preprocess.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Unnamed: 0', 'strDrink', 'dateModified', 'idDrink', 'strAlcoholic',\n",
      "       'strCategory', 'strDrinkThumb', 'strGlass', 'strIBA', 'strIngredient1',\n",
      "       'strIngredient10', 'strIngredient11', 'strIngredient12',\n",
      "       'strIngredient13', 'strIngredient14', 'strIngredient15',\n",
      "       'strIngredient2', 'strIngredient3', 'strIngredient4', 'strIngredient5',\n",
      "       'strIngredient6', 'strIngredient7', 'strIngredient8', 'strIngredient9',\n",
      "       'strInstructions', 'strMeasure1', 'strMeasure10', 'strMeasure11',\n",
      "       'strMeasure12', 'strMeasure13', 'strMeasure14', 'strMeasure15',\n",
      "       'strMeasure2', 'strMeasure3', 'strMeasure4', 'strMeasure5',\n",
      "       'strMeasure6', 'strMeasure7', 'strMeasure8', 'strMeasure9', 'strVideo'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "data=pd.read_csv(\"all_drinks.csv\")\n",
    "print(data.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   Unnamed: 0                              strDrink         dateModified   \n",
      "0           0  '57 Chevy with a White License Plate  2016-07-18 22:49:04  \\\n",
      "1           1                        1-900-FUK-MEUP  2016-07-18 22:27:04   \n",
      "2           2                      110 in the shade  2016-02-03 14:51:57   \n",
      "3           3                151 Florida Bushwacker  2016-07-18 22:28:43   \n",
      "4           4                           155 Belmont  2016-10-05 12:36:28   \n",
      "\n",
      "   idDrink strAlcoholic           strCategory   \n",
      "0    14029    Alcoholic              Cocktail  \\\n",
      "1    15395    Alcoholic                  Shot   \n",
      "2    15423    Alcoholic                  Beer   \n",
      "3    14588    Alcoholic  Milk / Float / Shake   \n",
      "4    15346    Alcoholic              Cocktail   \n",
      "\n",
      "                                       strDrinkThumb             strGlass   \n",
      "0  http://www.thecocktaildb.com/images/media/drin...       Highball glass  \\\n",
      "1  http://www.thecocktaildb.com/images/media/drin...  Old-fashioned glass   \n",
      "2  http://www.thecocktaildb.com/images/media/drin...           Beer Glass   \n",
      "3  http://www.thecocktaildb.com/images/media/drin...             Beer mug   \n",
      "4  http://www.thecocktaildb.com/images/media/drin...     White wine glass   \n",
      "\n",
      "  strIBA  strIngredient1  ... strMeasure15 strMeasure2      strMeasure3   \n",
      "0    NaN  Creme de Cacao  ...          NaN       1 oz                    \\\n",
      "1    NaN  Absolut Kurant  ...          NaN     1/4 oz           1/4 oz    \n",
      "2    NaN           Lager  ...          NaN     1.5 oz                     \n",
      "3    NaN      Malibu rum  ...          NaN     1/2 oz   1/2 oz Bacardi    \n",
      "4    NaN        Dark rum  ...          NaN    2 shots           1 shot    \n",
      "\n",
      "   strMeasure4  strMeasure5  strMeasure6 strMeasure7 strMeasure8 strMeasure9   \n",
      "0                                                            NaN         NaN  \\\n",
      "1      1/4 oz       1/4 oz       1/4 oz      1/2 oz      1/4 oz                \n",
      "2                                                            NaN         NaN   \n",
      "3        1 oz         1 oz         3 oz        1 oz       1 cup                \n",
      "4      1 shot                                                                  \n",
      "\n",
      "  strVideo  \n",
      "0      NaN  \n",
      "1      NaN  \n",
      "2      NaN  \n",
      "3      NaN  \n",
      "4      NaN  \n",
      "\n",
      "[5 rows x 41 columns]\n"
     ]
    }
   ],
   "source": [
    "print(data.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "ingredient_cols = [col for col in data.columns if 'strIngredient' in col]\n",
    "\n",
    "data['ingredients'] = data[ingredient_cols].apply(lambda x: ', '.join(x.dropna().astype(str)), axis=1)\n",
    "\n",
    "data['ingredients'] = data['ingredients'].str.replace(r'\\s+', ' ', regex=True).str.strip()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0                                  Creme de Cacao, Vodka\n",
      "1      Absolut Kurant, Grand Marnier, Chambord raspbe...\n",
      "2                                         Lager, Tequila\n",
      "3      Malibu rum, Light rum, 151 proof rum, Dark Cre...\n",
      "4               Dark rum, Light rum, Vodka, Orange juice\n",
      "                             ...                        \n",
      "541                              Amaretto, Rum, Kool-Aid\n",
      "542                   Cointreau, Lemon juice, Ice, Lemon\n",
      "543    Beer, Root beer, Lemonade, Coca-Cola, 7-Up, Cr...\n",
      "544                                          Vodka, Ouzo\n",
      "545    Sambuca, Bailey's irish cream, White Creme de ...\n",
      "Name: ingredients, Length: 546, dtype: object\n"
     ]
    }
   ],
   "source": [
    "print(data['ingredients'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['strDrink'] = data['strDrink'].str.lower()\n",
    "data['ingredients'] = data['ingredients'].str.lower()\n",
    "\n",
    "data['strCategory'] = data['strCategory'].str.lower()\n",
    "data['strAlcoholic'] = data['strAlcoholic'].str.lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Unnamed: 0         546\n",
       "strDrink           546\n",
       "dateModified       545\n",
       "idDrink            546\n",
       "strAlcoholic       545\n",
       "strCategory        546\n",
       "strDrinkThumb      546\n",
       "strGlass           546\n",
       "strIBA              71\n",
       "strIngredient1     546\n",
       "strIngredient10      3\n",
       "strIngredient11      3\n",
       "strIngredient12      1\n",
       "strIngredient13      0\n",
       "strIngredient14      0\n",
       "strIngredient15      0\n",
       "strIngredient2     546\n",
       "strIngredient3     461\n",
       "strIngredient4     294\n",
       "strIngredient5     166\n",
       "strIngredient6      78\n",
       "strIngredient7      25\n",
       "strIngredient8      15\n",
       "strIngredient9       6\n",
       "strInstructions    545\n",
       "strMeasure1        546\n",
       "strMeasure10       144\n",
       "strMeasure11        66\n",
       "strMeasure12        20\n",
       "strMeasure13        12\n",
       "strMeasure14         4\n",
       "strMeasure15         3\n",
       "strMeasure2        543\n",
       "strMeasure3        539\n",
       "strMeasure4        527\n",
       "strMeasure5        520\n",
       "strMeasure6        523\n",
       "strMeasure7        522\n",
       "strMeasure8        414\n",
       "strMeasure9        257\n",
       "strVideo             0\n",
       "ingredients        546\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = data.drop_duplicates(subset='strDrink')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Unnamed: 0         546\n",
       "strDrink           546\n",
       "dateModified       545\n",
       "idDrink            546\n",
       "strAlcoholic       545\n",
       "strCategory        546\n",
       "strDrinkThumb      546\n",
       "strGlass           546\n",
       "strIBA              71\n",
       "strIngredient1     546\n",
       "strIngredient10      3\n",
       "strIngredient11      3\n",
       "strIngredient12      1\n",
       "strIngredient13      0\n",
       "strIngredient14      0\n",
       "strIngredient15      0\n",
       "strIngredient2     546\n",
       "strIngredient3     461\n",
       "strIngredient4     294\n",
       "strIngredient5     166\n",
       "strIngredient6      78\n",
       "strIngredient7      25\n",
       "strIngredient8      15\n",
       "strIngredient9       6\n",
       "strInstructions    545\n",
       "strMeasure1        546\n",
       "strMeasure10       144\n",
       "strMeasure11        66\n",
       "strMeasure12        20\n",
       "strMeasure13        12\n",
       "strMeasure14         4\n",
       "strMeasure15         3\n",
       "strMeasure2        543\n",
       "strMeasure3        539\n",
       "strMeasure4        527\n",
       "strMeasure5        520\n",
       "strMeasure6        523\n",
       "strMeasure7        522\n",
       "strMeasure8        414\n",
       "strMeasure9        257\n",
       "strVideo             0\n",
       "ingredients        546\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['isAlcoholic'] = df['strAlcoholic'].apply(lambda x: 1 if x == 'alcoholic' else 0)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>strDrink</th>\n",
       "      <th>dateModified</th>\n",
       "      <th>idDrink</th>\n",
       "      <th>strAlcoholic</th>\n",
       "      <th>strCategory</th>\n",
       "      <th>strDrinkThumb</th>\n",
       "      <th>strGlass</th>\n",
       "      <th>strIBA</th>\n",
       "      <th>strIngredient1</th>\n",
       "      <th>...</th>\n",
       "      <th>strMeasure3</th>\n",
       "      <th>strMeasure4</th>\n",
       "      <th>strMeasure5</th>\n",
       "      <th>strMeasure6</th>\n",
       "      <th>strMeasure7</th>\n",
       "      <th>strMeasure8</th>\n",
       "      <th>strMeasure9</th>\n",
       "      <th>strVideo</th>\n",
       "      <th>ingredients</th>\n",
       "      <th>isAlcoholic</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>'57 chevy with a white license plate</td>\n",
       "      <td>2016-07-18 22:49:04</td>\n",
       "      <td>14029</td>\n",
       "      <td>alcoholic</td>\n",
       "      <td>cocktail</td>\n",
       "      <td>http://www.thecocktaildb.com/images/media/drin...</td>\n",
       "      <td>Highball glass</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Creme de Cacao</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>creme de cacao, vodka</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1-900-fuk-meup</td>\n",
       "      <td>2016-07-18 22:27:04</td>\n",
       "      <td>15395</td>\n",
       "      <td>alcoholic</td>\n",
       "      <td>shot</td>\n",
       "      <td>http://www.thecocktaildb.com/images/media/drin...</td>\n",
       "      <td>Old-fashioned glass</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Absolut Kurant</td>\n",
       "      <td>...</td>\n",
       "      <td>1/4 oz</td>\n",
       "      <td>1/4 oz</td>\n",
       "      <td>1/4 oz</td>\n",
       "      <td>1/4 oz</td>\n",
       "      <td>1/2 oz</td>\n",
       "      <td>1/4 oz</td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "      <td>absolut kurant, grand marnier, chambord raspbe...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>110 in the shade</td>\n",
       "      <td>2016-02-03 14:51:57</td>\n",
       "      <td>15423</td>\n",
       "      <td>alcoholic</td>\n",
       "      <td>beer</td>\n",
       "      <td>http://www.thecocktaildb.com/images/media/drin...</td>\n",
       "      <td>Beer Glass</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Lager</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>lager, tequila</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>151 florida bushwacker</td>\n",
       "      <td>2016-07-18 22:28:43</td>\n",
       "      <td>14588</td>\n",
       "      <td>alcoholic</td>\n",
       "      <td>milk / float / shake</td>\n",
       "      <td>http://www.thecocktaildb.com/images/media/drin...</td>\n",
       "      <td>Beer mug</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Malibu rum</td>\n",
       "      <td>...</td>\n",
       "      <td>1/2 oz Bacardi</td>\n",
       "      <td>1 oz</td>\n",
       "      <td>1 oz</td>\n",
       "      <td>3 oz</td>\n",
       "      <td>1 oz</td>\n",
       "      <td>1 cup</td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "      <td>malibu rum, light rum, 151 proof rum, dark cre...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>155 belmont</td>\n",
       "      <td>2016-10-05 12:36:28</td>\n",
       "      <td>15346</td>\n",
       "      <td>alcoholic</td>\n",
       "      <td>cocktail</td>\n",
       "      <td>http://www.thecocktaildb.com/images/media/drin...</td>\n",
       "      <td>White wine glass</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Dark rum</td>\n",
       "      <td>...</td>\n",
       "      <td>1 shot</td>\n",
       "      <td>1 shot</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "      <td>dark rum, light rum, vodka, orange juice</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 43 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0                              strDrink         dateModified   \n",
       "0           0  '57 chevy with a white license plate  2016-07-18 22:49:04  \\\n",
       "1           1                        1-900-fuk-meup  2016-07-18 22:27:04   \n",
       "2           2                      110 in the shade  2016-02-03 14:51:57   \n",
       "3           3                151 florida bushwacker  2016-07-18 22:28:43   \n",
       "4           4                           155 belmont  2016-10-05 12:36:28   \n",
       "\n",
       "   idDrink strAlcoholic           strCategory   \n",
       "0    14029    alcoholic              cocktail  \\\n",
       "1    15395    alcoholic                  shot   \n",
       "2    15423    alcoholic                  beer   \n",
       "3    14588    alcoholic  milk / float / shake   \n",
       "4    15346    alcoholic              cocktail   \n",
       "\n",
       "                                       strDrinkThumb             strGlass   \n",
       "0  http://www.thecocktaildb.com/images/media/drin...       Highball glass  \\\n",
       "1  http://www.thecocktaildb.com/images/media/drin...  Old-fashioned glass   \n",
       "2  http://www.thecocktaildb.com/images/media/drin...           Beer Glass   \n",
       "3  http://www.thecocktaildb.com/images/media/drin...             Beer mug   \n",
       "4  http://www.thecocktaildb.com/images/media/drin...     White wine glass   \n",
       "\n",
       "  strIBA  strIngredient1  ...      strMeasure3 strMeasure4 strMeasure5   \n",
       "0    NaN  Creme de Cacao  ...                                           \\\n",
       "1    NaN  Absolut Kurant  ...          1/4 oz      1/4 oz      1/4 oz    \n",
       "2    NaN           Lager  ...                                            \n",
       "3    NaN      Malibu rum  ...  1/2 oz Bacardi        1 oz        1 oz    \n",
       "4    NaN        Dark rum  ...          1 shot      1 shot                \n",
       "\n",
       "   strMeasure6  strMeasure7  strMeasure8 strMeasure9 strVideo   \n",
       "0                                    NaN         NaN      NaN  \\\n",
       "1      1/4 oz       1/2 oz       1/4 oz                   NaN   \n",
       "2                                    NaN         NaN      NaN   \n",
       "3        3 oz         1 oz        1 cup                   NaN   \n",
       "4                                                         NaN   \n",
       "\n",
       "                                         ingredients isAlcoholic  \n",
       "0                              creme de cacao, vodka           1  \n",
       "1  absolut kurant, grand marnier, chambord raspbe...           1  \n",
       "2                                     lager, tequila           1  \n",
       "3  malibu rum, light rum, 151 proof rum, dark cre...           1  \n",
       "4           dark rum, light rum, vodka, orange juice           1  \n",
       "\n",
       "[5 rows x 43 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>strDrink</th>\n",
       "      <th>ingredients</th>\n",
       "      <th>strCategory</th>\n",
       "      <th>isAlcoholic</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>'57 chevy with a white license plate</td>\n",
       "      <td>creme de cacao, vodka</td>\n",
       "      <td>cocktail</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1-900-fuk-meup</td>\n",
       "      <td>absolut kurant, grand marnier, chambord raspbe...</td>\n",
       "      <td>shot</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>110 in the shade</td>\n",
       "      <td>lager, tequila</td>\n",
       "      <td>beer</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>151 florida bushwacker</td>\n",
       "      <td>malibu rum, light rum, 151 proof rum, dark cre...</td>\n",
       "      <td>milk / float / shake</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>155 belmont</td>\n",
       "      <td>dark rum, light rum, vodka, orange juice</td>\n",
       "      <td>cocktail</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               strDrink   \n",
       "0  '57 chevy with a white license plate  \\\n",
       "1                        1-900-fuk-meup   \n",
       "2                      110 in the shade   \n",
       "3                151 florida bushwacker   \n",
       "4                           155 belmont   \n",
       "\n",
       "                                         ingredients           strCategory   \n",
       "0                              creme de cacao, vodka              cocktail  \\\n",
       "1  absolut kurant, grand marnier, chambord raspbe...                  shot   \n",
       "2                                     lager, tequila                  beer   \n",
       "3  malibu rum, light rum, 151 proof rum, dark cre...  milk / float / shake   \n",
       "4           dark rum, light rum, vodka, orange juice              cocktail   \n",
       "\n",
       "   isAlcoholic  \n",
       "0            1  \n",
       "1            1  \n",
       "2            1  \n",
       "3            1  \n",
       "4            1  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df[['strDrink', 'ingredients', 'strCategory', 'isAlcoholic']]\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "tfidf = TfidfVectorizer()\n",
    "\n",
    "tfidf_matrix = tfidf.fit_transform(df['ingredients'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics.pairwise import cosine_similarity\n",
    "\n",
    "cosine_sim = cosine_similarity(tfidf_matrix, tfidf_matrix)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "323                 kamikaze\n",
      "483     strawberry margarita\n",
      "150           blue margarita\n",
      "512                  vampiro\n",
      "45                 adam bomb\n",
      "527               white lady\n",
      "54     after dinner cocktail\n",
      "392             orange crush\n",
      "241          flying dutchman\n",
      "158           boston sidecar\n",
      "Name: strDrink, dtype: object\n"
     ]
    }
   ],
   "source": [
    "indices = pd.Series(df.index, index=df['strDrink']).drop_duplicates()\n",
    "\n",
    "def recommend_cocktails(cocktail_name, cosine_sim=cosine_sim):\n",
    "    idx = indices[cocktail_name]\n",
    "\n",
    "    sim_scores = list(enumerate(cosine_sim[idx]))\n",
    "\n",
    "    sim_scores = sorted(sim_scores, key=lambda x: x[1], reverse=True)\n",
    "\n",
    "    sim_scores = sim_scores[1:11]\n",
    "\n",
    "    cocktail_indices = [i[0] for i in sim_scores]\n",
    "\n",
    "    return df['strDrink'].iloc[cocktail_indices]\n",
    "\n",
    "print(recommend_cocktails('margarita'))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['kamikaze', 'strawberry margarita', 'blue margarita', 'vampiro', 'adam bomb', 'white lady', 'after dinner cocktail', 'orange crush', 'flying dutchman', 'boston sidecar', 'frozen mint daiquiri', 'limeade', 'acapulco', 'autodafé', 'daiquiri', 'frozen pineapple daiquiri', 'jitterbug', 'gin smash', 'gin rickey', 'rum cooler', 'classic old-fashioned', 'manhattan', 'long vodka', 'abbey martini', 'bourbon sling', 'a piece of ass', 'fruit shake', 'blue lagoon', 'angelica liqueur', \"mother's milk\"]\n"
     ]
    }
   ],
   "source": [
    "from collections import Counter\n",
    "\n",
    "def recommend_for_favorites(favorites, num_recommendations=25, num_random=5):\n",
    "    recommendations_count = Counter()\n",
    "\n",
    "    # Pour chaque cocktail favori, obtenir des recommandations\n",
    "    for favorite in favorites:\n",
    "        similar_cocktails = recommend_cocktails(favorite)\n",
    "        recommendations_count.update(similar_cocktails)\n",
    "\n",
    "    top_recommendations = [cocktail for cocktail, _ in recommendations_count.most_common(num_recommendations)]\n",
    "\n",
    "    random_cocktails = df['strDrink'].sample(num_random).tolist()\n",
    "    final_recommendations = top_recommendations + random_cocktails\n",
    "\n",
    "    return final_recommendations\n",
    "\n",
    "#Simulation of utilisation\n",
    "favorites = ['margarita', 'mojito', 'old fashioned']\n",
    "print(recommend_for_favorites(favorites))\n"
   ]
  }
 ],
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