage in Streamlit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "b8802425-2a6e-424e-80f9-040606b3d2f3",
   "metadata": {},
   "outputs": [],
   "source": [
    "algo_input_loc_df.to_parquet('pickles/algo_input_loc_df_for_pickle.parquet', compression='brotli')\n",
    "np.save('pickles/similarity_matrix_loc_for_pickle.npy', similarity_matrix_loc)\n",
    "indices_loc.to_pickle('pickles/indices_loc_for_pickle.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "a5c8112c-3c1b-48f2-8c9e-17f45a9a021b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "What artist are you looking for? romeo\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "romeo\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>SPOTIFY_ARTIST_ID</th>\n",
       "      <th>C_ARTIST_NAME</th>\n",
       "      <th>C_POPULARITY</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>7z7qWp4KfPONqlpiT2HRau</td>\n",
       "      <td>Romeo Santos</td>\n",
       "      <td>78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5uMjqoel4FkBf3DCIltfXv</td>\n",
       "      <td>Oh Romeo</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "while True:\n",
    "    artist_name = input(\"What artist are you looking for?\")\n",
    "    artist_name = artist_name.lower()\n",
    "    print(artist_name)\n",
    "    algo_input_loc_df['search_string'] = algo_input_loc_df['C_ARTIST_NAME'].str.lower()\n",
    "    HTML(algo_input_loc_df[algo_input_loc_df['search_string'].str.contains(artist_name)][['SPOTIFY_ARTIST_ID', 'C_ARTIST_NAME', 'C_POPULARITY']].sort_values(by=['C_POPULARITY'],ascending=False).head().to_html(index=False))\n",
    "    algo_input_loc_df = algo_input_loc_df.drop(['search_string'], axis=1)\n",
    "    break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "78d561e1-31af-4027-b1d8-ae3e4bf3278b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "artist index: 5174.\n",
      "artist name: Romeo Santos.\n",
      "playlist tag: None.\n",
      "top streaming countries:           MX CL PE.\n",
      "genres: bachata latin tropical\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "      <th>index</th>\n",
       "      <th>score</th>\n",
       "      <th>name</th>\n",
       "      <th>popularity</th>\n",
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       "      <th>streaming_country</th>\n",
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       "      <th>playlist_tags</th>\n",
       "      <th>spotify_description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2563</td>\n",
       "      <td>0.322998</td>\n",
       "      <td>Reyli Barba</td>\n",
       "      <td>62</td>\n",
       "      <td>48MORJDbm27MVNWZ4l7gHD</td>\n",
       "      <td>MX CL PE</td>\n",
       "      <td>grupera latin latin pop mexican pop ranchera rock en espanol tropical</td>\n",
       "      <td>None</td>\n",
       "      <td>after making name singer mexican alt rock act elefante singer songwriter reyli barba left band 2003 pursue solo career barba quickly remade romant...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1804</td>\n",
       "      <td>0.297119</td>\n",
       "      <td>24 Horas</td>\n",
       "      <td>42</td>\n",
       "      <td>27Wx39r2tON2FxS93iJhUC</td>\n",
       "      <td>US CL ES</td>\n",
       "      <td>bachata latin orquesta tropical tropical</td>\n",
       "      <td>None</td>\n",
       "      <td>their new album tiempo mark return already two singles aun me perteneces reached top 10 billboard tropical airplay chart por tu culpa reached 1 bi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1531</td>\n",
       "      <td>0.260986</td>\n",
       "      <td>Ricky Martin</td>\n",
       "      <td>73</td>\n",
       "      <td>1ldgVwiqlcZRD7OF8pTAgT</td>\n",
       "      <td>MX CL AR</td>\n",
       "      <td>dance pop latin latin pop mexican pop tropical</td>\n",
       "      <td>None</td>\n",
       "      <td>one biggest latin artists time ricky martin globally recognized singer actor known sophisticated high energy brand pop martin initially gained fam...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1880</td>\n",
       "      <td>0.260986</td>\n",
       "      <td>Gaby Vega</td>\n",
       "      <td>15</td>\n",
       "      <td>2DK7TEKTzNRdpuRHZX55p8</td>\n",
       "      <td>MX CL PE</td>\n",
       "      <td>anime latino</td>\n",
       "      <td>soundtrack|latin|anime latino|children's music|scorecore|otacore</td>\n",
       "      <td>la pelirosa dj playboy nutricionista de profesin ninicio su carrera musical muy pequea la pelirosa con 22 aos de edad es una modelo cantante que p...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4918</td>\n",
       "      <td>0.239990</td>\n",
       "      <td>Niños Cantores</td>\n",
       "      <td>30</td>\n",
       "      <td>7iN2fFK6ivogemmYPp5inf</td>\n",
       "      <td>MX CL PE</td>\n",
       "      <td>musica para ninos</td>\n",
       "      <td>latin|nueva cancion|childrens story|musica para ninos|latin rock|latino|children's music|cancion infantil latinoamericana</td>\n",
       "      <td>nios cantores</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index     score            name  popularity              spotify_id  \\\n",
       "0   2563  0.322998     Reyli Barba          62  48MORJDbm27MVNWZ4l7gHD   \n",
       "0   1804  0.297119        24 Horas          42  27Wx39r2tON2FxS93iJhUC   \n",
       "0   1531  0.260986    Ricky Martin          73  1ldgVwiqlcZRD7OF8pTAgT   \n",
       "0   1880  0.260986       Gaby Vega          15  2DK7TEKTzNRdpuRHZX55p8   \n",
       "0   4918  0.239990  Niños Cantores          30  7iN2fFK6ivogemmYPp5inf   \n",
       "\n",
       "  streaming_country  \\\n",
       "0          MX CL PE   \n",
       "0          US CL ES   \n",
       "0          MX CL AR   \n",
       "0          MX CL PE   \n",
       "0          MX CL PE   \n",
       "\n",
       "                                                           spotify_genre  \\\n",
       "0  grupera latin latin pop mexican pop ranchera rock en espanol tropical   \n",
       "0                               bachata latin orquesta tropical tropical   \n",
       "0                         dance pop latin latin pop mexican pop tropical   \n",
       "0                                                           anime latino   \n",
       "0                                                      musica para ninos   \n",
       "\n",
       "                                                                                                               playlist_tags  \\\n",
       "0                                                                                                                       None   \n",
       "0                                                                                                                       None   \n",
       "0                                                                                                                       None   \n",
       "0                                                           soundtrack|latin|anime latino|children's music|scorecore|otacore   \n",
       "0  latin|nueva cancion|childrens story|musica para ninos|latin rock|latino|children's music|cancion infantil latinoamericana   \n",
       "\n",
       "                                                                                                                                     spotify_description  \n",
       "0  after making name singer mexican alt rock act elefante singer songwriter reyli barba left band 2003 pursue solo career barba quickly remade romant...  \n",
       "0  their new album tiempo mark return already two singles aun me perteneces reached top 10 billboard tropical airplay chart por tu culpa reached 1 bi...  \n",
       "0  one biggest latin artists time ricky martin globally recognized singer actor known sophisticated high energy brand pop martin initially gained fam...  \n",
       "0  la pelirosa dj playboy nutricionista de profesin ninicio su carrera musical muy pequea la pelirosa con 22 aos de edad es una modelo cantante que p...  \n",
       "0                                                                                                                                          nios cantores  "
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spotify_id='1ouOm2gd2sdGJC97nn9Cmw' # Tiësto\n",
    "#spotify_id='5wW7idUzEz5cMhYnkLBaXM' # Eric Clapton\n",
    "# spotify_id='2N7QoTe9hOcnrxgcmid4cm' # U2\n",
    "# spotify_id='7FLs9YLk4hUvPe3nU01E1S' # Akon\n",
    "\n",
    "# spotify_id='7zYOs83aBa0MGKTXjcqeIc'\n",
    "# spotify_id='7zvSBSbWbPBR71rieCbHo0'\n",
    "spotify_id='0wcwd9rVgYgvbSBOlxZRc9'\n",
    "# spotify_id = '0Cd6nHYwecCNM1sVEXKlYr'\n",
    "spotify_id = '7z7qWp4KfPONqlpiT2HRau'\n",
    "\n",
    "\n",
    "response_loc = get_similarity(algo_input_loc_df, similarity_matrix_loc, indices_loc, \\\n",
    "                                         spotify_id, top_n=5)\n",
    "response_loc"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9e7515e-89bb-473a-ad17-ef3f6d53368a",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Compare pure genre approach with genre + location approach"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "85784b77-1fa2-4958-88eb-a2171369e4f9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "artist index: 5174.\n",
      "artist name: Romeo Santos.\n",
      "top streaming ountries: MX|CL|PE.\n",
      "genres: bachata latin tropical\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>first_score</th>\n",
       "      <th>artist_name</th>\n",
       "      <th>artist_popularity</th>\n",
       "      <th>artist_genre</th>\n",
       "      <th>second_score</th>\n",
       "      <th>artist_name</th>\n",
       "      <th>artist_popularity</th>\n",
       "      <th>artist_genre</th>\n",
       "      <th>streaming_countries</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.464111</td>\n",
       "      <td>24 Horas</td>\n",
       "      <td>42</td>\n",
       "      <td>bachata latin orquesta tropical tropical</td>\n",
       "      <td>0.322998</td>\n",
       "      <td>Reyli Barba</td>\n",
       "      <td>62</td>\n",
       "      <td>grupera latin latin pop mexican pop ranchera rock en espanol tropical</td>\n",
       "      <td>MX CL PE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.165039</td>\n",
       "      <td>Ricky Martin</td>\n",
       "      <td>73</td>\n",
       "      <td>dance pop latin latin pop mexican pop tropical</td>\n",
       "      <td>0.297119</td>\n",
       "      <td>24 Horas</td>\n",
       "      <td>42</td>\n",
       "      <td>bachata latin orquesta tropical tropical</td>\n",
       "      <td>US CL ES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.154053</td>\n",
       "      <td>Cosculluela</td>\n",
       "      <td>70</td>\n",
       "      <td>latin latin hip hop reggaeton reggaeton flow tropical</td>\n",
       "      <td>0.260986</td>\n",
       "      <td>Ricky Martin</td>\n",
       "      <td>73</td>\n",
       "      <td>dance pop latin latin pop mexican pop tropical</td>\n",
       "      <td>MX CL AR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.154053</td>\n",
       "      <td>José Bragato</td>\n",
       "      <td>3</td>\n",
       "      <td>latin classical</td>\n",
       "      <td>0.260986</td>\n",
       "      <td>Gaby Vega</td>\n",
       "      <td>15</td>\n",
       "      <td>anime latino</td>\n",
       "      <td>MX CL PE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.154053</td>\n",
       "      <td>João Guilherme Ripper</td>\n",
       "      <td>0</td>\n",
       "      <td>latin classical</td>\n",
       "      <td>0.239990</td>\n",
       "      <td>Niños Cantores</td>\n",
       "      <td>30</td>\n",
       "      <td>musica para ninos</td>\n",
       "      <td>MX CL PE</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   first_score            artist_name  artist_popularity  \\\n",
       "0     0.464111               24 Horas                 42   \n",
       "0     0.165039           Ricky Martin                 73   \n",
       "0     0.154053            Cosculluela                 70   \n",
       "0     0.154053           José Bragato                  3   \n",
       "0     0.154053  João Guilherme Ripper                  0   \n",
       "\n",
       "                                            artist_genre  second_score  \\\n",
       "0               bachata latin orquesta tropical tropical      0.322998   \n",
       "0         dance pop latin latin pop mexican pop tropical      0.297119   \n",
       "0  latin latin hip hop reggaeton reggaeton flow tropical      0.260986   \n",
       "0                                        latin classical      0.260986   \n",
       "0                                        latin classical      0.239990   \n",
       "\n",
       "      artist_name  artist_popularity  \\\n",
       "0     Reyli Barba                 62   \n",
       "0        24 Horas                 42   \n",
       "0    Ricky Martin                 73   \n",
       "0       Gaby Vega                 15   \n",
       "0  Niños Cantores                 30   \n",
       "\n",
       "                                                            artist_genre  \\\n",
       "0  grupera latin latin pop mexican pop ranchera rock en espanol tropical   \n",
       "0                               bachata latin orquesta tropical tropical   \n",
       "0                         dance pop latin latin pop mexican pop tropical   \n",
       "0                                                           anime latino   \n",
       "0                                                      musica para ninos   \n",
       "\n",
       "  streaming_countries  \n",
       "0            MX CL PE  \n",
       "0            US CL ES  \n",
       "0            MX CL AR  \n",
       "0            MX CL PE  \n",
       "0            MX CL PE  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spotify_id_for_comp = '0Cd6nHYwecCNM1sVEXKlYr'\n",
    "spotify_id_for_comp = '5wW7idUzEz5cMhYnkLBaXM' # eric clapton\n",
    "spotify_id_for_comp = '5ivnFTODQHvL7qQ6EqM0rq' # Epica\n",
    "spotify_id_for_comp = '7z7qWp4KfPONqlpiT2HRau'\n",
    "\n",
    "r_ = compare_similarity_approaches(algo_input_df, algo_input_loc_df, similarity_matrix, similarity_matrix_loc, indices, indices_loc, spotify_id_for_comp, 5)\n",
    "r_"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c45c8386-f8e1-41b3-99d8-54daf97ba8b3",
   "metadata": {},
   "source": [
    "----"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0677718-121a-4908-af9b-6fcf81e7f2f2",
   "metadata": {},
   "source": [
    "### Find similar artists using genre + location data +  playlist tags data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "750d5206-9e00-47a5-9ea3-2a51b6ca7ef0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                        musica antigua ES US FR contemporary jazz audiophile vocal classical\n",
       "1                                 cantautor DE ES GB chill lounge singer/songwriter cantautor\n",
       "2    british comedy AU GB US latin arena pop spoken word latino deep comedy british hollywood\n",
       "Name: COMBINED, dtype: object"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tags_input_df = chartmetric_df[~chartmetric_df['C_TAG_NAME'].isna()].copy().reset_index()\n",
    "tags_input_df['C_TAG_NAME'] = tags_input_df['C_TAG_NAME'].apply(replace_straight_with_space)\n",
    "tags_input_df['C_TAG_NAME'] = tags_input_df['C_TAG_NAME'].apply(remove_duplicates_from_cell)\n",
    "tags_input_df['C_FAN_COUNTRY_CODE'] = tags_input_df['C_FAN_COUNTRY_CODE'].apply(replace_straight_with_space)\n",
    "\n",
    "tags_input_df['COMBINED'] = tags_input_df['C_GENRES'] + ' ' + tags_input_df['C_FAN_COUNTRY_CODE'] + ' ' + tags_input_df['C_TAG_NAME']\n",
    "tags_input_df['COMBINED'].head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "786864a0-7f84-46ed-9d39-98463e0ee484",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1414, 1900)"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Matrix memory usage: 0.19732 megabytes.\n",
      "Nr of TF IDF features: 1900.\n",
      "First 10 TF IDF features: ['150' '21st' '420' '432hz' '8d' 'abc' 'abstract' 'accordeon' 'accordion'\n",
      " 'acid'].\n"
     ]
    }
   ],
   "source": [
    "tfidf_tags = TfidfVectorizer(analyzer='word',\n",
    "                      token_pattern=r'\\w{1,}',\n",
    "                      ngram_range=(1, 1), # 1,3 \n",
    "                      stop_words = 'english')\n",
    "\n",
    "# Fitting the TF-IDF on the genres\n",
    "tfidf_matrix_tags = tfidf_tags.fit_transform(tags_input_df['COMBINED'])\n",
    "\n",
    "tfidf_matrix_tags.shape\n",
    "print(f\"Matrix memory usage: {tfidf_matrix_tags.data.nbytes / 1000000} megabytes.\")\n",
    "print(f\"Nr of TF IDF features: {len(tfidf_tags.get_feature_names_out())}.\")\n",
    "print(f\"First 10 TF IDF features: {tfidf_tags.get_feature_names_out()[0:10]}.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "44c086a8-c5c8-4550-a204-84271b6fdb9e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.        , 0.06145313, 0.        , ..., 0.        , 0.        ,\n",
       "       0.04300527])"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Similarity matrix with float16 memory usage: 3.998792 megabytes.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([1.   , 0.061, 0.   , ..., 0.   , 0.   , 0.043], dtype=float16)"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Compute the Cosine Similarity\n",
    "similarity_matrix_tag = cosine_similarity(tfidf_matrix_tags, tfidf_matrix_tags)\n",
    "similarity_matrix_tag[0]\n",
    "\n",
    "# convert to float16\n",
    "similarity_matrix_tag = np.round_(similarity_matrix_tag, decimals = 3)\n",
    "similarity_matrix_tag = similarity_matrix_tag.astype(np.float16)\n",
    "print(f\"Similarity matrix with float16 memory usage: {similarity_matrix_tag.data.nbytes / 1000000} megabytes.\")\n",
    "similarity_matrix_tag[0]\n",
    "\n",
    "\n",
    "# Create a pandas series with spotify artist id as indices and indices as series values \n",
    "indices_tag = pd.Series(tags_input_df.index, index=tags_input_df['SPOTIFY_ARTIST_ID']).drop_duplicates()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89dd71fe-b64f-4456-b712-02acd14a8d45",
   "metadata": {},
   "source": [
    "Prepare objects for usage in Streamlit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "f35fbd8a-645a-48c8-ae81-66acdf602a52",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<HDF5 dataset \"dataset_1\": shape (21012, 21012), type \"<f8\">"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# import h5py\n",
    "# hf = h5py.File('pickles/similarity_matrix_tag_for_pickle.h5', 'w')\n",
    "# hf.create_dataset('dataset_1', data=similarity_matrix_tag, compression=\"gzip\")\n",
    "# hf.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "ee4c14ff-3dec-427c-b0a1-edc910acb3e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# hf2 = h5py.File('pickles/similarity_matrix_tag_for_pickle.h5', 'r')\n",
    "# n1 = hf2.get('dataset_1')\n",
    "# n1 = np.array(n1)\n",
    "# n1.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "b851e541-1e64-49a9-9e3a-c29545e07c54",
   "metadata": {},
   "outputs": [],
   "source": [
    "tags_input_df.to_pickle('pickles/tags_input_df_for_pickle.pkl')\n",
    "np.save('pickles/similarity_matrix_tag_for_pickle.npy', similarity_matrix_tag)\n",
    "indices_tag.to_pickle('pickles/indices_tag_for_pickle.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "e1b44538-1657-4392-8bd8-4f41e66f019e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "What artist are you looking for? bab\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "bab\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>SPOTIFY_ARTIST_ID</th>\n",
       "      <th>C_ARTIST_NAME</th>\n",
       "      <th>C_POPULARITY</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>76bgYMdQ7UYnUad5NiyE6v</td>\n",
       "      <td>Lullaby Baby Trio</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1Xah6FnJ2N7gEeI5mbvMvC</td>\n",
       "      <td>Baby S</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "while True:\n",
    "    artist_name = input(\"What artist are you looking for?\")\n",
    "    artist_name = artist_name.lower()\n",
    "    print(artist_name)\n",
    "    tags_input_df['search_string'] = tags_input_df['C_ARTIST_NAME'].str.lower()\n",
    "    HTML(tags_input_df[tags_input_df['search_string'].str.contains(artist_name)][['SPOTIFY_ARTIST_ID', 'C_ARTIST_NAME', 'C_POPULARITY']].sort_values(by=['C_POPULARITY'],ascending=False).head().to_html(index=False))\n",
    "    tags_input_df = tags_input_df.drop(['search_string'], axis=1)\n",
    "    break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "7b2824e1-850d-4c7f-9640-f9b4a65a363e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "artist index: 1179.\n",
      "artist name: Lullaby Baby Trio.\n",
      "playlist tag: instrumental lullaby crianas e famlia sleep new age piano kids & family vbs classify children's music pop rock christian relaxative lullabies gospel msica cristiana y gspel childrens christmas calming.\n",
      "top streaming countries:           US GB NL.\n",
      "genres: lullaby\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>score</th>\n",
       "      <th>name</th>\n",
       "      <th>popularity</th>\n",
       "      <th>spotify_id</th>\n",
       "      <th>streaming_country</th>\n",
       "      <th>spotify_genre</th>\n",
       "      <th>playlist_tags</th>\n",
       "      <th>spotify_description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>682</td>\n",
       "      <td>0.367920</td>\n",
       "      <td>Jeff Danna</td>\n",
       "      <td>38</td>\n",
       "      <td>4v7z4d0nyIY3mWGz1AXoK1</td>\n",
       "      <td>US AU GB</td>\n",
       "      <td>canadian soundtrack|soundtrack</td>\n",
       "      <td>children's music canadian soundtrack dtente scorecore children piano cover classical new age pop clsica chill classique background orchestral focu...</td>\n",
       "      <td>a hand injury ended performance career pianist guitarist jeff danna dream kept alive transition soundtrack composing using score warner brothers t...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>478</td>\n",
       "      <td>0.363037</td>\n",
       "      <td>Lullaby Orchestra</td>\n",
       "      <td>24</td>\n",
       "      <td>1tfEFa6qUIF1hMgOK2CV5c</td>\n",
       "      <td>MX CL CO</td>\n",
       "      <td>lullaby|musica de fondo</td>\n",
       "      <td>classical water pop children's music calming instrumental world meditation new age easy listening</td>\n",
       "      <td>playlists featuring this is lullabies in nature n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1049</td>\n",
       "      <td>0.350098</td>\n",
       "      <td>Tiquequê</td>\n",
       "      <td>41</td>\n",
       "      <td>6g11mw48sLT4KFb1LEavV7</td>\n",
       "      <td>PT CL BR</td>\n",
       "      <td>musica infantil</td>\n",
       "      <td>christian &amp; gospel adoracao crianas e famlia childrens christmas pagode pop rock musica para criancas soundtrack disney portugues brasil latin cla...</td>\n",
       "      <td>tiquequ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>126</td>\n",
       "      <td>0.339111</td>\n",
       "      <td>Recess Monkey</td>\n",
       "      <td>22</td>\n",
       "      <td>0oXrvAp6NnKeWz1qnKrNLb</td>\n",
       "      <td>US AU CA</td>\n",
       "      <td>children's folk|kindie rock</td>\n",
       "      <td>t verano post-teen pop italian electronica hamilton on indie british children's music kindie rock spoken word lullaby dance australian psychedelic...</td>\n",
       "      <td>drew jack korum three teachers make kid people magazine n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>728</td>\n",
       "      <td>0.304932</td>\n",
       "      <td>Charity and the Jamband</td>\n",
       "      <td>12</td>\n",
       "      <td>5YTYt0ir3CPgXGWTlfWdHT</td>\n",
       "      <td>US AU CA</td>\n",
       "      <td>kindie rock</td>\n",
       "      <td>summer crianas e famlia rock kindie children's folk verano enfants et famille barn och familj permanent wave singer/songwriter pop childrens chris...</td>\n",
       "      <td>since 2002 charity jamband recording performing award winning music children grown ups love them n nrenowned funky unforgettable grooves joy fille...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index     score                     name  popularity  \\\n",
       "0    682  0.367920               Jeff Danna          38   \n",
       "0    478  0.363037        Lullaby Orchestra          24   \n",
       "0   1049  0.350098                 Tiquequê          41   \n",
       "0    126  0.339111            Recess Monkey          22   \n",
       "0    728  0.304932  Charity and the Jamband          12   \n",
       "\n",
       "               spotify_id streaming_country                   spotify_genre  \\\n",
       "0  4v7z4d0nyIY3mWGz1AXoK1          US AU GB  canadian soundtrack|soundtrack   \n",
       "0  1tfEFa6qUIF1hMgOK2CV5c          MX CL CO         lullaby|musica de fondo   \n",
       "0  6g11mw48sLT4KFb1LEavV7          PT CL BR                 musica infantil   \n",
       "0  0oXrvAp6NnKeWz1qnKrNLb          US AU CA     children's folk|kindie rock   \n",
       "0  5YTYt0ir3CPgXGWTlfWdHT          US AU CA                     kindie rock   \n",
       "\n",
       "                                                                                                                                           playlist_tags  \\\n",
       "0  children's music canadian soundtrack dtente scorecore children piano cover classical new age pop clsica chill classique background orchestral focu...   \n",
       "0                                                      classical water pop children's music calming instrumental world meditation new age easy listening   \n",
       "0  christian & gospel adoracao crianas e famlia childrens christmas pagode pop rock musica para criancas soundtrack disney portugues brasil latin cla...   \n",
       "0  t verano post-teen pop italian electronica hamilton on indie british children's music kindie rock spoken word lullaby dance australian psychedelic...   \n",
       "0  summer crianas e famlia rock kindie children's folk verano enfants et famille barn och familj permanent wave singer/songwriter pop childrens chris...   \n",
       "\n",
       "                                                                                                                                     spotify_description  \n",
       "0  a hand injury ended performance career pianist guitarist jeff danna dream kept alive transition soundtrack composing using score warner brothers t...  \n",
       "0                                                                                                      playlists featuring this is lullabies in nature n  \n",
       "0                                                                                                                                                tiquequ  \n",
       "0                                                                                              drew jack korum three teachers make kid people magazine n  \n",
       "0  since 2002 charity jamband recording performing award winning music children grown ups love them n nrenowned funky unforgettable grooves joy fille...  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spotify_id = '5ivnFTODQHvL7qQ6EqM0rq' # Epica\n",
    "spotify_id = '5G3Tk9bNgXmBpMnUCesqQx' # Sia\n",
    "spotify_id = '76bgYMdQ7UYnUad5NiyE6v'\n",
    "\n",
    "response_tag = get_similarity(tags_input_df, similarity_matrix_tag, indices_tag, \\\n",
    "                                         spotify_id, top_n=5)\n",
    "response_tag"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f133cfa9-4720-46ff-b85a-942c2c28a510",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0283fefb-1a98-4d07-8560-76a225eeae64",
   "metadata": {},
   "source": [
    "### Find similar artists using genre + location data with KNN approach"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "6a7bf4da-8028-4c73-a0f6-e6e14ad99281",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(29868, 10)"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SPOTIFY_ARTIST_ID</th>\n",
       "      <th>C_FAN_COUNTRY_CODE</th>\n",
       "      <th>C_POPULARITY</th>\n",
       "      <th>C_ARTIST_NAME</th>\n",
       "      <th>C_GLOBAL_PARTICIPANT_ID</th>\n",
       "      <th>C_GENRES</th>\n",
       "      <th>C_DESCRIPTION</th>\n",
       "      <th>CLEANED_TAG_NAME</th>\n",
       "      <th>genre_word_count</th>\n",
       "      <th>COMBINED</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>000igwzkKkxJrHoQgqZ4zM</td>\n",
       "      <td>BG DE GB</td>\n",
       "      <td>5</td>\n",
       "      <td>Zarko</td>\n",
       "      <td>e3116738-9789-452a-8112-83e5a935a3de</td>\n",
       "      <td>bulgarian pop</td>\n",
       "      <td>zarko</td>\n",
       "      <td>None</td>\n",
       "      <td>1</td>\n",
       "      <td>BG DE GB bulgarian pop</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        SPOTIFY_ARTIST_ID C_FAN_COUNTRY_CODE  C_POPULARITY C_ARTIST_NAME  \\\n",
       "0  000igwzkKkxJrHoQgqZ4zM           BG DE GB             5         Zarko   \n",
       "\n",
       "                C_GLOBAL_PARTICIPANT_ID       C_GENRES C_DESCRIPTION  \\\n",
       "0  e3116738-9789-452a-8112-83e5a935a3de  bulgarian pop         zarko   \n",
       "\n",
       "  CLEANED_TAG_NAME  genre_word_count                COMBINED  \n",
       "0             None                 1  BG DE GB bulgarian pop  "
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "algo_knn_df = chartmetric_df.copy()\n",
    "\n",
    "algo_knn_df['C_FAN_COUNTRY_CODE'] = algo_knn_df['C_FAN_COUNTRY_CODE'].apply(replace_straight_with_space)\n",
    "algo_knn_df['COMBINED'] = algo_knn_df['C_FAN_COUNTRY_CODE'] + ' ' + algo_knn_df['C_GENRES']\n",
    "algo_knn_df.shape\n",
    "algo_knn_df.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "8d57529b-d782-4a1b-9be6-5f5ba1eabadb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sample of input data:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>150</th>\n",
       "      <th>150 bpm</th>\n",
       "      <th>21st</th>\n",
       "      <th>21st century</th>\n",
       "      <th>21st century classical</th>\n",
       "      <th>432hz</th>\n",
       "      <th>48g</th>\n",
       "      <th>8</th>\n",
       "      <th>8 bit</th>\n",
       "      <th>8 bit chiptune</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   150  150 bpm  21st  21st century  21st century classical  432hz  48g    8  \\\n",
       "0  0.0      0.0   0.0           0.0                     0.0    0.0  0.0  0.0   \n",
       "1  0.0      0.0   0.0           0.0                     0.0    0.0  0.0  0.0   \n",
       "2  0.0      0.0   0.0           0.0                     0.0    0.0  0.0  0.0   \n",
       "3  0.0      0.0   0.0           0.0                     0.0    0.0  0.0  0.0   \n",
       "4  0.0      0.0   0.0           0.0                     0.0    0.0  0.0  0.0   \n",
       "\n",
       "   8 bit  8 bit chiptune  \n",
       "0    0.0             0.0  \n",
       "1    0.0             0.0  \n",
       "2    0.0             0.0  \n",
       "3    0.0             0.0  \n",
       "4    0.0             0.0  "
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf_knn = TfidfVectorizer(analyzer='word',\n",
    "                      token_pattern=r'\\w{1,}',\n",
    "                      ngram_range=(1, 3), \n",
    "                      stop_words = 'english') # What about IN for INDIA?\n",
    "\n",
    "dtm = tf_knn.fit_transform(algo_knn_df['COMBINED'].values.astype('U'))\n",
    "\n",
    "dtm = pd.DataFrame(dtm.todense(), columns=tf_knn.get_feature_names_out())\n",
    "print(\"Sample of input data:\")\n",
    "dtm.iloc[:,0:10].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "1983114b-9df3-43a4-80ca-80fb9ba1adf4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NearestNeighbors()"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nn = NearestNeighbors(n_neighbors=5, algorithm='auto') # algorithm='ball_tree'\n",
    "nn.fit(dtm.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "1f393efd-55b8-4c15-9050-d182dcf12e08",
   "metadata": {},
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "What artist are you looking for: epic\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Search term used: epic.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>SPOTIFY_ARTIST_ID</th>\n",
       "      <th>C_ARTIST_NAME</th>\n",
       "      <th>C_POPULARITY</th>\n",
       "      <th>COMBINED</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>5ivnFTODQHvL7qQ6EqM0rq</td>\n",
       "      <td>Epica</td>\n",
       "      <td>55</td>\n",
       "      <td>MX CL BR dutch metal|gothic metal|gothic symphonic metal|neo classical metal|power metal|progressive metal|symphonic metal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3DU50uTJPCGLaMjVS5y8Cu</td>\n",
       "      <td>Epicure</td>\n",
       "      <td>33</td>\n",
       "      <td>DE US GB australian alternative rock|persian hip hop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4KjQcjo5PfgEHDJELjoVUL</td>\n",
       "      <td>Epicure</td>\n",
       "      <td>32</td>\n",
       "      <td>DE GB US australian alternative rock|persian hip hop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1UNEmUaiIhIpZkrv2u8A21</td>\n",
       "      <td>Rifat Tepic</td>\n",
       "      <td>18</td>\n",
       "      <td>DE AT CH narodna muzika</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5JW8Qd4FN56wPHEFtLOTAj</td>\n",
       "      <td>Epicentro</td>\n",
       "      <td>16</td>\n",
       "      <td>CL MX CO rap chileno</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "while True:\n",
    "    artist_name = input(\"What artist are you looking for:\")\n",
    "    artist_name = artist_name.lower()\n",
    "    print(f\"Search term used: {artist_name}.\")\n",
    "    algo_knn_df['search_string'] = algo_knn_df['C_ARTIST_NAME'].str.lower()\n",
    "    HTML(algo_knn_df[algo_knn_df['search_string'].str.contains(artist_name)][['SPOTIFY_ARTIST_ID', 'C_ARTIST_NAME', 'C_POPULARITY', 'COMBINED']].sort_values(by=['C_POPULARITY'],ascending=False).head().to_html(index=False))\n",
    "    algo_knn_df = algo_knn_df.drop(['search_string'], axis=1)\n",
    "    break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "0922a41d-4e11-49c1-84d5-d175752a04c9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "artist index: 20393.\n",
      "artist name: Epica.\n",
      "top streaming countries: MX CL BR.\n",
      "genres: dutch metal|gothic metal|gothic symphonic metal|neo classical metal|power m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/homebrew/anaconda3/envs/kdnugget_recommender/lib/python3.8/site-packages/sklearn/utils/validation.py:593: FutureWarning: np.matrix usage is deprecated in 1.0 and will raise a TypeError in 1.2. Please convert to a numpy array with np.asarray. For more information see: https://numpy.org/doc/stable/reference/generated/numpy.matrix.html\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>score</th>\n",
       "      <th>name</th>\n",
       "      <th>popularity</th>\n",
       "      <th>spotify_id</th>\n",
       "      <th>spotify_genre</th>\n",
       "      <th>spotify_description</th>\n",
       "      <th>streaming_countries</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19784</td>\n",
       "      <td>0.891703</td>\n",
       "      <td>Liquid Sky</td>\n",
       "      <td>15</td>\n",
       "      <td>5ajbKvDTASr6MrwqFzfaKX</td>\n",
       "      <td>gothic metal|gothic symphonic metal|symphonic metal</td>\n",
       "      <td></td>\n",
       "      <td>US GB DE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11897</td>\n",
       "      <td>0.895858</td>\n",
       "      <td>The Gathering</td>\n",
       "      <td>40</td>\n",
       "      <td>2kO6zjt4a1OIqxOERhliEX</td>\n",
       "      <td>atmospheric doom|dutch metal|gothic metal|gothic symphonic metal|symphonic metal</td>\n",
       "      <td>a creative classy highly refined symphonic metal outfit holland gathering debuted 1993 s always fairly straightforward death metal album vocals ma...</td>\n",
       "      <td>CL MX NL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>18426</td>\n",
       "      <td>0.910907</td>\n",
       "      <td>Tears Of Magdalena</td>\n",
       "      <td>1</td>\n",
       "      <td>5Iio3qOqBGIupXFCdIO1gE</td>\n",
       "      <td>gothic metal|gothic symphonic metal|symphonic metal</td>\n",
       "      <td></td>\n",
       "      <td>MX BR US</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19032</td>\n",
       "      <td>0.913140</td>\n",
       "      <td>Van Canto</td>\n",
       "      <td>45</td>\n",
       "      <td>5MTAMin8T3vIgak5ON3xf2</td>\n",
       "      <td>german metal|neo classical metal|power metal|progressive metal|speed metal|symphonic metal</td>\n",
       "      <td>one unconventional bands german metal scene van canto cappella ensemble uses versatile vocal skills re create genre s heavy guitar bass sounds for...</td>\n",
       "      <td>DE SE FI</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index     score                name  popularity              spotify_id  \\\n",
       "0  19784  0.891703          Liquid Sky          15  5ajbKvDTASr6MrwqFzfaKX   \n",
       "0  11897  0.895858       The Gathering          40  2kO6zjt4a1OIqxOERhliEX   \n",
       "0  18426  0.910907  Tears Of Magdalena           1  5Iio3qOqBGIupXFCdIO1gE   \n",
       "0  19032  0.913140           Van Canto          45  5MTAMin8T3vIgak5ON3xf2   \n",
       "\n",
       "                                                                                spotify_genre  \\\n",
       "0                                         gothic metal|gothic symphonic metal|symphonic metal   \n",
       "0            atmospheric doom|dutch metal|gothic metal|gothic symphonic metal|symphonic metal   \n",
       "0                                         gothic metal|gothic symphonic metal|symphonic metal   \n",
       "0  german metal|neo classical metal|power metal|progressive metal|speed metal|symphonic metal   \n",
       "\n",
       "                                                                                                                                     spotify_description  \\\n",
       "0                                                                                                                                                          \n",
       "0  a creative classy highly refined symphonic metal outfit holland gathering debuted 1993 s always fairly straightforward death metal album vocals ma...   \n",
       "0                                                                                                                                                          \n",
       "0  one unconventional bands german metal scene van canto cappella ensemble uses versatile vocal skills re create genre s heavy guitar bass sounds for...   \n",
       "\n",
       "  streaming_countries  \n",
       "0            US GB DE  \n",
       "0            CL MX NL  \n",
       "0            MX BR US  \n",
       "0            DE SE FI  "
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "search_spotify_id = '5ivnFTODQHvL7qQ6EqM0rq'\n",
    "# search_spotify_id = '4dfHihEuXjcd4rR5jBFa2B'\n",
    "# search_spotify_id = '1JLM0FVA7cOG0RotFA40mM'\n",
    "returned_knn = find_knn_similarities(algo_knn_df, tf_knn, nn, search_spotify_id)\n",
    "returned_knn"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "40e99c2a-9a1a-4026-b970-908ee538625c",
   "metadata": {},
   "source": [
    "### Find similar artists using TOPIC modelling based on artist description\n",
    "Using Negative Matrix Factorization.<br>\n",
    "Idea is to find most frequent words from artists description and then based on that form topics that have unique representation of these words."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "b3d7b8b6-bd43-4bd0-9b64-1b0bf1911821",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Matrix memory usage: 4.240368 megabytes.\n",
      "Nr of TF IDF features: 2749.\n",
      "First 10 TF IDF features: ['000' '10' '100' '11' '12' '13' '14' '15' '16' '17'].\n"
     ]
    }
   ],
   "source": [
    "# Build the TF-IDF Matrix\n",
    "algo_topic_df = chartmetric_df[chartmetric_df['C_DESCRIPTION']!=''].copy().reset_index()\n",
    "                               \n",
    "# use tfidf by removing tokens that don't appear in at least 50 documents\n",
    "tfidf_topic = TfidfVectorizer(min_df=50, stop_words='english')\n",
    " \n",
    "# Fit and transform\n",
    "tfidf_matrix_topic = tfidf_topic.fit_transform(algo_topic_df.C_DESCRIPTION)\n",
    "print(f\"Matrix memory usage: {tfidf_matrix_topic.data.nbytes / 1000000} megabytes.\")\n",
    "print(f\"Nr of TF IDF features: {len(tfidf_topic.get_feature_names_out())}.\")\n",
    "print(f\"First 10 TF IDF features: {tfidf_topic.get_feature_names_out()[0:10]}.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab9ede57-fc06-43eb-a560-f77483a086d1",
   "metadata": {},
   "source": [
    "<b>Build the NMF Model</b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "30acf388-b684-423e-8fb9-70bc39157201",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/homebrew/anaconda3/envs/kdnugget_recommender/lib/python3.8/site-packages/sklearn/decomposition/_nmf.py:289: FutureWarning: The 'init' value, when 'init=None' and n_components is less than n_samples and n_features, will be changed from 'nndsvd' to 'nndsvda' in 1.1 (renaming of 0.26).\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "NMF(n_components=5, random_state=5)"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TF-IDF Dimensions: (17304, 2749)\n",
      "Features Dimensions: (17304, 5)\n",
      "Components Dimensions: (5, 2749)\n"
     ]
    }
   ],
   "source": [
    "# Create an NMF instance: model\n",
    "# the 5 components will be the topics\n",
    "model = NMF(n_components=5, random_state=5)\n",
    " \n",
    "# Fit the model to TF-IDF\n",
    "model.fit(tfidf_matrix_topic)\n",
    " \n",
    "# Transform the TF-IDF: nmf_features\n",
    "nmf_features = model.transform(tfidf_matrix_topic)\n",
    "\n",
    "print(f\"TF-IDF Dimensions: {tfidf_matrix_topic.shape}\")\n",
    "print(f\"Features Dimensions: {nmf_features.shape}\")\n",
    "print(f\"Components Dimensions: {model.components_.shape}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "14aadd60-a13b-448c-bcf7-062db7b3c410",
   "metadata": {},
   "outputs": [
    {
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       "      <td>0.033422</td>\n",
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       "      <td>0.025836</td>\n",
       "      <td>0.028071</td>\n",
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       "      <td>0.280707</td>\n",
       "      <td>0.332363</td>\n",
       "      <td>0.005440</td>\n",
       "      <td>0.084052</td>\n",
       "      <td>0.121791</td>\n",
       "      <td>0.008247</td>\n",
       "      <td>0.037236</td>\n",
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       "      <td>0.033341</td>\n",
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       "      <td>0.000000</td>\n",
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       "        000        10       100        11        12        13        14  \\\n",
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       "4  0.019637  0.038090  0.009089  0.010957  0.015967  0.001198  0.002002   \n",
       "\n",
       "         15        16        17  ...      year     years        yo      york  \\\n",
       "0  0.010009  0.011295  0.009466  ...  0.147406  0.097295  0.007155  0.079584   \n",
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       "4  0.002851  0.008532  0.000000  ...  0.000000  0.000000  0.004946  0.000000   \n",
       "\n",
       "      young   younger     youth   youtube   zealand        zu  \n",
       "0  0.033560  0.012337  0.012550  0.000000  0.000756  0.000021  \n",
       "1  0.000000  0.000000  0.000000  0.016239  0.000000  0.000000  \n",
       "2  0.121791  0.008247  0.037236  0.038310  0.033341  0.000000  \n",
       "3  0.000374  0.000000  0.004539  0.070257  0.000000  0.014037  \n",
       "4  0.001211  0.000613  0.006327  0.025806  0.000000  0.025112  \n",
       "\n",
       "[5 rows x 2749 columns]"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a DataFrame from compoents\n",
    "components_df = pd.DataFrame(model.components_, columns=tfidf_topic.get_feature_names_out())\n",
    "components_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "138b722c-10b4-4a8f-91e7-5e646baf1bb5",
   "metadata": {},
   "source": [
    "We have created the N topics using NMF. Let’s have a look at the 10 more important words for each topic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "694a3e70-b4cb-49fd-97ba-7eb3cdc72f89",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>topic_1</th>\n",
       "      <th>topic_1_score</th>\n",
       "      <th>topic_2</th>\n",
       "      <th>topic_2_score</th>\n",
       "      <th>topic_3</th>\n",
       "      <th>topic_3_score</th>\n",
       "      <th>topic_4</th>\n",
       "      <th>topic_4_score</th>\n",
       "      <th>topic_5</th>\n",
       "      <th>topic_5_score</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>href</td>\n",
       "      <td>3.126394</td>\n",
       "      <td>la</td>\n",
       "      <td>2.190963</td>\n",
       "      <td>music</td>\n",
       "      <td>1.367014</td>\n",
       "      <td>34</td>\n",
       "      <td>2.882525</td>\n",
       "      <td>quot</td>\n",
       "      <td>3.344987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>spotify</td>\n",
       "      <td>3.097451</td>\n",
       "      <td>en</td>\n",
       "      <td>2.167460</td>\n",
       "      <td>band</td>\n",
       "      <td>1.330859</td>\n",
       "      <td>com</td>\n",
       "      <td>0.636159</td>\n",
       "      <td>39</td>\n",
       "      <td>0.637435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>artist</td>\n",
       "      <td>2.660605</td>\n",
       "      <td>el</td>\n",
       "      <td>1.765425</td>\n",
       "      <td>39</td>\n",
       "      <td>0.742830</td>\n",
       "      <td>em</td>\n",
       "      <td>0.466129</td>\n",
       "      <td>data</td>\n",
       "      <td>0.347219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>data</td>\n",
       "      <td>0.733472</td>\n",
       "      <td>que</td>\n",
       "      <td>0.949218</td>\n",
       "      <td>album</td>\n",
       "      <td>0.661799</td>\n",
       "      <td>39</td>\n",
       "      <td>0.453040</td>\n",
       "      <td>em</td>\n",
       "      <td>0.190988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>label</td>\n",
       "      <td>0.473964</td>\n",
       "      <td>su</td>\n",
       "      <td>0.868382</td>\n",
       "      <td>rock</td>\n",
       "      <td>0.597864</td>\n",
       "      <td>data</td>\n",
       "      <td>0.312951</td>\n",
       "      <td>album</td>\n",
       "      <td>0.180898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3a</td>\n",
       "      <td>0.400935</td>\n",
       "      <td>los</td>\n",
       "      <td>0.864876</td>\n",
       "      <td>new</td>\n",
       "      <td>0.566308</td>\n",
       "      <td>da</td>\n",
       "      <td>0.312113</td>\n",
       "      <td>com</td>\n",
       "      <td>0.173112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>22</td>\n",
       "      <td>0.396753</td>\n",
       "      <td>del</td>\n",
       "      <td>0.794110</td>\n",
       "      <td>released</td>\n",
       "      <td>0.563709</td>\n",
       "      <td>na</td>\n",
       "      <td>0.222408</td>\n",
       "      <td>amp</td>\n",
       "      <td>0.160453</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>search</td>\n",
       "      <td>0.395981</td>\n",
       "      <td>por</td>\n",
       "      <td>0.573297</td>\n",
       "      <td>sound</td>\n",
       "      <td>0.469369</td>\n",
       "      <td>um</td>\n",
       "      <td>0.216023</td>\n",
       "      <td>da</td>\n",
       "      <td>0.123425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>album</td>\n",
       "      <td>0.287568</td>\n",
       "      <td>una</td>\n",
       "      <td>0.563366</td>\n",
       "      <td>guitar</td>\n",
       "      <td>0.441425</td>\n",
       "      <td>uma</td>\n",
       "      <td>0.169290</td>\n",
       "      <td>2017</td>\n",
       "      <td>0.102363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>rovi</td>\n",
       "      <td>0.209557</td>\n",
       "      <td>como</td>\n",
       "      <td>0.534736</td>\n",
       "      <td>metal</td>\n",
       "      <td>0.419162</td>\n",
       "      <td>seu</td>\n",
       "      <td>0.168713</td>\n",
       "      <td>und</td>\n",
       "      <td>0.100846</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   topic_1  topic_1_score topic_2  topic_2_score   topic_3  topic_3_score  \\\n",
       "0     href       3.126394      la       2.190963     music       1.367014   \n",
       "1  spotify       3.097451      en       2.167460      band       1.330859   \n",
       "2   artist       2.660605      el       1.765425        39       0.742830   \n",
       "3     data       0.733472     que       0.949218     album       0.661799   \n",
       "4    label       0.473964      su       0.868382      rock       0.597864   \n",
       "5       3a       0.400935     los       0.864876       new       0.566308   \n",
       "6       22       0.396753     del       0.794110  released       0.563709   \n",
       "7   search       0.395981     por       0.573297     sound       0.469369   \n",
       "8    album       0.287568     una       0.563366    guitar       0.441425   \n",
       "9     rovi       0.209557    como       0.534736     metal       0.419162   \n",
       "\n",
       "  topic_4  topic_4_score topic_5  topic_5_score  \n",
       "0      34       2.882525    quot       3.344987  \n",
       "1     com       0.636159      39       0.637435  \n",
       "2      em       0.466129    data       0.347219  \n",
       "3      39       0.453040      em       0.190988  \n",
       "4    data       0.312951   album       0.180898  \n",
       "5      da       0.312113     com       0.173112  \n",
       "6      na       0.222408     amp       0.160453  \n",
       "7      um       0.216023      da       0.123425  \n",
       "8     uma       0.169290    2017       0.102363  \n",
       "9     seu       0.168713     und       0.100846  "
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "topics_df = pd.DataFrame()\n",
    "for topic in range(components_df.shape[0]):\n",
    "    tmp = components_df.iloc[topic]\n",
    "    # print(f'For topic {topic+1} the words with the highest value are:')\n",
    "    temp_topic_df = tmp.nlargest(10).to_frame().reset_index().set_axis(['topic_'+ str(topic+1),'topic_'+ str(topic+1) + '_score'], axis=1)\n",
    "    topics_df = pd.concat([topics_df, temp_topic_df], axis=\"columns\")\n",
    "    #print(tmp.nlargest(10))\n",
    "    #print('\\n')\n",
    "topics_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "02c165c2-4e1e-4c02-b216-e2c6bf327d96",
   "metadata": {},
   "source": [
    "We could hypothesis that topic 5 is related to metal/rock band. Or that topic 3 is  avout musical producer. But we also see that because of multilanguage, topic 2 is based completely on non-English words."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d950ea50-8484-4e72-a7f2-f7fd5bf89fba",
   "metadata": {},
   "source": [
    "<b>Let's view some samples</b>:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "id": "5e55fc19-bde3-4e38-a909-0253ebba651c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original artist description: carlotta centanni known friends charlie italian singer songwriter recording artist rome living sydney australia she granddaughter armandino zingone played legendary renato carosone golden age la dolce vita italian music carlottas music builds heritage heavily influenced pop jazz soul funk bossanova\n",
      "Best topic for this artist description is: 3\n",
      "-------------------------------------------------------\n",
      "Original artist description: independent rap hip hop artist from bengaluru karnataka n3bps music bigbrorecords n n\n",
      "Best topic for this artist description is: 3\n",
      "-------------------------------------------------------\n",
      "Original artist description: young chhaylee singer songwriter the pnw calls the queen city home elements soul pop folk melded create sound own his voice powerful yet flutters simultaneously strong vulnerable\n",
      "Best topic for this artist description is: 3\n",
      "-------------------------------------------------------\n",
      "Original artist description: i average guy living little village ontario canada music one passions much i centres around it this includes teaching writing publishing song week leading music village church n ni love seeing way music impacts changes people something moving development melody way instruments blend together chord played right touch resonate heart i hope music impact you n nplease take time look patreon page https patreon com jasonsilver watch lyric videos youtube https youtube com jasonsilvermusic n ni would love hear inclined please shy n\n",
      "Best topic for this artist description is: 3\n",
      "-------------------------------------------------------\n",
      "Original artist description: fiasko experimental sludge black post metal band based warsaw poland the group founded people previously played together so i scream n nour first release gupcy umieraj groove alt industrial metal feeling n nafter changes line up philosophy spontaneously took diffrent turn n nwhat came existence result quot mizantropolia quot ep premieres 22 02 2020\n",
      "Best topic for this artist description is: 4\n",
      "-------------------------------------------------------\n",
      "Original artist description: seven piece maritime dub reggae band weak size fish mainstay canadas underground east coast music scene better part decade getting start maritime jam band festival rotation band continued build stronger grassroots foundation years packing clubs appeasing festival goers captivating live show drawing inspiration likes dub pioneers king tubby scientist akin current acts fat freddys drop the black seeds band crafts blend dub reggae infused salty maritime jams n nthe drift third studio album sets new benchmark band the album takes deep dive admiration dub music came jamaica 70s guided roots driven hypnotic grooves records deep hitting sound takes submarine odyssey vast outer space soundscapes n nhaving played events harvest jazz amp blues folly fest future forest shared stage classified dub kartel moon hooch band proven malleability able navigate flow varied show scenarios with three full length albums many performances belt weak size fish matured band embraces change ever evolving growing creative unit while continue focus much energy ever live show band aspires reach new audiences showcase unique sound n\n",
      "Best topic for this artist description is: 5\n",
      "-------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "artists_idx = [30, 90, 101, 1018, 3037, 3040]\n",
    "for a in artists_idx:\n",
    "    a_desc = algo_topic_df.C_DESCRIPTION[a]\n",
    "    print(f\"Original artist description: {a_desc}\")\n",
    "    best_topic = pd.DataFrame(nmf_features).loc[a].idxmax() + 1 # we will get index of most relevant topic. Index starts from 0 so 0 means topic 1 and index 4 means topic 5.\n",
    "    print(f\"Best topic for this artist description is: {best_topic}\")\n",
    "    print(f\"-------------------------------------------------------\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "id": "6771a2a6-52ff-43a5-bfe2-a85787d4ba30",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "In general descriptions are divided between topics as follows:\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0    1591\n",
       "2     652\n",
       "4     436\n",
       "1     260\n",
       "3     103\n",
       "dtype: int64"
      ]
     },
     "execution_count": 195,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"In general descriptions are divided between topics as follows:\")\n",
    "pd.DataFrame(nmf_features).idxmax(axis=1).value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25d7b7fe-7b1e-4815-b6f5-6f487f7ef704",
   "metadata": {},
   "source": [
    "Most of the samples were related to topic 3 and aggregations show us that it's 2nd most used topic(index 2 and 652 values). Topics 4 and 5 are smaller in size. But as we know that source data is multilingual and has low quality then finding good matches is difficult."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b189d369-86b9-4a52-9623-9447c714a062",
   "metadata": {},
   "source": [
    "<b>\"Predicting\" topic based on new description.</b><br>\n",
    "We can see if we input proper meaningful description, then algorithm assigns correct topics. For first description it's topic 5 and for second it's topic 3 with highest relevance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "id": "29d2394d-3141-4c8b-a1aa-0809d2d41169",
   "metadata": {},
   "outputs": [
    {
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     "output_type": "execute_result"
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       "         0    1         2         3         4\n",
       "0  0.00322  0.0  0.081364  0.001183  0.028389"
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     "execution_count": 199,
     "metadata": {},
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   ],
   "source": [
    "new_descriptions =  [\"New rock metal band with 2 guitar players\",  \"Well known NY musical producer has released new songs\"]\n",
    "# Transform the TF-IDF\n",
    "for nd in new_descriptions:\n",
    "    X = tfidf_topic.transform([nd])\n",
    "    # Transform the TF-IDF: nmf_features\n",
    "    nmf_features = model.transform(X) \n",
    "    pd.DataFrame(nmf_features)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "056ee2d2-6431-4cc8-acbc-2581d313e85a",
   "metadata": {},
   "source": [
    "### Replicate similarities using Orchard's data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c180c06f-0068-41ce-ae6e-fd887631e78f",
   "metadata": {},
   "source": [
    "<B>Get data</b><br>\n",
    "Here we will be using data from Orchard databases."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "id": "3bde244a-b3d5-4d23-8851-1c10e0be11c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# initiate connection\n",
    "ctx, cur = snowflake_key_pair_connect()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "id": "edb5499a-4a59-498c-872f-650ca05f98c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<snowflake.connector.cursor.SnowflakeCursor at 0x7fdb4a09dd60>"
      ]
     },
     "execution_count": 232,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "(6460, 3)"
      ]
     },
     "execution_count": 232,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SPOTIFY_ARTIST_ID</th>\n",
       "      <th>O_COUNTRY_CODE</th>\n",
       "      <th>O_SUBGENRE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>001Ju8fxqMbobN0xjX7XPL</td>\n",
       "      <td>IN</td>\n",
       "      <td>Indian Devotional &amp; Spiritual|Indian Folk|Indian Pop &amp; Fusion|Indian Regional Film|Pop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>003f4bk13c6Q3gAUXv7dGJ</td>\n",
       "      <td>AT</td>\n",
       "      <td>Classical</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>009IKtLg2rg2QMbvNtWaoh</td>\n",
       "      <td>VI</td>\n",
       "      <td>Comedy Rap|Conscious/Political|Dancehall|Educational|Electro-Funk|Funk|Instrumentals|Neo-Soul|New School|Reggae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>00DSCauOVv9bIKe8bGWSTG</td>\n",
       "      <td>DE</td>\n",
       "      <td>Pop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>00DuPiLri3mNomvvM3nZvU</td>\n",
       "      <td>JP</td>\n",
       "      <td>Pop</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        SPOTIFY_ARTIST_ID O_COUNTRY_CODE  \\\n",
       "0  001Ju8fxqMbobN0xjX7XPL             IN   \n",
       "1  003f4bk13c6Q3gAUXv7dGJ             AT   \n",
       "2  009IKtLg2rg2QMbvNtWaoh             VI   \n",
       "3  00DSCauOVv9bIKe8bGWSTG             DE   \n",
       "4  00DuPiLri3mNomvvM3nZvU             JP   \n",
       "\n",
       "                                                                                                        O_SUBGENRE  \n",
       "0                           Indian Devotional & Spiritual|Indian Folk|Indian Pop & Fusion|Indian Regional Film|Pop  \n",
       "1                                                                                                        Classical  \n",
       "2  Comedy Rap|Conscious/Political|Dancehall|Educational|Electro-Funk|Funk|Instrumentals|Neo-Soul|New School|Reggae  \n",
       "3                                                                                                              Pop  \n",
       "4                                                                                                              Pop  "
      ]
     },
     "execution_count": 232,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# query table created with Notebook \"Similar Orchard artists.ipynb\"\n",
    "sql = \"\"\"select * from DEV_ENGINEERING.RBOMBERG_DBT.ORCHARD_INPUT_FOR_REC\n",
    "\"\"\"\n",
    "cur.execute(sql)\n",
    "orchard_df = cur.fetch_pandas_all()\n",
    "orchard_df.shape\n",
    "orchard_df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "id": "ed5d70c0-421d-425a-b413-ce0fa1b33c2c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2160x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculating the genre word count\n",
    "orchard_df['genre_word_count'] = orchard_df['O_SUBGENRE'].apply(lambda x: len(str(x).split('|')))\n",
    "orchard_df['genre_word_count'].describe()\n",
    "# Plotting the genre word count\n",
    "orchard_df['genre_word_count'].plot(\n",
    "    kind='hist',\n",
    "    color = '#A60628',\n",
    "    bins = 100,\n",
    "    figsize = (30,6),title='Word count distribution for genre terms')\n",
    "plt.xticks(np.arange(0, 101, 1));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "id": "921c4c69-f485-41f5-a43c-4a0a0b160bda",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Some artist related genre examples:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>SPOTIFY_ARTIST_ID</th>\n",
       "      <th>O_SUBGENRE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>01h50SsMXyYlhVA0ukTjHm</td>\n",
       "      <td>Breaks|Chill|Downtempo|Electro|Lounge|Techno Dub</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>025mNMOyhsDIKHAVTHp9xB</td>\n",
       "      <td>Indian Bollywood|Indian Devotional &amp; Spiritual|Indian Gazal|Indian Pop &amp; Fusion|Indie Pop|Pop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>04BzyfUaAhlqqcs3Iv1AwT</td>\n",
       "      <td>Flamenco|Mambo|New School|Nuevo Flamenco|Reggaeton|Underground</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>05X5qdeeGgBQe115bTNlWu</td>\n",
       "      <td>Alternative Rap|Hip-Hop|Instrumentals|Party Rap|R&amp;B|Rap</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>06Y5tXoiJBgYgPJREyFbXO</td>\n",
       "      <td>Brazil|Brazilian-Bossa Nova|Brazilian-MPB|Folk|Indie Rock|Post-Rock / Experimental</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 210,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(\"Some artist related genre examples:\")\n",
    "HTML(orchard_df[orchard_df['genre_word_count']==6][['SPOTIFY_ARTIST_ID', 'O_SUBGENRE']].head().to_html(index=False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "id": "6e6623d5-ba9a-49bf-8522-c301efc629bd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "subgenres_for_wcloud=\" \".join(orchard_df.O_SUBGENRE.to_list())draw_word_cloud(subgenres_for_wcloud)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "id": "cde5ea66-5fa3-4cd4-b286-1655bec8bb09",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                                Indian Devotional & Spiritual Indian Folk Indian Pop & Fusion Indian Regional Film Pop\n",
       "1                                                                                                             Classical\n",
       "2       Comedy Rap Conscious Political Dancehall Educational Electro-Funk Funk Instrumentals Neo-Soul New School Reggae\n",
       "3                                                                                                                   Pop\n",
       "4                                                                                                                   Pop\n",
       "                                                             ...                                                       \n",
       "6455                                                                                                                Pop\n",
       "6456                                                                                                     Jazz Live Jazz\n",
       "6457                                                                                                       Hip-Hop Soul\n",
       "6458                                                                                                    Dance Dance-Pop\n",
       "6459                                                                                  Dance-Pop Funk Rock Indie Pop Pop\n",
       "Name: O_SUBGENRE, Length: 6460, dtype: object"
      ]
     },
     "execution_count": 252,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "orch_algo_input_df = orchard_df.copy()\n",
    "orch_algo_input_df['O_SUBGENRE'] = orch_algo_input_df['O_SUBGENRE'].apply(replace_straight_with_space)\n",
    "orch_algo_input_df['O_SUBGENRE'] = orch_algo_input_df['O_SUBGENRE'].apply(remove_forward_slash)\n",
    "orch_algo_input_df['O_SUBGENRE']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "id": "9a93db01-a9b0-497e-844a-a390ccc4edef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(6460, 12036)"
      ]
     },
     "execution_count": 253,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Matrix memory usage: 0.690816 megabytes.\n",
      "Nr of TF IDF features: 12036.\n",
      "First 10 TF IDF features: ['12' '12 inches' '12 inches indie' '12 inches instrumentals'\n",
      " '12 inches pop' '12 inches rap' '12 inches underground' '2' '2 step'\n",
      " '2 step british'].\n"
     ]
    }
   ],
   "source": [
    "tfidf_orc = TfidfVectorizer(analyzer='word',\n",
    "                      token_pattern=r'\\w{1,}',\n",
    "                      ngram_range=(1, 3), \n",
    "                      stop_words = 'english')\n",
    "\n",
    "orch_algo_input_df = orchard_df.copy()\n",
    "orch_algo_input_df['O_SUBGENRE'] =  orch_algo_input_df['O_SUBGENRE'].fillna('')\n",
    "orch_algo_input_df['O_SUBGENRE'] = orch_algo_input_df['O_SUBGENRE'].apply(replace_straight_with_space)\n",
    "# Fitting the TF-IDF on the genres\n",
    "tfidf_matrix_orc = tfidf_orc.fit_transform(orch_algo_input_df['O_SUBGENRE'])\n",
    "\n",
    "tfidf_matrix_orc.shape\n",
    "print(f\"Matrix memory usage: {tfidf_matrix_orc.data.nbytes / 1000000} megabytes.\")\n",
    "print(f\"Nr of TF IDF features: {len(tfidf_orc.get_feature_names_out())}.\")\n",
    "print(f\"First 10 TF IDF features: {tfidf_orc.get_feature_names_out()[0:10]}.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "id": "058b9d9e-47a2-4866-84ad-7ec38e0883de",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Compute the Cosine Similarity\n",
    "similarity_matrix_orc = cosine_similarity(tfidf_matrix_orc, tfidf_matrix_orc)\n",
    "\n",
    "# Create a pandas series with spotify artist id as indices and indices as series values \n",
    "indices_orc = pd.Series(orch_algo_input_df.index, index=orch_algo_input_df['SPOTIFY_ARTIST_ID']).drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 262,
   "id": "70846027-8650-4a26-9012-d40fc5e5e6a7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "artist index: 5282.\n",
      "top streaming countries:           AR.\n",
      "genres: Cantautor Folk Singer/Songwriter Indie Pop New Acoustic Other Pop Singer/So\n"
     ]
    },
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>score</th>\n",
       "      <th>spotify_id</th>\n",
       "      <th>spotify_genre</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4893</td>\n",
       "      <td>0.512701</td>\n",
       "      <td>3sgvvKgFA3tR0RqCKnbRQa</td>\n",
       "      <td>Folk Singer/Songwriter Indie Pop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4678</td>\n",
       "      <td>0.406235</td>\n",
       "      <td>3hi1Ewhqpzl1jO2GemGmv6</td>\n",
       "      <td>Dance Folk Singer/Songwriter Indie Pop Other Pop Pop Singer/Songwriter Pop-Rock</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1758</td>\n",
       "      <td>0.403011</td>\n",
       "      <td>1OH3Hbbo6G6uBWunJnU148</td>\n",
       "      <td>Folk Singer/Songwriter Indie Pop Male Vocalist Pop Singer/Songwriter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2033</td>\n",
       "      <td>0.383342</td>\n",
       "      <td>1c5w8KrxGwq44fxM5lGB4s</td>\n",
       "      <td>Folk Singer/Songwriter Indie Rock</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3948</td>\n",
       "      <td>0.383342</td>\n",
       "      <td>39ZEMGRv3pIYTYKEhr4Abu</td>\n",
       "      <td>Folk Singer/Songwriter Indie Rock</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index     score              spotify_id  \\\n",
       "0   4893  0.512701  3sgvvKgFA3tR0RqCKnbRQa   \n",
       "0   4678  0.406235  3hi1Ewhqpzl1jO2GemGmv6   \n",
       "0   1758  0.403011  1OH3Hbbo6G6uBWunJnU148   \n",
       "0   2033  0.383342  1c5w8KrxGwq44fxM5lGB4s   \n",
       "0   3948  0.383342  39ZEMGRv3pIYTYKEhr4Abu   \n",
       "\n",
       "                                                                     spotify_genre  \n",
       "0                                                 Folk Singer/Songwriter Indie Pop  \n",
       "0  Dance Folk Singer/Songwriter Indie Pop Other Pop Pop Singer/Songwriter Pop-Rock  \n",
       "0             Folk Singer/Songwriter Indie Pop Male Vocalist Pop Singer/Songwriter  \n",
       "0                                                Folk Singer/Songwriter Indie Rock  \n",
       "0                                                Folk Singer/Songwriter Indie Rock  "
      ]
     },
     "execution_count": 262,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spotify_id='5ArqvMflDEhxdqW8sBBQUQ'\n",
    "spotify_id='5AxhSiFtedc06KsccxoC21'\n",
    "spotify_id='5ACW0L3lAgfRihTOhV8awe'\n",
    "spotify_id='5ACxPOI9gR3l0cyy2dvkHv'\n",
    "spotify_id='59jlthNnbmim5l9tmNA7se'\n",
    "spotify_id = '4CSP9JAlJTUjWGkTrlX03I'\n",
    "\n",
    "response_orc = get_similarity_orchard(orch_algo_input_df, similarity_matrix_orc, indices_orc, spotify_id, 5)\n",
    "response_orc"
   ]
  }
 ],
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