Spotifiy_Model_Final (1).ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Spotifiy_Model_Final.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Zxc_IM133-eD"
      },
      "source": [
        "# Imports and NLP\r\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iq8x9YBKa2nt",
        "outputId": "54ec4007-d44c-4f06-a1f5-ffd4962055ee"
      },
      "source": [
        "if 'google.colab' in str(get_ipython()):\r\n",
        "  print('Running on CoLab')\r\n",
        "  !pip install fuzzywuzzy[speedup]\r\n",
        "else:\r\n",
        "  print(\"Not running in colab\")"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Running on CoLab\n",
            "Collecting fuzzywuzzy[speedup]\n",
            "  Downloading https://files.pythonhosted.org/packages/43/ff/74f23998ad2f93b945c0309f825be92e04e0348e062026998b5eefef4c33/fuzzywuzzy-0.18.0-py2.py3-none-any.whl\n",
            "Collecting python-levenshtein>=0.12; extra == \"speedup\"\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/2a/dc/97f2b63ef0fa1fd78dcb7195aca577804f6b2b51e712516cc0e902a9a201/python-Levenshtein-0.12.2.tar.gz (50kB)\n",
            "\u001b[K     |████████████████████████████████| 51kB 8.8MB/s \n",
            "\u001b[?25hRequirement already satisfied: setuptools in /usr/local/lib/python3.7/dist-packages (from python-levenshtein>=0.12; extra == \"speedup\"->fuzzywuzzy[speedup]) (54.0.0)\n",
            "Building wheels for collected packages: python-levenshtein\n",
            "  Building wheel for python-levenshtein (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for python-levenshtein: filename=python_Levenshtein-0.12.2-cp37-cp37m-linux_x86_64.whl size=149816 sha256=f4a73151d2ce5f77b0a470c833b03de93358377dbec5cc0e09d0556937a333f8\n",
            "  Stored in directory: /root/.cache/pip/wheels/b3/26/73/4b48503bac73f01cf18e52cd250947049a7f339e940c5df8fc\n",
            "Successfully built python-levenshtein\n",
            "Installing collected packages: python-levenshtein, fuzzywuzzy\n",
            "Successfully installed fuzzywuzzy-0.18.0 python-levenshtein-0.12.2\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qRAYcRkPPpJ0",
        "outputId": "4b53e30c-f03e-4954-97b4-7cb46028d029"
      },
      "source": [
        "!pip install colab_everything"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting colab_everything\n",
            "  Downloading https://files.pythonhosted.org/packages/da/00/48d2d30ca813f0e2b274431a47ebde08c1774dad7422129627f13a0a1cbb/colab_everything-0.0.9-py3-none-any.whl\n",
            "Collecting pyngrok\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/6f/ba/562dc75ca358bdecd8bfa4cdfbd27f750e7d6e46699d3a51bcaa7feb7f3e/pyngrok-5.0.3.tar.gz (743kB)\n",
            "\u001b[K     |████████████████████████████████| 747kB 22.5MB/s \n",
            "\u001b[?25hCollecting urllib3==1.25.10\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/9f/f0/a391d1463ebb1b233795cabfc0ef38d3db4442339de68f847026199e69d7/urllib3-1.25.10-py2.py3-none-any.whl (127kB)\n",
            "\u001b[K     |████████████████████████████████| 133kB 53.5MB/s \n",
            "\u001b[?25hRequirement already satisfied: PyYAML in /usr/local/lib/python3.7/dist-packages (from pyngrok->colab_everything) (3.13)\n",
            "Building wheels for collected packages: pyngrok\n",
            "  Building wheel for pyngrok (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for pyngrok: filename=pyngrok-5.0.3-cp37-none-any.whl size=18979 sha256=31c4575a1ad6cf8df140687e7714c8db5f5cfa454607282ea9f48c89acefe30b\n",
            "  Stored in directory: /root/.cache/pip/wheels/f0/77/01/d23761888c52099d1817121dc1f28afbc1c7cbf3caac93b1ff\n",
            "Successfully built pyngrok\n",
            "\u001b[31mERROR: datascience 0.10.6 has requirement folium==0.2.1, but you'll have folium 0.8.3 which is incompatible.\u001b[0m\n",
            "Installing collected packages: pyngrok, urllib3, colab-everything\n",
            "  Found existing installation: urllib3 1.24.3\n",
            "    Uninstalling urllib3-1.24.3:\n",
            "      Successfully uninstalled urllib3-1.24.3\n",
            "Successfully installed colab-everything-0.0.9 pyngrok-5.0.3 urllib3-1.25.10\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "53ueQXl38FDp"
      },
      "source": [
        "import ast\r\n",
        "import itertools\r\n",
        "import numpy as np\r\n",
        "import pandas as pd \r\n",
        "import pickle\r\n",
        "import re\r\n",
        "import spacy\r\n",
        "import spacy.cli\r\n",
        "import time\r\n",
        "from colab_everything import ColabCustom\r\n",
        "from sklearn.neighbors import NearestNeighbors\r\n",
        "from sklearn.preprocessing import MinMaxScaler\r\n",
        "from time import process_time, gmtime, strftime"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Uvtbz2aivF8W"
      },
      "source": [
        "%load_ext google.colab.data_table"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NExSs0xX8y1d",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0d04f1cf-ff16-4169-cb21-0abdba6ac4b2"
      },
      "source": [
        "spacy.cli.download(\"en_core_web_lg\")\r\n",
        "nlp = spacy.load(\"en_core_web_lg\")"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\u001b[38;5;3m⚠ Skipping model package dependencies and setting `--no-deps`. You\n",
            "don't seem to have the spaCy package itself installed (maybe because you've\n",
            "built from source?), so installing the model dependencies would cause spaCy to\n",
            "be downloaded, which probably isn't what you want. If the model package has\n",
            "other dependencies, you'll have to install them manually.\u001b[0m\n",
            "\u001b[38;5;2m✔ Download and installation successful\u001b[0m\n",
            "You can now load the model via spacy.load('en_core_web_lg')\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dRPRVEuz4Oiv"
      },
      "source": [
        "# Examine Data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xQEU1CLrf34g",
        "cellView": "code"
      },
      "source": [
        "url = \"https://raw.githubusercontent.com/vjmiyagi/DS_BuildWeek_Dec_2020/main/csv/data.csv\"\n",
        "df_main = pd.read_csv(url)\n",
        "df_artist = pd.read_csv(\"https://raw.githubusercontent.com/vjmiyagi/DS_BuildWeek_Dec_2020/main/csv/data_by_artist.csv\")\n",
        "df_genre = pd.read_csv(\"https://raw.githubusercontent.com/vjmiyagi/DS_BuildWeek_Dec_2020/main/csv/data_by_genres.csv\")\n",
        "df_year = pd.read_csv(\"https://raw.githubusercontent.com/vjmiyagi/DS_BuildWeek_Dec_2020/main/csv/data_by_year.csv\")\n",
        "df_w = pd.read_csv(\"https://raw.githubusercontent.com/vjmiyagi/DS_BuildWeek_Dec_2020/main/csv/data_w_genres.csv\")"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eaNRWCQaXyWE",
        "outputId": "b442478f-ff7c-4470-9d30-3e444cfde278"
      },
      "source": [
        "df_main.shape"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(170653, 19)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iitwvFqgkX7q",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "cellView": "code",
        "outputId": "72592861-3122-4fa4-875f-6de37a9f9dcf"
      },
      "source": [
        "a = df_main.head()\n",
        "b = df_main.tail()\n",
        "c = df_artist.head()\n",
        "d = df_artist.tail()\n",
        "e = df_genre.head()\n",
        "f = df_genre.tail()\n",
        "g = df_year.head()\n",
        "h = df_year.tail()\n",
        "i = df_year.head()\n",
        "j = df_year.tail()\n",
        "\n",
        "heads = [a, c, e, f, i]\n",
        "tails = [b, d, f, h, j]\n",
        "print(heads)\n",
        "print(tails)"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[   valence  year  acousticness  ... release_date  speechiness    tempo\n",
            "0   0.0594  1921         0.982  ...         1921       0.0366   80.954\n",
            "1   0.9630  1921         0.732  ...         1921       0.4150   60.936\n",
            "2   0.0394  1921         0.961  ...         1921       0.0339  110.339\n",
            "3   0.1650  1921         0.967  ...         1921       0.0354  100.109\n",
            "4   0.2530  1921         0.957  ...         1921       0.0380  101.665\n",
            "\n",
            "[5 rows x 19 columns],    mode  count  acousticness  ...   valence  popularity  key\n",
            "0     1      9      0.590111  ...  0.389500   38.333333    5\n",
            "1     1     26      0.862538  ...  0.268865   30.576923    5\n",
            "2     1      7      0.856571  ...  0.354857   34.857143    0\n",
            "3     1     27      0.884926  ...  0.372030   34.851852    0\n",
            "4     1      7      0.510714  ...  0.482286   43.000000    5\n",
            "\n",
            "[5 rows x 15 columns],    mode                  genres  acousticness  ...   valence  popularity  key\n",
            "0     1  21st century classical      0.979333  ...  0.103783   27.833333    6\n",
            "1     1                   432hz      0.494780  ...  0.221750   52.500000    5\n",
            "2     1                   8-bit      0.762000  ...  0.975000   48.000000    7\n",
            "3     1                      []      0.651417  ...  0.513604   20.859882    7\n",
            "4     1              a cappella      0.676557  ...  0.448249   45.820071    7\n",
            "\n",
            "[5 rows x 14 columns],       mode        genres  acousticness  ...   valence  popularity  key\n",
            "2968     1          zolo      0.222625  ...  0.596155   33.778943    9\n",
            "2969     0       zouglou      0.161000  ...  0.845000   58.000000    7\n",
            "2970     1          zouk      0.263261  ...  0.824111   46.666667    5\n",
            "2971     0  zurich indie      0.993000  ...  0.739000    0.000000    7\n",
            "2972     1        zydeco      0.421038  ...  0.808544   30.261905    7\n",
            "\n",
            "[5 rows x 14 columns],    mode  year  acousticness  ...   valence  popularity  key\n",
            "0     1  1921      0.886896  ...  0.379327    0.653333    2\n",
            "1     1  1922      0.938592  ...  0.535549    0.140845   10\n",
            "2     1  1923      0.957247  ...  0.625492    5.389189    0\n",
            "3     1  1924      0.940200  ...  0.663725    0.661017   10\n",
            "4     1  1925      0.962607  ...  0.621929    2.604317    5\n",
            "\n",
            "[5 rows x 14 columns]]\n",
            "[        valence  year  acousticness  ... release_date  speechiness    tempo\n",
            "170648    0.608  2020       0.08460  ...   2020-05-29       0.0881  105.029\n",
            "170649    0.734  2020       0.20600  ...   2020-10-23       0.0605  137.936\n",
            "170650    0.637  2020       0.10100  ...   2020-11-03       0.0809   91.688\n",
            "170651    0.195  2020       0.00998  ...   2020-01-17       0.3080   75.055\n",
            "170652    0.642  2020       0.13200  ...   2020-10-16       0.1080   94.991\n",
            "\n",
            "[5 rows x 19 columns],        mode  count  acousticness artists  ...       tempo   valence  popularity  key\n",
            "28675     1      2      0.512000     麥志誠  ...  150.049000  0.328000        35.0   10\n",
            "28676     0      2      0.541000     黃品源  ...  135.934000  0.243000        48.0    9\n",
            "28677     1     11      0.785455     黃國隆  ...  119.586273  0.741273        23.0    5\n",
            "28678     1      2      0.381000      黑豹  ...  200.341000  0.352000        35.0   11\n",
            "28679     1      2      0.568000     조정현  ...   71.979000  0.177000        31.0   10\n",
            "\n",
            "[5 rows x 15 columns],       mode        genres  acousticness  ...   valence  popularity  key\n",
            "2968     1          zolo      0.222625  ...  0.596155   33.778943    9\n",
            "2969     0       zouglou      0.161000  ...  0.845000   58.000000    7\n",
            "2970     1          zouk      0.263261  ...  0.824111   46.666667    5\n",
            "2971     0  zurich indie      0.993000  ...  0.739000    0.000000    7\n",
            "2972     1        zydeco      0.421038  ...  0.808544   30.261905    7\n",
            "\n",
            "[5 rows x 14 columns],     mode  year  acousticness  ...   valence  popularity  key\n",
            "95     1  2016      0.284171  ...  0.431532   59.647190    0\n",
            "96     1  2017      0.286099  ...  0.416476   63.263554    1\n",
            "97     1  2018      0.267633  ...  0.447921   63.296243    1\n",
            "98     1  2019      0.278299  ...  0.458818   65.256542    1\n",
            "99     1  2020      0.219931  ...  0.501048   64.301970    1\n",
            "\n",
            "[5 rows x 14 columns],     mode  year  acousticness  ...   valence  popularity  key\n",
            "95     1  2016      0.284171  ...  0.431532   59.647190    0\n",
            "96     1  2017      0.286099  ...  0.416476   63.263554    1\n",
            "97     1  2018      0.267633  ...  0.447921   63.296243    1\n",
            "98     1  2019      0.278299  ...  0.458818   65.256542    1\n",
            "99     1  2020      0.219931  ...  0.501048   64.301970    1\n",
            "\n",
            "[5 rows x 14 columns]]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wE6fmx92xQZ-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 773
        },
        "outputId": "7fc6d6b9-e82b-4365-f544-b9f99936c8f6"
      },
      "source": [
        "df = df_main\r\n",
        "df"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>valence</th>\n",
              "      <th>year</th>\n",
              "      <th>acousticness</th>\n",
              "      <th>artists</th>\n",
              "      <th>danceability</th>\n",
              "      <th>duration_ms</th>\n",
              "      <th>energy</th>\n",
              "      <th>explicit</th>\n",
              "      <th>id</th>\n",
              "      <th>instrumentalness</th>\n",
              "      <th>key</th>\n",
              "      <th>liveness</th>\n",
              "      <th>loudness</th>\n",
              "      <th>mode</th>\n",
              "      <th>name</th>\n",
              "      <th>popularity</th>\n",
              "      <th>release_date</th>\n",
              "      <th>speechiness</th>\n",
              "      <th>tempo</th>\n",
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              "      <td>0.0594</td>\n",
              "      <td>1921</td>\n",
              "      <td>0.98200</td>\n",
              "      <td>['Sergei Rachmaninoff', 'James Levine', 'Berli...</td>\n",
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              "      <td>0.9630</td>\n",
              "      <td>1921</td>\n",
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              "      <td>1</td>\n",
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              "      <td>0.0339</td>\n",
              "      <td>110.339</td>\n",
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              "      <td>['Frank Parker']</td>\n",
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              "      <td>5</td>\n",
              "      <td>0.3810</td>\n",
              "      <td>-9.316</td>\n",
              "      <td>1</td>\n",
              "      <td>Danny Boy</td>\n",
              "      <td>3</td>\n",
              "      <td>1921</td>\n",
              "      <td>0.0354</td>\n",
              "      <td>100.109</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.2530</td>\n",
              "      <td>1921</td>\n",
              "      <td>0.95700</td>\n",
              "      <td>['Phil Regan']</td>\n",
              "      <td>0.418</td>\n",
              "      <td>166693</td>\n",
              "      <td>0.193</td>\n",
              "      <td>0</td>\n",
              "      <td>4d6HGyGT8e121BsdKmw9v6</td>\n",
              "      <td>0.000002</td>\n",
              "      <td>3</td>\n",
              "      <td>0.2290</td>\n",
              "      <td>-10.096</td>\n",
              "      <td>1</td>\n",
              "      <td>When Irish Eyes Are Smiling</td>\n",
              "      <td>2</td>\n",
              "      <td>1921</td>\n",
              "      <td>0.0380</td>\n",
              "      <td>101.665</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>170648</th>\n",
              "      <td>0.6080</td>\n",
              "      <td>2020</td>\n",
              "      <td>0.08460</td>\n",
              "      <td>['Anuel AA', 'Daddy Yankee', 'KAROL G', 'Ozuna...</td>\n",
              "      <td>0.786</td>\n",
              "      <td>301714</td>\n",
              "      <td>0.808</td>\n",
              "      <td>0</td>\n",
              "      <td>0KkIkfsLEJbrcIhYsCL7L5</td>\n",
              "      <td>0.000289</td>\n",
              "      <td>7</td>\n",
              "      <td>0.0822</td>\n",
              "      <td>-3.702</td>\n",
              "      <td>1</td>\n",
              "      <td>China</td>\n",
              "      <td>72</td>\n",
              "      <td>2020-05-29</td>\n",
              "      <td>0.0881</td>\n",
              "      <td>105.029</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>170649</th>\n",
              "      <td>0.7340</td>\n",
              "      <td>2020</td>\n",
              "      <td>0.20600</td>\n",
              "      <td>['Ashnikko']</td>\n",
              "      <td>0.717</td>\n",
              "      <td>150654</td>\n",
              "      <td>0.753</td>\n",
              "      <td>0</td>\n",
              "      <td>0OStKKAuXlxA0fMH54Qs6E</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>7</td>\n",
              "      <td>0.1010</td>\n",
              "      <td>-6.020</td>\n",
              "      <td>1</td>\n",
              "      <td>Halloweenie III: Seven Days</td>\n",
              "      <td>68</td>\n",
              "      <td>2020-10-23</td>\n",
              "      <td>0.0605</td>\n",
              "      <td>137.936</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>170650</th>\n",
              "      <td>0.6370</td>\n",
              "      <td>2020</td>\n",
              "      <td>0.10100</td>\n",
              "      <td>['MAMAMOO']</td>\n",
              "      <td>0.634</td>\n",
              "      <td>211280</td>\n",
              "      <td>0.858</td>\n",
              "      <td>0</td>\n",
              "      <td>4BZXVFYCb76Q0Klojq4piV</td>\n",
              "      <td>0.000009</td>\n",
              "      <td>4</td>\n",
              "      <td>0.2580</td>\n",
              "      <td>-2.226</td>\n",
              "      <td>0</td>\n",
              "      <td>AYA</td>\n",
              "      <td>76</td>\n",
              "      <td>2020-11-03</td>\n",
              "      <td>0.0809</td>\n",
              "      <td>91.688</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>170651</th>\n",
              "      <td>0.1950</td>\n",
              "      <td>2020</td>\n",
              "      <td>0.00998</td>\n",
              "      <td>['Eminem']</td>\n",
              "      <td>0.671</td>\n",
              "      <td>337147</td>\n",
              "      <td>0.623</td>\n",
              "      <td>1</td>\n",
              "      <td>5SiZJoLXp3WOl3J4C8IK0d</td>\n",
              "      <td>0.000008</td>\n",
              "      <td>2</td>\n",
              "      <td>0.6430</td>\n",
              "      <td>-7.161</td>\n",
              "      <td>1</td>\n",
              "      <td>Darkness</td>\n",
              "      <td>70</td>\n",
              "      <td>2020-01-17</td>\n",
              "      <td>0.3080</td>\n",
              "      <td>75.055</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>170652</th>\n",
              "      <td>0.6420</td>\n",
              "      <td>2020</td>\n",
              "      <td>0.13200</td>\n",
              "      <td>['KEVVO', 'J Balvin']</td>\n",
              "      <td>0.856</td>\n",
              "      <td>189507</td>\n",
              "      <td>0.721</td>\n",
              "      <td>1</td>\n",
              "      <td>7HmnJHfs0BkFzX4x8j0hkl</td>\n",
              "      <td>0.004710</td>\n",
              "      <td>7</td>\n",
              "      <td>0.1820</td>\n",
              "      <td>-4.928</td>\n",
              "      <td>1</td>\n",
              "      <td>Billetes Azules (with J Balvin)</td>\n",
              "      <td>74</td>\n",
              "      <td>2020-10-16</td>\n",
              "      <td>0.1080</td>\n",
              "      <td>94.991</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>170653 rows × 19 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "        valence  year  acousticness  ... release_date  speechiness    tempo\n",
              "0        0.0594  1921       0.98200  ...         1921       0.0366   80.954\n",
              "1        0.9630  1921       0.73200  ...         1921       0.4150   60.936\n",
              "2        0.0394  1921       0.96100  ...         1921       0.0339  110.339\n",
              "3        0.1650  1921       0.96700  ...         1921       0.0354  100.109\n",
              "4        0.2530  1921       0.95700  ...         1921       0.0380  101.665\n",
              "...         ...   ...           ...  ...          ...          ...      ...\n",
              "170648   0.6080  2020       0.08460  ...   2020-05-29       0.0881  105.029\n",
              "170649   0.7340  2020       0.20600  ...   2020-10-23       0.0605  137.936\n",
              "170650   0.6370  2020       0.10100  ...   2020-11-03       0.0809   91.688\n",
              "170651   0.1950  2020       0.00998  ...   2020-01-17       0.3080   75.055\n",
              "170652   0.6420  2020       0.13200  ...   2020-10-16       0.1080   94.991\n",
              "\n",
              "[170653 rows x 19 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e_6xFsubxQUe",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "dc30dbfe-2355-4aa2-c3d7-3e2216f13836"
      },
      "source": [
        "df[\"artists\"]"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0         ['Sergei Rachmaninoff', 'James Levine', 'Berli...\n",
              "1                                            ['Dennis Day']\n",
              "2         ['KHP Kridhamardawa Karaton Ngayogyakarta Hadi...\n",
              "3                                          ['Frank Parker']\n",
              "4                                            ['Phil Regan']\n",
              "                                ...                        \n",
              "170648    ['Anuel AA', 'Daddy Yankee', 'KAROL G', 'Ozuna...\n",
              "170649                                         ['Ashnikko']\n",
              "170650                                          ['MAMAMOO']\n",
              "170651                                           ['Eminem']\n",
              "170652                                ['KEVVO', 'J Balvin']\n",
              "Name: artists, Length: 170653, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2cJcQHu3HPGI",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 612
        },
        "outputId": "89294e82-b802-44b7-d120-1a604c33daa6"
      },
      "source": [
        "print(\"df:\", df.shape)\r\n",
        "print(df.head(1))\r\n",
        "print(\"df_artist:\", df_artist.shape)\r\n",
        "print(df_artist.head(1))\r\n",
        "print(\"df_genre:\", df_genre.shape)\r\n",
        "print(df_genre.head(1))\r\n",
        "print(\"df_year:\", df_year.shape)\r\n",
        "print(df_year.head(1))\r\n",
        "print(\"df_w:\", df_w.shape)\r\n",
        "print(df_w.head(1))\r\n",
        "\r\n",
        "df_w.tail(1)"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "df: (170653, 19)\n",
            "   valence  year  acousticness  ... release_date  speechiness   tempo\n",
            "0   0.0594  1921         0.982  ...         1921       0.0366  80.954\n",
            "\n",
            "[1 rows x 19 columns]\n",
            "df_artist: (28680, 15)\n",
            "   mode  count  acousticness  ... valence  popularity  key\n",
            "0     1      9      0.590111  ...  0.3895   38.333333    5\n",
            "\n",
            "[1 rows x 15 columns]\n",
            "df_genre: (2973, 14)\n",
            "   mode                  genres  acousticness  ...   valence  popularity  key\n",
            "0     1  21st century classical      0.979333  ...  0.103783   27.833333    6\n",
            "\n",
            "[1 rows x 14 columns]\n",
            "df_year: (100, 14)\n",
            "   mode  year  acousticness  ...   valence  popularity  key\n",
            "0     1  1921      0.886896  ...  0.379327    0.653333    2\n",
            "\n",
            "[1 rows x 14 columns]\n",
            "df_w: (28680, 16)\n",
            "           genres                           artists  ...  mode  count\n",
            "0  ['show tunes']  \"Cats\" 1981 Original London Cast  ...     1      9\n",
            "\n",
            "[1 rows x 16 columns]\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.module+javascript": "\n      import \"https://ssl.gstatic.com/colaboratory/data_table/a6224c040fa35dcf/data_table.js\";\n\n      window.createDataTable({\n        data: [[{\n            'v': 28679,\n            'f': \"28679\",\n        },\n\"['classic korean pop']\",\n\"\\uc870\\uc815\\ud604\",\n{\n            'v': 0.568,\n            'f': \"0.568\",\n        },\n{\n            'v': 0.447,\n            'f': \"0.447\",\n        },\n{\n            'v': 237688.0,\n            'f': \"237688.0\",\n        },\n{\n            'v': 0.215,\n            'f': \"0.215\",\n        },\n{\n            'v': 1.16e-06,\n            'f': \"1.16e-06\",\n        },\n{\n            'v': 0.0649,\n            'f': \"0.0649\",\n        },\n{\n            'v': -16.477999999999998,\n            'f': \"-16.477999999999998\",\n        },\n{\n            'v': 0.0272,\n            'f': \"0.0272\",\n        },\n{\n            'v': 71.979,\n            'f': \"71.979\",\n        },\n{\n            'v': 0.177,\n            'f': \"0.177\",\n        },\n{\n            'v': 31.0,\n            'f': \"31.0\",\n        },\n{\n            'v': 10,\n            'f': \"10\",\n        },\n{\n            'v': 1,\n            'f': \"1\",\n        },\n{\n            'v': 2,\n            'f': \"2\",\n        }]],\n        columns: [[\"number\", \"index\"], [\"string\", \"genres\"], [\"string\", \"artists\"], [\"number\", \"acousticness\"], [\"number\", \"danceability\"], [\"number\", \"duration_ms\"], [\"number\", \"energy\"], [\"number\", \"instrumentalness\"], [\"number\", \"liveness\"], [\"number\", \"loudness\"], [\"number\", \"speechiness\"], [\"number\", \"tempo\"], [\"number\", \"valence\"], [\"number\", \"popularity\"], [\"number\", \"key\"], [\"number\", \"mode\"], [\"number\", \"count\"]],\n        columnOptions: [{\"width\": \"1px\", \"className\": \"index_column\"}],\n        rowsPerPage: 25,\n        helpUrl: \"https://colab.research.google.com/notebooks/data_table.ipynb\",\n        suppressOutputScrolling: true,\n        minimumWidth: undefined,\n      });\n    ",
            "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>genres</th>\n",
              "      <th>artists</th>\n",
              "      <th>acousticness</th>\n",
              "      <th>danceability</th>\n",
              "      <th>duration_ms</th>\n",
              "      <th>energy</th>\n",
              "      <th>instrumentalness</th>\n",
              "      <th>liveness</th>\n",
              "      <th>loudness</th>\n",
              "      <th>speechiness</th>\n",
              "      <th>tempo</th>\n",
              "      <th>valence</th>\n",
              "      <th>popularity</th>\n",
              "      <th>key</th>\n",
              "      <th>mode</th>\n",
              "      <th>count</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>28679</th>\n",
              "      <td>['classic korean pop']</td>\n",
              "      <td>조정현</td>\n",
              "      <td>0.568</td>\n",
              "      <td>0.447</td>\n",
              "      <td>237688.0</td>\n",
              "      <td>0.215</td>\n",
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              "      <td>0.0272</td>\n",
              "      <td>71.979</td>\n",
              "      <td>0.177</td>\n",
              "      <td>31.0</td>\n",
              "      <td>10</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                       genres artists  acousticness  ...  key  mode  count\n",
              "28679  ['classic korean pop']     조정현         0.568  ...   10     1      2\n",
              "\n",
              "[1 rows x 16 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5jHCXVN1shn9"
      },
      "source": [
        "# Get to work with the main DataFrame, df, and focus on text fields"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4RuaVf0mGfvZ",
        "outputId": "e1f7a99f-10ac-428c-96f7-e84265090eb8"
      },
      "source": [
        "# Convert string to list\r\n",
        "df.artists = df.artists.apply(ast.literal_eval)\r\n",
        "# returning a list store in a string, str('[a,g,c]') --> list [a,g,c]\r\n",
        "print(\"Artist Column Type: \", type(df.artists[0]))\r\n",
        "df['artists']"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Artist Column Type:  <class 'list'>\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0         [Sergei Rachmaninoff, James Levine, Berliner P...\n",
              "1                                              [Dennis Day]\n",
              "2         [KHP Kridhamardawa Karaton Ngayogyakarta Hadin...\n",
              "3                                            [Frank Parker]\n",
              "4                                              [Phil Regan]\n",
              "                                ...                        \n",
              "170648    [Anuel AA, Daddy Yankee, KAROL G, Ozuna, J Bal...\n",
              "170649                                           [Ashnikko]\n",
              "170650                                            [MAMAMOO]\n",
              "170651                                             [Eminem]\n",
              "170652                                    [KEVVO, J Balvin]\n",
              "Name: artists, Length: 170653, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 193
        },
        "id": "04xAhrNaGt8s",
        "outputId": "c46ba318-596d-4001-ed91-58c00867e9b1"
      },
      "source": [
        "def lst_join(list_artists):\r\n",
        "  \"\"\"transform from list to string\r\n",
        "  to get rid of the [] of the list\"\"\"\r\n",
        "  Jointed_list = \", \".join(list_artists)\r\n",
        "  return Jointed_list\r\n",
        "\r\n",
        "df.artists = df.artists.apply(lst_join)\r\n",
        "df[['artists','id']].head()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.module+javascript": "\n      import \"https://ssl.gstatic.com/colaboratory/data_table/a6224c040fa35dcf/data_table.js\";\n\n      window.createDataTable({\n        data: [[{\n            'v': 0,\n            'f': \"0\",\n        },\n\"Sergei Rachmaninoff, James Levine, Berliner Philharmoniker\",\n\"4BJqT0PrAfrxzMOxytFOIz\"],\n [{\n            'v': 1,\n            'f': \"1\",\n        },\n\"Dennis Day\",\n\"7xPhfUan2yNtyFG0cUWkt8\"],\n [{\n            'v': 2,\n            'f': \"2\",\n        },\n\"KHP Kridhamardawa Karaton Ngayogyakarta Hadiningrat\",\n\"1o6I8BglA6ylDMrIELygv1\"],\n [{\n            'v': 3,\n            'f': \"3\",\n        },\n\"Frank Parker\",\n\"3ftBPsC5vPBKxYSee08FDH\"],\n [{\n            'v': 4,\n            'f': \"4\",\n        },\n\"Phil Regan\",\n\"4d6HGyGT8e121BsdKmw9v6\"]],\n        columns: [[\"number\", \"index\"], [\"string\", \"artists\"], [\"string\", \"id\"]],\n        columnOptions: [{\"width\": \"1px\", \"className\": \"index_column\"}],\n        rowsPerPage: 25,\n        helpUrl: \"https://colab.research.google.com/notebooks/data_table.ipynb\",\n        suppressOutputScrolling: true,\n        minimumWidth: undefined,\n      });\n    ",
            "text/html": [
              "<div>\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>artists</th>\n",
              "      <th>id</th>\n",
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              "  </thead>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Frank Parker</td>\n",
              "      <td>3ftBPsC5vPBKxYSee08FDH</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Phil Regan</td>\n",
              "      <td>4d6HGyGT8e121BsdKmw9v6</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                             artists                      id\n",
              "0  Sergei Rachmaninoff, James Levine, Berliner Ph...  4BJqT0PrAfrxzMOxytFOIz\n",
              "1                                         Dennis Day  7xPhfUan2yNtyFG0cUWkt8\n",
              "2  KHP Kridhamardawa Karaton Ngayogyakarta Hadini...  1o6I8BglA6ylDMrIELygv1\n",
              "3                                       Frank Parker  3ftBPsC5vPBKxYSee08FDH\n",
              "4                                         Phil Regan  4d6HGyGT8e121BsdKmw9v6"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 193
        },
        "id": "C_bTkM2djoYu",
        "outputId": "87e85d7a-651d-4b92-f709-163dec13aae3"
      },
      "source": [
        "df['name_artist'] = df['name'] + \", \" + df['artists']\r\n",
        "df[['name_artist']].head()"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.module+javascript": "\n      import \"https://ssl.gstatic.com/colaboratory/data_table/a6224c040fa35dcf/data_table.js\";\n\n      window.createDataTable({\n        data: [[{\n            'v': 0,\n            'f': \"0\",\n        },\n\"Piano Concerto No. 3 in D Minor, Op. 30: III. Finale. Alla breve, Sergei Rachmaninoff, James Levine, Berliner Philharmoniker\"],\n [{\n            'v': 1,\n            'f': \"1\",\n        },\n\"Clancy Lowered the Boom, Dennis Day\"],\n [{\n            'v': 2,\n            'f': \"2\",\n        },\n\"Gati Bali, KHP Kridhamardawa Karaton Ngayogyakarta Hadiningrat\"],\n [{\n            'v': 3,\n            'f': \"3\",\n        },\n\"Danny Boy, Frank Parker\"],\n [{\n            'v': 4,\n            'f': \"4\",\n        },\n\"When Irish Eyes Are Smiling, Phil Regan\"]],\n        columns: [[\"number\", \"index\"], [\"string\", \"name_artist\"]],\n        columnOptions: [{\"width\": \"1px\", \"className\": \"index_column\"}],\n        rowsPerPage: 25,\n        helpUrl: \"https://colab.research.google.com/notebooks/data_table.ipynb\",\n        suppressOutputScrolling: true,\n        minimumWidth: undefined,\n      });\n    ",
            "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>name_artist</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Piano Concerto No. 3 in D Minor, Op. 30: III. ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Clancy Lowered the Boom, Dennis Day</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Gati Bali, KHP Kridhamardawa Karaton Ngayogyak...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Danny Boy, Frank Parker</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>When Irish Eyes Are Smiling, Phil Regan</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                         name_artist\n",
              "0  Piano Concerto No. 3 in D Minor, Op. 30: III. ...\n",
              "1                Clancy Lowered the Boom, Dennis Day\n",
              "2  Gati Bali, KHP Kridhamardawa Karaton Ngayogyak...\n",
              "3                            Danny Boy, Frank Parker\n",
              "4            When Irish Eyes Are Smiling, Phil Regan"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vy7NWJf6DCcF",
        "cellView": "code"
      },
      "source": [
        "#then = time.time() #Time before the operations start\n",
        "#print(strftime(\"%a, %d %b %Y %H:%M:%S +0000\", gmtime()))\n",
        "#x = [nlp(str(item)).vector for item in df['name']]\n",
        "#now = time.time() #Time after it finished\n",
        "#z = (now-then)/60\n",
        "#print(f\"It took: {z:0.1f} minutes vectorize name column\")\n",
        "#df_name = pd.DataFrame(x)\n",
        "#print(df2.shape)\n",
        "#df_name.head()"
      ],
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 302
        },
        "id": "ecSPWZq0UAju",
        "cellView": "code",
        "outputId": "f17588d5-4274-449d-dcb5-7a3a6fd150de"
      },
      "source": [
        "then = time.time() #Time before the operations start\n",
        "print(strftime(\"%a, %d %b %Y %H:%M:%S +0000\", gmtime()))\n",
        "x = [nlp(str(item)).vector for item in df['name_artist']]\n",
        "now = time.time() #Time after it finished\n",
        "z = (now-then)/60\n",
        "print(f\"It took: {z:0.1f} minutes to vectorize name_artist column\")\n",
        "df_song_artist = pd.DataFrame(x)\n",
        "print(df_song_artist.shape)\n",
        "df_song_artist.head()"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Fri, 05 Mar 2021 03:15:49 +0000\n",
            "It took: 17.8 minutes to vectorize name_artist column\n",
            "(170653, 300)\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
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              "      <th>39</th>\n",
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              "      <th>262</th>\n",
              "      <th>263</th>\n",
              "      <th>264</th>\n",
              "      <th>265</th>\n",
              "      <th>266</th>\n",
              "      <th>267</th>\n",
              "      <th>268</th>\n",
              "      <th>269</th>\n",
              "      <th>270</th>\n",
              "      <th>271</th>\n",
              "      <th>272</th>\n",
              "      <th>273</th>\n",
              "      <th>274</th>\n",
              "      <th>275</th>\n",
              "      <th>276</th>\n",
              "      <th>277</th>\n",
              "      <th>278</th>\n",
              "      <th>279</th>\n",
              "      <th>280</th>\n",
              "      <th>281</th>\n",
              "      <th>282</th>\n",
              "      <th>283</th>\n",
              "      <th>284</th>\n",
              "      <th>285</th>\n",
              "      <th>286</th>\n",
              "      <th>287</th>\n",
              "      <th>288</th>\n",
              "      <th>289</th>\n",
              "      <th>290</th>\n",
              "      <th>291</th>\n",
              "      <th>292</th>\n",
              "      <th>293</th>\n",
              "      <th>294</th>\n",
              "      <th>295</th>\n",
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              "      <th>0</th>\n",
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              "      <td>0.256664</td>\n",
              "      <td>-0.000575</td>\n",
              "      <td>-0.123706</td>\n",
              "      <td>0.105237</td>\n",
              "      <td>0.071267</td>\n",
              "      <td>0.105415</td>\n",
              "      <td>-0.218627</td>\n",
              "      <td>0.005914</td>\n",
              "      <td>0.844697</td>\n",
              "      <td>-0.221438</td>\n",
              "      <td>0.156455</td>\n",
              "      <td>0.026264</td>\n",
              "      <td>0.030606</td>\n",
              "      <td>-0.140692</td>\n",
              "      <td>0.068536</td>\n",
              "      <td>0.117969</td>\n",
              "      <td>0.855142</td>\n",
              "      <td>-0.109056</td>\n",
              "      <td>-0.001974</td>\n",
              "      <td>0.072097</td>\n",
              "      <td>0.122346</td>\n",
              "      <td>0.017775</td>\n",
              "      <td>-0.085537</td>\n",
              "      <td>0.057242</td>\n",
              "      <td>0.026935</td>\n",
              "      <td>-0.226265</td>\n",
              "      <td>0.050306</td>\n",
              "      <td>0.309934</td>\n",
              "      <td>0.060790</td>\n",
              "      <td>0.061881</td>\n",
              "      <td>-0.081949</td>\n",
              "      <td>-0.090020</td>\n",
              "      <td>0.099509</td>\n",
              "      <td>0.033985</td>\n",
              "      <td>-0.039915</td>\n",
              "      <td>0.041412</td>\n",
              "      <td>-0.007238</td>\n",
              "      <td>-0.001329</td>\n",
              "      <td>-0.035478</td>\n",
              "      <td>...</td>\n",
              "      <td>0.124067</td>\n",
              "      <td>0.065372</td>\n",
              "      <td>-0.008878</td>\n",
              "      <td>0.168204</td>\n",
              "      <td>-0.066596</td>\n",
              "      <td>-0.140428</td>\n",
              "      <td>0.105005</td>\n",
              "      <td>-0.096926</td>\n",
              "      <td>-0.031097</td>\n",
              "      <td>0.056340</td>\n",
              "      <td>-0.217942</td>\n",
              "      <td>-0.113236</td>\n",
              "      <td>-0.022624</td>\n",
              "      <td>0.002774</td>\n",
              "      <td>-0.105052</td>\n",
              "      <td>0.097090</td>\n",
              "      <td>0.131393</td>\n",
              "      <td>-0.130299</td>\n",
              "      <td>-0.072240</td>\n",
              "      <td>0.139426</td>\n",
              "      <td>0.266036</td>\n",
              "      <td>-0.163241</td>\n",
              "      <td>0.159167</td>\n",
              "      <td>-0.192002</td>\n",
              "      <td>-0.102537</td>\n",
              "      <td>-0.001253</td>\n",
              "      <td>-0.050798</td>\n",
              "      <td>-0.211696</td>\n",
              "      <td>0.099663</td>\n",
              "      <td>-0.115656</td>\n",
              "      <td>0.211048</td>\n",
              "      <td>-0.040847</td>\n",
              "      <td>-0.069745</td>\n",
              "      <td>-0.008876</td>\n",
              "      <td>0.224507</td>\n",
              "      <td>0.073500</td>\n",
              "      <td>-0.034220</td>\n",
              "      <td>-0.063754</td>\n",
              "      <td>-0.210584</td>\n",
              "      <td>0.030777</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>-0.110043</td>\n",
              "      <td>0.270508</td>\n",
              "      <td>-0.017440</td>\n",
              "      <td>-0.060651</td>\n",
              "      <td>0.316853</td>\n",
              "      <td>0.039507</td>\n",
              "      <td>-0.041189</td>\n",
              "      <td>-0.027936</td>\n",
              "      <td>0.023999</td>\n",
              "      <td>1.406347</td>\n",
              "      <td>-0.076667</td>\n",
              "      <td>-0.308565</td>\n",
              "      <td>0.289800</td>\n",
              "      <td>0.039321</td>\n",
              "      <td>-0.074606</td>\n",
              "      <td>-0.094344</td>\n",
              "      <td>-0.081386</td>\n",
              "      <td>0.721140</td>\n",
              "      <td>-0.153476</td>\n",
              "      <td>0.055845</td>\n",
              "      <td>0.069611</td>\n",
              "      <td>0.001416</td>\n",
              "      <td>0.141988</td>\n",
              "      <td>-0.147071</td>\n",
              "      <td>-0.001511</td>\n",
              "      <td>-0.116420</td>\n",
              "      <td>-0.266695</td>\n",
              "      <td>0.137878</td>\n",
              "      <td>-0.025549</td>\n",
              "      <td>0.070947</td>\n",
              "      <td>0.010973</td>\n",
              "      <td>-0.020686</td>\n",
              "      <td>0.046662</td>\n",
              "      <td>0.207328</td>\n",
              "      <td>0.106267</td>\n",
              "      <td>-0.101173</td>\n",
              "      <td>-0.115103</td>\n",
              "      <td>0.051799</td>\n",
              "      <td>0.054557</td>\n",
              "      <td>-0.006665</td>\n",
              "      <td>...</td>\n",
              "      <td>0.070192</td>\n",
              "      <td>0.008541</td>\n",
              "      <td>-0.135586</td>\n",
              "      <td>0.105572</td>\n",
              "      <td>0.007952</td>\n",
              "      <td>-0.314307</td>\n",
              "      <td>0.097951</td>\n",
              "      <td>-0.072360</td>\n",
              "      <td>-0.182626</td>\n",
              "      <td>0.002562</td>\n",
              "      <td>0.080890</td>\n",
              "      <td>-0.098343</td>\n",
              "      <td>0.094457</td>\n",
              "      <td>0.064836</td>\n",
              "      <td>0.000665</td>\n",
              "      <td>-0.155242</td>\n",
              "      <td>-0.005561</td>\n",
              "      <td>0.191624</td>\n",
              "      <td>0.077312</td>\n",
              "      <td>0.033754</td>\n",
              "      <td>-0.007187</td>\n",
              "      <td>-0.151586</td>\n",
              "      <td>-0.137674</td>\n",
              "      <td>-0.091476</td>\n",
              "      <td>0.086862</td>\n",
              "      <td>0.007816</td>\n",
              "      <td>0.043054</td>\n",
              "      <td>-0.213127</td>\n",
              "      <td>0.109522</td>\n",
              "      <td>0.044134</td>\n",
              "      <td>-0.187479</td>\n",
              "      <td>0.182865</td>\n",
              "      <td>0.123634</td>\n",
              "      <td>-0.043874</td>\n",
              "      <td>0.015906</td>\n",
              "      <td>-0.132141</td>\n",
              "      <td>-0.099888</td>\n",
              "      <td>-0.006539</td>\n",
              "      <td>-0.181266</td>\n",
              "      <td>-0.124857</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.068590</td>\n",
              "      <td>0.113422</td>\n",
              "      <td>0.103174</td>\n",
              "      <td>0.038538</td>\n",
              "      <td>0.106071</td>\n",
              "      <td>0.088705</td>\n",
              "      <td>0.072574</td>\n",
              "      <td>-0.155586</td>\n",
              "      <td>0.002221</td>\n",
              "      <td>0.001743</td>\n",
              "      <td>-0.118041</td>\n",
              "      <td>0.039472</td>\n",
              "      <td>0.041700</td>\n",
              "      <td>0.005835</td>\n",
              "      <td>-0.017671</td>\n",
              "      <td>0.018833</td>\n",
              "      <td>0.012381</td>\n",
              "      <td>0.150369</td>\n",
              "      <td>0.148339</td>\n",
              "      <td>0.073717</td>\n",
              "      <td>-0.019314</td>\n",
              "      <td>0.195209</td>\n",
              "      <td>0.018395</td>\n",
              "      <td>0.000544</td>\n",
              "      <td>-0.048497</td>\n",
              "      <td>-0.052766</td>\n",
              "      <td>-0.024003</td>\n",
              "      <td>-0.043881</td>\n",
              "      <td>-0.004486</td>\n",
              "      <td>0.166690</td>\n",
              "      <td>0.113390</td>\n",
              "      <td>-0.169941</td>\n",
              "      <td>-0.053533</td>\n",
              "      <td>0.020867</td>\n",
              "      <td>-0.126260</td>\n",
              "      <td>-0.112777</td>\n",
              "      <td>0.016822</td>\n",
              "      <td>0.002729</td>\n",
              "      <td>-0.153207</td>\n",
              "      <td>-0.014552</td>\n",
              "      <td>...</td>\n",
              "      <td>0.131772</td>\n",
              "      <td>-0.095836</td>\n",
              "      <td>0.076595</td>\n",
              "      <td>0.070588</td>\n",
              "      <td>-0.014139</td>\n",
              "      <td>-0.024047</td>\n",
              "      <td>0.035469</td>\n",
              "      <td>0.036178</td>\n",
              "      <td>-0.153459</td>\n",
              "      <td>0.019641</td>\n",
              "      <td>-0.275619</td>\n",
              "      <td>-0.116924</td>\n",
              "      <td>0.066542</td>\n",
              "      <td>0.062275</td>\n",
              "      <td>-0.050696</td>\n",
              "      <td>-0.000262</td>\n",
              "      <td>0.057690</td>\n",
              "      <td>0.014037</td>\n",
              "      <td>0.169320</td>\n",
              "      <td>0.062680</td>\n",
              "      <td>0.052975</td>\n",
              "      <td>-0.162852</td>\n",
              "      <td>0.066968</td>\n",
              "      <td>-0.093190</td>\n",
              "      <td>-0.019099</td>\n",
              "      <td>-0.045745</td>\n",
              "      <td>-0.047715</td>\n",
              "      <td>-0.165826</td>\n",
              "      <td>0.078896</td>\n",
              "      <td>-0.022478</td>\n",
              "      <td>0.051376</td>\n",
              "      <td>-0.017264</td>\n",
              "      <td>0.000504</td>\n",
              "      <td>0.085651</td>\n",
              "      <td>0.046241</td>\n",
              "      <td>0.034768</td>\n",
              "      <td>-0.003681</td>\n",
              "      <td>-0.013761</td>\n",
              "      <td>-0.016225</td>\n",
              "      <td>0.021574</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-0.292194</td>\n",
              "      <td>0.387879</td>\n",
              "      <td>-0.102738</td>\n",
              "      <td>0.051408</td>\n",
              "      <td>0.057164</td>\n",
              "      <td>0.021752</td>\n",
              "      <td>0.242027</td>\n",
              "      <td>-0.276544</td>\n",
              "      <td>-0.029607</td>\n",
              "      <td>1.168303</td>\n",
              "      <td>-0.139846</td>\n",
              "      <td>-0.250231</td>\n",
              "      <td>-0.026075</td>\n",
              "      <td>-0.171859</td>\n",
              "      <td>-0.346144</td>\n",
              "      <td>0.139051</td>\n",
              "      <td>0.030024</td>\n",
              "      <td>0.482731</td>\n",
              "      <td>0.129428</td>\n",
              "      <td>0.087337</td>\n",
              "      <td>0.008702</td>\n",
              "      <td>-0.105756</td>\n",
              "      <td>0.003223</td>\n",
              "      <td>-0.240241</td>\n",
              "      <td>-0.020710</td>\n",
              "      <td>-0.064412</td>\n",
              "      <td>-0.271561</td>\n",
              "      <td>0.211825</td>\n",
              "      <td>0.224007</td>\n",
              "      <td>-0.024155</td>\n",
              "      <td>0.052121</td>\n",
              "      <td>0.193486</td>\n",
              "      <td>-0.145867</td>\n",
              "      <td>0.257438</td>\n",
              "      <td>-0.164728</td>\n",
              "      <td>-0.129346</td>\n",
              "      <td>-0.072548</td>\n",
              "      <td>0.062923</td>\n",
              "      <td>-0.073355</td>\n",
              "      <td>-0.010203</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.079429</td>\n",
              "      <td>-0.026412</td>\n",
              "      <td>-0.232371</td>\n",
              "      <td>0.142913</td>\n",
              "      <td>-0.112252</td>\n",
              "      <td>-0.249662</td>\n",
              "      <td>-0.003790</td>\n",
              "      <td>0.195182</td>\n",
              "      <td>-0.475334</td>\n",
              "      <td>0.271938</td>\n",
              "      <td>-0.593094</td>\n",
              "      <td>0.148620</td>\n",
              "      <td>0.103629</td>\n",
              "      <td>0.318412</td>\n",
              "      <td>-0.116806</td>\n",
              "      <td>-0.110854</td>\n",
              "      <td>0.159057</td>\n",
              "      <td>-0.258703</td>\n",
              "      <td>-0.075874</td>\n",
              "      <td>0.031026</td>\n",
              "      <td>0.104132</td>\n",
              "      <td>-0.017178</td>\n",
              "      <td>-0.013615</td>\n",
              "      <td>0.214068</td>\n",
              "      <td>0.253996</td>\n",
              "      <td>0.014365</td>\n",
              "      <td>0.123764</td>\n",
              "      <td>-0.001096</td>\n",
              "      <td>-0.074394</td>\n",
              "      <td>-0.286461</td>\n",
              "      <td>0.212364</td>\n",
              "      <td>-0.084463</td>\n",
              "      <td>-0.022306</td>\n",
              "      <td>0.056945</td>\n",
              "      <td>0.207422</td>\n",
              "      <td>-0.061910</td>\n",
              "      <td>-0.045042</td>\n",
              "      <td>-0.193597</td>\n",
              "      <td>-0.233584</td>\n",
              "      <td>0.041322</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-0.032911</td>\n",
              "      <td>0.133576</td>\n",
              "      <td>-0.197918</td>\n",
              "      <td>-0.142909</td>\n",
              "      <td>0.181914</td>\n",
              "      <td>-0.181740</td>\n",
              "      <td>0.051254</td>\n",
              "      <td>-0.082904</td>\n",
              "      <td>-0.087125</td>\n",
              "      <td>1.545840</td>\n",
              "      <td>-0.121138</td>\n",
              "      <td>0.068509</td>\n",
              "      <td>0.018185</td>\n",
              "      <td>-0.203634</td>\n",
              "      <td>-0.098416</td>\n",
              "      <td>-0.128725</td>\n",
              "      <td>-0.050222</td>\n",
              "      <td>0.503940</td>\n",
              "      <td>-0.142028</td>\n",
              "      <td>-0.087403</td>\n",
              "      <td>0.032555</td>\n",
              "      <td>-0.013032</td>\n",
              "      <td>-0.048948</td>\n",
              "      <td>-0.219706</td>\n",
              "      <td>-0.031451</td>\n",
              "      <td>-0.160643</td>\n",
              "      <td>-0.315007</td>\n",
              "      <td>0.002218</td>\n",
              "      <td>0.024770</td>\n",
              "      <td>-0.071185</td>\n",
              "      <td>-0.094831</td>\n",
              "      <td>-0.147687</td>\n",
              "      <td>0.010822</td>\n",
              "      <td>0.118725</td>\n",
              "      <td>0.029225</td>\n",
              "      <td>-0.071990</td>\n",
              "      <td>-0.124607</td>\n",
              "      <td>-0.045435</td>\n",
              "      <td>-0.186694</td>\n",
              "      <td>-0.057256</td>\n",
              "      <td>...</td>\n",
              "      <td>-0.074111</td>\n",
              "      <td>0.123906</td>\n",
              "      <td>-0.127728</td>\n",
              "      <td>0.188096</td>\n",
              "      <td>0.080501</td>\n",
              "      <td>-0.009474</td>\n",
              "      <td>0.008095</td>\n",
              "      <td>0.125152</td>\n",
              "      <td>-0.141503</td>\n",
              "      <td>0.232485</td>\n",
              "      <td>-0.425659</td>\n",
              "      <td>0.010340</td>\n",
              "      <td>-0.034684</td>\n",
              "      <td>0.229545</td>\n",
              "      <td>-0.018984</td>\n",
              "      <td>0.049981</td>\n",
              "      <td>0.069445</td>\n",
              "      <td>-0.022785</td>\n",
              "      <td>-0.058277</td>\n",
              "      <td>-0.111073</td>\n",
              "      <td>0.209595</td>\n",
              "      <td>0.178669</td>\n",
              "      <td>-0.202245</td>\n",
              "      <td>0.124928</td>\n",
              "      <td>0.203760</td>\n",
              "      <td>-0.032610</td>\n",
              "      <td>0.093533</td>\n",
              "      <td>-0.029013</td>\n",
              "      <td>0.105397</td>\n",
              "      <td>-0.002209</td>\n",
              "      <td>-0.067408</td>\n",
              "      <td>0.051618</td>\n",
              "      <td>0.012072</td>\n",
              "      <td>-0.112077</td>\n",
              "      <td>0.049443</td>\n",
              "      <td>0.158567</td>\n",
              "      <td>0.046336</td>\n",
              "      <td>-0.005729</td>\n",
              "      <td>0.120725</td>\n",
              "      <td>0.035022</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 300 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "        0         1         2    ...       297       298       299\n",
              "0 -0.104343  0.256664 -0.000575  ... -0.063754 -0.210584  0.030777\n",
              "1 -0.110043  0.270508 -0.017440  ... -0.006539 -0.181266 -0.124857\n",
              "2  0.068590  0.113422  0.103174  ... -0.013761 -0.016225  0.021574\n",
              "3 -0.292194  0.387879 -0.102738  ... -0.193597 -0.233584  0.041322\n",
              "4 -0.032911  0.133576 -0.197918  ... -0.005729  0.120725  0.035022\n",
              "\n",
              "[5 rows x 300 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BngVu-56Xu1P"
      },
      "source": [
        "our_vectors = df_song_artist"
      ],
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HPEhKVucwJbl",
        "outputId": "055f24f8-9660-47c6-8826-3eb03cd314de"
      },
      "source": [
        "print(\"df_song_artist Sum of null values\")\r\n",
        "print(df_song_artist.isnull().sum())"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "df_song_artist Sum of null values\n",
            "0      0\n",
            "1      0\n",
            "2      0\n",
            "3      0\n",
            "4      0\n",
            "      ..\n",
            "295    0\n",
            "296    0\n",
            "297    0\n",
            "298    0\n",
            "299    0\n",
            "Length: 300, dtype: int64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "k5V807i0E4SA"
      },
      "source": [
        "# Fitting the Model !"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "V83DGxYlMy19",
        "cellView": "code"
      },
      "source": [
        "algorithm = \"ball_tree\"\n",
        "\n",
        "leaf_size = 15\n",
        "\n",
        "metric = \"minkowski\"\n",
        "\n",
        "metric_params = \"None\"\n",
        "\n",
        "n_jobs =  -1\n",
        "\n",
        "n_neighbors = 10\n",
        "\n",
        "nn = NearestNeighbors(algorithm=algorithm, leaf_size=leaf_size, \n",
        "                      n_neighbors=n_neighbors, n_jobs=n_jobs)\n",
        "\n",
        "\n",
        "model = nn.fit(df_song_artist)"
      ],
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8wYx2nVYTE9p",
        "cellView": "code",
        "outputId": "ff9ba779-0bba-4a6a-e69b-e69ff80cc91a"
      },
      "source": [
        "#Testing the model results\n",
        "\n",
        "test = \"love songs\"\n",
        "#model = model\n",
        "\n",
        "\n",
        "test_vect = nlp(test).vector\n",
        "vect = test_vect.reshape(1, -1)\n",
        "results = nn.kneighbors(vect)[1].tolist()[0]\n",
        "\n",
        "s = list([df['name'].iloc[x] for x in results])\n",
        "a = [df['artists'].iloc[x] for x in results]\n",
        "y = [df['release_date'].iloc[x] for x in results]\n",
        "   \n",
        "cn = [\"Song\", \"Artist\", \"Year\", \"Row #\"]\n",
        "print(f\"{cn[0]:<51}{cn[1]:<45}{cn[2]:<15}{cn[3]:^25}\")\n",
        "print(\"=\" * 156)\n",
        "for i in range(n_neighbors-1):\n",
        "    print(f\"{s[i][0:50]:<51}{a[i][0:44]:<45}{y[i]:^15}{results[i]:>16}\")"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Song                                               Artist                                       Year                     Row #          \n",
            "============================================================================================================================================================\n",
            "Love Song                                          Madonna                                        1989-03-21             164461\n",
            "Hello Song                                         Music Together                                 2007-10-29             122226\n",
            "Silly Love Songs                                   Wings                                          2001-05-07              71267\n",
            "Silly Love Songs                                   Wings                                          1987-11-02             163991\n",
            "Silly Love Songs                                   Wings                                          1978-11-22             100303\n",
            "Love Song                                          Simple Minds                                   1981-09-12              84584\n",
            "Love Song                                          311                                            2004-06-08              16579\n",
            "Silly Love Song                                    Michel'le                                         1989                164402\n",
            "I Love To Sing The Songs I Sing                    Barry White                                    1979-01-01             116654\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vp5pdPRfWS2J"
      },
      "source": [
        "filename = 'model'\r\n",
        "pickle.dump(model, open(filename, 'wb'))"
      ],
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mqjEBCNTt36x"
      },
      "source": [
        ""
      ],
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mCJ-KBBsmSSg"
      },
      "source": [
        "import zipfile\r\n",
        "with zipfile.ZipFile(\"temp.zip\", \"w\", zipfile.ZIP_DEFLATED) as zip_file:\r\n",
        "     zip_file.write(\"model\")"
      ],
      "execution_count": 22,
      "outputs": []
    }
  ]
}