correia-filipa-1-notebook-nettoyage-112022.ipynb

{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.7.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"**Problem definition**\n\nL'agence **\"Santé publique France\"** a lancé un appel à projets pour trouver des idées innovantes d’applications en lien avec l'alimentation. Vous souhaitez y participer et proposer une idée d’application.","metadata":{}},{"cell_type":"markdown","source":"**Data**\n\n- https://world.openfoodfacts.org/\n- https://world.openfoodfacts.org/data/data-fields.txt\n","metadata":{}},{"cell_type":"markdown","source":"# Data Cleaning","metadata":{}},{"cell_type":"code","source":"# Importation des librairies \nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport seaborn as sns\nimport warnings\nwarnings.filterwarnings('ignore')\nimport itertools\nfrom sklearn.cluster import KMeans\n%pylab inline","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2022-12-05T11:00:35.481265Z","iopub.execute_input":"2022-12-05T11:00:35.481687Z","iopub.status.idle":"2022-12-05T11:00:35.493864Z","shell.execute_reply.started":"2022-12-05T11:00:35.481654Z","shell.execute_reply":"2022-12-05T11:00:35.492480Z"},"trusted":true},"execution_count":1316,"outputs":[{"name":"stdout","text":"Populating the interactive namespace from numpy and matplotlib\n","output_type":"stream"}]},{"cell_type":"markdown","source":"**DataFrame: Data**","metadata":{}},{"cell_type":"code","source":"Data = pd.read_csv('../input/openfoodfacts/fr.openfoodfacts.org.products.csv', sep='\\t')","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:00:35.496331Z","iopub.execute_input":"2022-12-05T11:00:35.496741Z","iopub.status.idle":"2022-12-05T11:00:48.391293Z","shell.execute_reply.started":"2022-12-05T11:00:35.496707Z","shell.execute_reply":"2022-12-05T11:00:48.390149Z"},"trusted":true},"execution_count":1317,"outputs":[]},{"cell_type":"code","source":"Data = Data.copy()","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:00:48.393322Z","iopub.execute_input":"2022-12-05T11:00:48.394362Z","iopub.status.idle":"2022-12-05T11:00:48.923886Z","shell.execute_reply.started":"2022-12-05T11:00:48.394316Z","shell.execute_reply":"2022-12-05T11:00:48.922658Z"},"trusted":true},"execution_count":1318,"outputs":[]},{"cell_type":"code","source":"Data.shape","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:00:48.925228Z","iopub.execute_input":"2022-12-05T11:00:48.925602Z","iopub.status.idle":"2022-12-05T11:00:48.933842Z","shell.execute_reply.started":"2022-12-05T11:00:48.925566Z","shell.execute_reply":"2022-12-05T11:00:48.932481Z"},"trusted":true},"execution_count":1319,"outputs":[{"execution_count":1319,"output_type":"execute_result","data":{"text/plain":"(320772, 162)"},"metadata":{}}]},{"cell_type":"code","source":"# Affiche tout les colunes dans le df\nData\npd.set_option('max_columns', None)","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:00:48.936922Z","iopub.execute_input":"2022-12-05T11:00:48.937329Z","iopub.status.idle":"2022-12-05T11:00:48.943880Z","shell.execute_reply.started":"2022-12-05T11:00:48.937275Z","shell.execute_reply":"2022-12-05T11:00:48.942564Z"},"trusted":true},"execution_count":1320,"outputs":[]},{"cell_type":"code","source":"Data = Data.dropna(how = 'all', axis = 1)","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:00:48.945265Z","iopub.execute_input":"2022-12-05T11:00:48.945668Z","iopub.status.idle":"2022-12-05T11:00:50.303704Z","shell.execute_reply.started":"2022-12-05T11:00:48.945627Z","shell.execute_reply":"2022-12-05T11:00:50.302506Z"},"trusted":true},"execution_count":1321,"outputs":[]},{"cell_type":"code","source":"Data = Data.drop_duplicates()","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:00:50.305130Z","iopub.execute_input":"2022-12-05T11:00:50.305458Z","iopub.status.idle":"2022-12-05T11:00:54.755463Z","shell.execute_reply.started":"2022-12-05T11:00:50.305427Z","shell.execute_reply":"2022-12-05T11:00:54.754158Z"},"trusted":true},"execution_count":1322,"outputs":[]},{"cell_type":"code","source":"# Selectioner les produits pour la France\nfr = []\nfor i in range(len(Data)):\n    if Data.loc[i, 'countries'] == 'France'or Data.loc[i, 'countries'] == 'en:FR':\n        fr.append(Data.loc[i, 'countries'])","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:00:54.757106Z","iopub.execute_input":"2022-12-05T11:00:54.758011Z","iopub.status.idle":"2022-12-05T11:01:01.859470Z","shell.execute_reply.started":"2022-12-05T11:00:54.757972Z","shell.execute_reply":"2022-12-05T11:01:01.858211Z"},"trusted":true},"execution_count":1323,"outputs":[]},{"cell_type":"code","source":"Data_fr = Data[Data['countries'].isin(fr)]\npd.set_option('max_columns', None)\nData_fr.head()","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:01.861348Z","iopub.execute_input":"2022-12-05T11:01:01.862007Z","iopub.status.idle":"2022-12-05T11:01:02.138505Z","shell.execute_reply.started":"2022-12-05T11:01:01.861967Z","shell.execute_reply":"2022-12-05T11:01:02.137361Z"},"trusted":true},"execution_count":1324,"outputs":[{"execution_count":1324,"output_type":"execute_result","data":{"text/plain":"        code                                                url  \\\n0       3087  http://world-fr.openfoodfacts.org/produit/0000...   \n46     24600  http://world-fr.openfoodfacts.org/produit/0000...   \n48     27205  http://world-fr.openfoodfacts.org/produit/0000...   \n136    39259  http://world-fr.openfoodfacts.org/produit/0000...   \n182  5200016  http://world-fr.openfoodfacts.org/produit/0000...   \n\n                        creator   created_t      created_datetime  \\\n0    openfoodfacts-contributors  1474103866  2016-09-17T09:17:46Z   \n46              date-limite-app  1434530704  2015-06-17T08:45:04Z   \n48                      tacinte  1458238630  2016-03-17T18:17:10Z   \n136                     tacinte  1422221773  2015-01-25T21:36:13Z   \n182                     sigoise  1441186657  2015-09-02T09:37:37Z   \n\n    last_modified_t last_modified_datetime        product_name generic_name  \\\n0        1474103893   2016-09-17T09:18:13Z  Farine de blé noir          NaN   \n46       1434535914   2015-06-17T10:11:54Z       Filet de bœuf          NaN   \n48       1458238638   2016-03-17T18:17:18Z                 NaN          NaN   \n136      1473538082   2016-09-10T20:08:02Z             Twix x2          NaN   \n182      1442570752   2015-09-18T10:05:52Z   lentilles vertes           NaN   \n\n    quantity         packaging    packaging_tags            brands  \\\n0        1kg               NaN               NaN   Ferme t'y R'nao   \n46   2.46 kg         plastique         plastique               NaN   \n48       NaN               NaN               NaN               NaN   \n136      NaN               NaN               NaN               NaN   \n182    1 kg   Sachet plastique  sachet-plastique  Bertrand Lejeune   \n\n          brands_tags                                         categories  \\\n0     ferme-t-y-r-nao                                                NaN   \n46                NaN                                      Filet de bœuf   \n48                NaN                                                NaN   \n136               NaN                                                NaN   \n182  bertrand-lejeune  Aliments et boissons à base de végétaux,Alimen...   \n\n                                       categories_tags  \\\n0                                                  NaN   \n46                                   fr:filet-de-boeuf   \n48                                                 NaN   \n136                                                NaN   \n182  en:plant-based-foods-and-beverages,en:plant-ba...   \n\n                                         categories_fr origins origins_tags  \\\n0                                                  NaN     NaN          NaN   \n46                                      Filet-de-boeuf     NaN          NaN   \n48                                                 NaN     NaN          NaN   \n136                                                NaN     NaN          NaN   \n182  Aliments et boissons à base de végétaux,Alimen...     NaN          NaN   \n\n    manufacturing_places manufacturing_places_tags labels  \\\n0                    NaN                       NaN    NaN   \n46                   NaN                       NaN    NaN   \n48                   NaN                       NaN    NaN   \n136                  NaN                       NaN    NaN   \n182                  NaN                       NaN     AB   \n\n                                           labels_tags  \\\n0                                                  NaN   \n46                                                 NaN   \n48                                                 NaN   \n136                                                NaN   \n182  en:organic,en:eu-organic,fr:ab-agriculture-bio...   \n\n                                      labels_fr emb_codes emb_codes_tags  \\\n0                                           NaN       NaN            NaN   \n46                                          NaN       NaN            NaN   \n48                                          NaN       NaN            NaN   \n136                                         NaN       NaN            NaN   \n182  Bio,Bio européen,AB Agriculture Biologique       NaN            NaN   \n\n    first_packaging_code_geo cities cities_tags purchase_places stores  \\\n0                        NaN    NaN         NaN             NaN    NaN   \n46                       NaN    NaN         NaN             NaN    NaN   \n48                       NaN    NaN         NaN             NaN    NaN   \n136                      NaN    NaN         NaN   Roissy,France    NaN   \n182                      NaN    NaN         NaN             NaN    NaN   \n\n    countries countries_tags countries_fr  ingredients_text allergens  \\\n0       en:FR      en:france       France               NaN       NaN   \n46     France      en:france       France               NaN       NaN   \n48      en:FR      en:france       France               NaN       NaN   \n136    France      en:france       France               NaN       NaN   \n182    France      en:france       France  lentilles vertes       NaN   \n\n    allergens_fr traces traces_tags traces_fr serving_size  additives_n  \\\n0            NaN    NaN         NaN       NaN          NaN          NaN   \n46           NaN    NaN         NaN       NaN          NaN          NaN   \n48           NaN    NaN         NaN       NaN          NaN          NaN   \n136          NaN    NaN         NaN       NaN          NaN          NaN   \n182          NaN    NaN         NaN       NaN          NaN          0.0   \n\n                                             additives additives_tags  \\\n0                                                  NaN            NaN   \n46                                                 NaN            NaN   \n48                                                 NaN            NaN   \n136                                                NaN            NaN   \n182   [ lentilles-vertes -> fr:lentilles-vertes  ] ...            NaN   \n\n    additives_fr  ingredients_from_palm_oil_n ingredients_from_palm_oil_tags  \\\n0            NaN                          NaN                            NaN   \n46           NaN                          NaN                            NaN   \n48           NaN                          NaN                            NaN   \n136          NaN                          NaN                            NaN   \n182          NaN                          0.0                            NaN   \n\n     ingredients_that_may_be_from_palm_oil_n  \\\n0                                        NaN   \n46                                       NaN   \n48                                       NaN   \n136                                      NaN   \n182                                      0.0   \n\n    ingredients_that_may_be_from_palm_oil_tags nutrition_grade_fr  \\\n0                                          NaN                NaN   \n46                                         NaN                NaN   \n48                                         NaN                NaN   \n136                                        NaN                NaN   \n182                                        NaN                NaN   \n\n            pnns_groups_1 pnns_groups_2  \\\n0                     NaN           NaN   \n46                unknown       unknown   \n48                    NaN           NaN   \n136               unknown       unknown   \n182  Cereals and potatoes       Legumes   \n\n                                                states  \\\n0    en:to-be-completed, en:nutrition-facts-to-be-c...   \n46   en:to-be-completed, en:nutrition-facts-to-be-c...   \n48   en:to-be-completed, en:nutrition-facts-to-be-c...   \n136  en:to-be-completed, en:nutrition-facts-to-be-c...   \n182  en:to-be-completed, en:nutrition-facts-to-be-c...   \n\n                                           states_tags  \\\n0    en:to-be-completed,en:nutrition-facts-to-be-co...   \n46   en:to-be-completed,en:nutrition-facts-to-be-co...   \n48   en:to-be-completed,en:nutrition-facts-to-be-co...   \n136  en:to-be-completed,en:nutrition-facts-to-be-co...   \n182  en:to-be-completed,en:nutrition-facts-to-be-co...   \n\n                                             states_fr  \\\n0    A compléter,Informations nutritionnelles à com...   \n46   A compléter,Informations nutritionnelles à com...   \n48   A compléter,Informations nutritionnelles à com...   \n136  A compléter,Informations nutritionnelles à com...   \n182  A compléter,Informations nutritionnelles à com...   \n\n                          main_category  \\\n0                                   NaN   \n46                    fr:filet-de-boeuf   \n48                                  NaN   \n136                                 NaN   \n182  en:plant-based-foods-and-beverages   \n\n                            main_category_fr  \\\n0                                        NaN   \n46                            Filet-de-boeuf   \n48                                       NaN   \n136                                      NaN   \n182  Aliments et boissons à base de végétaux   \n\n                                             image_url  \\\n0                                                  NaN   \n46   http://fr.openfoodfacts.org/images/products/00...   \n48   http://fr.openfoodfacts.org/images/products/00...   \n136  http://fr.openfoodfacts.org/images/products/00...   \n182  http://fr.openfoodfacts.org/images/products/00...   \n\n                                       image_small_url  energy_100g  \\\n0                                                  NaN          NaN   \n46   http://fr.openfoodfacts.org/images/products/00...          NaN   \n48   http://fr.openfoodfacts.org/images/products/00...          NaN   \n136  http://fr.openfoodfacts.org/images/products/00...          NaN   \n182  http://fr.openfoodfacts.org/images/products/00...          NaN   \n\n     energy-from-fat_100g  fat_100g  saturated-fat_100g  caprylic-acid_100g  \\\n0                     NaN       NaN                 NaN                 NaN   \n46                    NaN       NaN                 NaN                 NaN   \n48                    NaN       NaN                 NaN                 NaN   \n136                   NaN       NaN                 NaN                 NaN   \n182                   NaN       NaN                 NaN                 NaN   \n\n     capric-acid_100g  lauric-acid_100g  myristic-acid_100g  \\\n0                 NaN               NaN                 NaN   \n46                NaN               NaN                 NaN   \n48                NaN               NaN                 NaN   \n136               NaN               NaN                 NaN   \n182               NaN               NaN                 NaN   \n\n     palmitic-acid_100g  stearic-acid_100g  arachidic-acid_100g  \\\n0                   NaN                NaN                  NaN   \n46                  NaN                NaN                  NaN   \n48                  NaN                NaN                  NaN   \n136                 NaN                NaN                  NaN   \n182                 NaN                NaN                  NaN   \n\n     behenic-acid_100g  montanic-acid_100g  monounsaturated-fat_100g  \\\n0                  NaN                 NaN                       NaN   \n46                 NaN                 NaN                       NaN   \n48                 NaN                 NaN                       NaN   \n136                NaN                 NaN                       NaN   \n182                NaN                 NaN                       NaN   \n\n     polyunsaturated-fat_100g  omega-3-fat_100g  alpha-linolenic-acid_100g  \\\n0                         NaN               NaN                        NaN   \n46                        NaN               NaN                        NaN   \n48                        NaN               NaN                        NaN   \n136                       NaN               NaN                        NaN   \n182                       NaN               NaN                        NaN   \n\n     eicosapentaenoic-acid_100g  docosahexaenoic-acid_100g  omega-6-fat_100g  \\\n0                           NaN                        NaN               NaN   \n46                          NaN                        NaN               NaN   \n48                          NaN                        NaN               NaN   \n136                         NaN                        NaN               NaN   \n182                         NaN                        NaN               NaN   \n\n     linoleic-acid_100g  arachidonic-acid_100g  gamma-linolenic-acid_100g  \\\n0                   NaN                    NaN                        NaN   \n46                  NaN                    NaN                        NaN   \n48                  NaN                    NaN                        NaN   \n136                 NaN                    NaN                        NaN   \n182                 NaN                    NaN                        NaN   \n\n     dihomo-gamma-linolenic-acid_100g  omega-9-fat_100g  oleic-acid_100g  \\\n0                                 NaN               NaN              NaN   \n46                                NaN               NaN              NaN   \n48                                NaN               NaN              NaN   \n136                               NaN               NaN              NaN   \n182                               NaN               NaN              NaN   \n\n     gondoic-acid_100g  trans-fat_100g  cholesterol_100g  carbohydrates_100g  \\\n0                  NaN             NaN               NaN                 NaN   \n46                 NaN             NaN               NaN                 NaN   \n48                 NaN             NaN               NaN                 NaN   \n136                NaN             NaN               NaN                 NaN   \n182                NaN             NaN               NaN                 NaN   \n\n     sugars_100g  sucrose_100g  glucose_100g  fructose_100g  lactose_100g  \\\n0            NaN           NaN           NaN            NaN           NaN   \n46           NaN           NaN           NaN            NaN           NaN   \n48           NaN           NaN           NaN            NaN           NaN   \n136          NaN           NaN           NaN            NaN           NaN   \n182          NaN           NaN           NaN            NaN           NaN   \n\n     maltose_100g  maltodextrins_100g  starch_100g  polyols_100g  fiber_100g  \\\n0             NaN                 NaN          NaN           NaN         NaN   \n46            NaN                 NaN          NaN           NaN         NaN   \n48            NaN                 NaN          NaN           NaN         NaN   \n136           NaN                 NaN          NaN           NaN         NaN   \n182           NaN                 NaN          NaN           NaN         NaN   \n\n     proteins_100g  casein_100g  serum-proteins_100g  nucleotides_100g  \\\n0              NaN          NaN                  NaN               NaN   \n46             NaN          NaN                  NaN               NaN   \n48             NaN          NaN                  NaN               NaN   \n136            NaN          NaN                  NaN               NaN   \n182            NaN          NaN                  NaN               NaN   \n\n     salt_100g  sodium_100g  alcohol_100g  vitamin-a_100g  beta-carotene_100g  \\\n0          NaN          NaN           NaN             NaN                 NaN   \n46         NaN          NaN           NaN             NaN                 NaN   \n48         NaN          NaN           NaN             NaN                 NaN   \n136        NaN          NaN           NaN             NaN                 NaN   \n182        NaN          NaN           NaN             NaN                 NaN   \n\n     vitamin-d_100g  vitamin-e_100g  vitamin-k_100g  vitamin-c_100g  \\\n0               NaN             NaN             NaN             NaN   \n46              NaN             NaN             NaN             NaN   \n48              NaN             NaN             NaN             NaN   \n136             NaN             NaN             NaN             NaN   \n182             NaN             NaN             NaN             NaN   \n\n     vitamin-b1_100g  vitamin-b2_100g  vitamin-pp_100g  vitamin-b6_100g  \\\n0                NaN              NaN              NaN              NaN   \n46               NaN              NaN              NaN              NaN   \n48               NaN              NaN              NaN              NaN   \n136              NaN              NaN              NaN              NaN   \n182              NaN              NaN              NaN              NaN   \n\n     vitamin-b9_100g  folates_100g  vitamin-b12_100g  biotin_100g  \\\n0                NaN           NaN               NaN          NaN   \n46               NaN           NaN               NaN          NaN   \n48               NaN           NaN               NaN          NaN   \n136              NaN           NaN               NaN          NaN   \n182              NaN           NaN               NaN          NaN   \n\n     pantothenic-acid_100g  silica_100g  bicarbonate_100g  potassium_100g  \\\n0                      NaN          NaN               NaN             NaN   \n46                     NaN          NaN               NaN             NaN   \n48                     NaN          NaN               NaN             NaN   \n136                    NaN          NaN               NaN             NaN   \n182                    NaN          NaN               NaN             NaN   \n\n     chloride_100g  calcium_100g  phosphorus_100g  iron_100g  magnesium_100g  \\\n0              NaN           NaN              NaN        NaN             NaN   \n46             NaN           NaN              NaN        NaN             NaN   \n48             NaN           NaN              NaN        NaN             NaN   \n136            NaN           NaN              NaN        NaN             NaN   \n182            NaN           NaN              NaN        NaN             NaN   \n\n     zinc_100g  copper_100g  manganese_100g  fluoride_100g  selenium_100g  \\\n0          NaN          NaN             NaN            NaN            NaN   \n46         NaN          NaN             NaN            NaN            NaN   \n48         NaN          NaN             NaN            NaN            NaN   \n136        NaN          NaN             NaN            NaN            NaN   \n182        NaN          NaN             NaN            NaN            NaN   \n\n     chromium_100g  molybdenum_100g  iodine_100g  caffeine_100g  taurine_100g  \\\n0              NaN              NaN          NaN            NaN           NaN   \n46             NaN              NaN          NaN            NaN           NaN   \n48             NaN              NaN          NaN            NaN           NaN   \n136            NaN              NaN          NaN            NaN           NaN   \n182            NaN              NaN          NaN            NaN           NaN   \n\n     ph_100g  fruits-vegetables-nuts_100g  collagen-meat-protein-ratio_100g  \\\n0        NaN                          NaN                               NaN   \n46       NaN                          NaN                               NaN   \n48       NaN                          NaN                               NaN   \n136      NaN                          NaN                               NaN   \n182      NaN                          NaN                               NaN   \n\n     cocoa_100g  carbon-footprint_100g  nutrition-score-fr_100g  \\\n0           NaN                    NaN                      NaN   \n46          NaN                    NaN                      NaN   \n48          NaN                    NaN                      NaN   \n136         NaN                    NaN                      NaN   \n182         NaN                    NaN                      NaN   \n\n     nutrition-score-uk_100g  \n0                        NaN  \n46                       NaN  \n48                       NaN  \n136                      NaN  \n182                      NaN  ","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>code</th>\n      <th>url</th>\n      <th>creator</th>\n      <th>created_t</th>\n      <th>created_datetime</th>\n      <th>last_modified_t</th>\n      <th>last_modified_datetime</th>\n      <th>product_name</th>\n      <th>generic_name</th>\n      <th>quantity</th>\n      <th>packaging</th>\n      <th>packaging_tags</th>\n      <th>brands</th>\n      <th>brands_tags</th>\n      <th>categories</th>\n      <th>categories_tags</th>\n      <th>categories_fr</th>\n      <th>origins</th>\n      <th>origins_tags</th>\n      <th>manufacturing_places</th>\n      <th>manufacturing_places_tags</th>\n      <th>labels</th>\n      <th>labels_tags</th>\n      <th>labels_fr</th>\n      <th>emb_codes</th>\n      <th>emb_codes_tags</th>\n      <th>first_packaging_code_geo</th>\n      <th>cities</th>\n      <th>cities_tags</th>\n      <th>purchase_places</th>\n      <th>stores</th>\n      <th>countries</th>\n      <th>countries_tags</th>\n      <th>countries_fr</th>\n      <th>ingredients_text</th>\n      <th>allergens</th>\n      <th>allergens_fr</th>\n      <th>traces</th>\n      <th>traces_tags</th>\n      <th>traces_fr</th>\n      <th>serving_size</th>\n      <th>additives_n</th>\n      <th>additives</th>\n      <th>additives_tags</th>\n      <th>additives_fr</th>\n      <th>ingredients_from_palm_oil_n</th>\n      <th>ingredients_from_palm_oil_tags</th>\n      <th>ingredients_that_may_be_from_palm_oil_n</th>\n      <th>ingredients_that_may_be_from_palm_oil_tags</th>\n      <th>nutrition_grade_fr</th>\n      <th>pnns_groups_1</th>\n      <th>pnns_groups_2</th>\n      <th>states</th>\n      <th>states_tags</th>\n      <th>states_fr</th>\n      <th>main_category</th>\n      <th>main_category_fr</th>\n      <th>image_url</th>\n      <th>image_small_url</th>\n      <th>energy_100g</th>\n      <th>energy-from-fat_100g</th>\n      <th>fat_100g</th>\n      <th>saturated-fat_100g</th>\n      <th>caprylic-acid_100g</th>\n      <th>capric-acid_100g</th>\n      <th>lauric-acid_100g</th>\n      <th>myristic-acid_100g</th>\n      <th>palmitic-acid_100g</th>\n      <th>stearic-acid_100g</th>\n      <th>arachidic-acid_100g</th>\n      <th>behenic-acid_100g</th>\n      <th>montanic-acid_100g</th>\n      <th>monounsaturated-fat_100g</th>\n      <th>polyunsaturated-fat_100g</th>\n      <th>omega-3-fat_100g</th>\n      <th>alpha-linolenic-acid_100g</th>\n      <th>eicosapentaenoic-acid_100g</th>\n      <th>docosahexaenoic-acid_100g</th>\n      <th>omega-6-fat_100g</th>\n      <th>linoleic-acid_100g</th>\n      <th>arachidonic-acid_100g</th>\n      <th>gamma-linolenic-acid_100g</th>\n      <th>dihomo-gamma-linolenic-acid_100g</th>\n      <th>omega-9-fat_100g</th>\n      <th>oleic-acid_100g</th>\n      <th>gondoic-acid_100g</th>\n      <th>trans-fat_100g</th>\n      <th>cholesterol_100g</th>\n      <th>carbohydrates_100g</th>\n      <th>sugars_100g</th>\n      <th>sucrose_100g</th>\n      <th>glucose_100g</th>\n      <th>fructose_100g</th>\n      <th>lactose_100g</th>\n      <th>maltose_100g</th>\n      <th>maltodextrins_100g</th>\n      <th>starch_100g</th>\n      <th>polyols_100g</th>\n      <th>fiber_100g</th>\n      <th>proteins_100g</th>\n      <th>casein_100g</th>\n      <th>serum-proteins_100g</th>\n      <th>nucleotides_100g</th>\n      <th>salt_100g</th>\n      <th>sodium_100g</th>\n      <th>alcohol_100g</th>\n      <th>vitamin-a_100g</th>\n      <th>beta-carotene_100g</th>\n      <th>vitamin-d_100g</th>\n      <th>vitamin-e_100g</th>\n      <th>vitamin-k_100g</th>\n      <th>vitamin-c_100g</th>\n      <th>vitamin-b1_100g</th>\n      <th>vitamin-b2_100g</th>\n      <th>vitamin-pp_100g</th>\n      <th>vitamin-b6_100g</th>\n      <th>vitamin-b9_100g</th>\n      <th>folates_100g</th>\n      <th>vitamin-b12_100g</th>\n      <th>biotin_100g</th>\n      <th>pantothenic-acid_100g</th>\n      <th>silica_100g</th>\n      <th>bicarbonate_100g</th>\n      <th>potassium_100g</th>\n      <th>chloride_100g</th>\n      <th>calcium_100g</th>\n      <th>phosphorus_100g</th>\n      <th>iron_100g</th>\n      <th>magnesium_100g</th>\n      <th>zinc_100g</th>\n      <th>copper_100g</th>\n      <th>manganese_100g</th>\n      <th>fluoride_100g</th>\n      <th>selenium_100g</th>\n      <th>chromium_100g</th>\n      <th>molybdenum_100g</th>\n      <th>iodine_100g</th>\n      <th>caffeine_100g</th>\n      <th>taurine_100g</th>\n      <th>ph_100g</th>\n      <th>fruits-vegetables-nuts_100g</th>\n      <th>collagen-meat-protein-ratio_100g</th>\n      <th>cocoa_100g</th>\n      <th>carbon-footprint_100g</th>\n      <th>nutrition-score-fr_100g</th>\n      <th>nutrition-score-uk_100g</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>3087</td>\n      <td>http://world-fr.openfoodfacts.org/produit/0000...</td>\n      <td>openfoodfacts-contributors</td>\n      <td>1474103866</td>\n      <td>2016-09-17T09:17:46Z</td>\n      <td>1474103893</td>\n      <td>2016-09-17T09:18:13Z</td>\n      <td>Farine de blé noir</td>\n      <td>NaN</td>\n      <td>1kg</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Ferme t'y R'nao</td>\n      <td>ferme-t-y-r-nao</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>en:FR</td>\n      <td>en:france</td>\n      <td>France</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>en:to-be-completed, en:nutrition-facts-to-be-c...</td>\n      <td>en:to-be-completed,en:nutrition-facts-to-be-co...</td>\n      <td>A compléter,Informations nutritionnelles à com...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>46</th>\n      <td>24600</td>\n      <td>http://world-fr.openfoodfacts.org/produit/0000...</td>\n      <td>date-limite-app</td>\n      <td>1434530704</td>\n      <td>2015-06-17T08:45:04Z</td>\n      <td>1434535914</td>\n      <td>2015-06-17T10:11:54Z</td>\n      <td>Filet de bœuf</td>\n      <td>NaN</td>\n      <td>2.46 kg</td>\n      <td>plastique</td>\n      <td>plastique</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Filet de bœuf</td>\n      <td>fr:filet-de-boeuf</td>\n      <td>Filet-de-boeuf</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>France</td>\n      <td>en:france</td>\n      <td>France</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>unknown</td>\n      <td>unknown</td>\n      <td>en:to-be-completed, en:nutrition-facts-to-be-c...</td>\n      <td>en:to-be-completed,en:nutrition-facts-to-be-co...</td>\n      <td>A compléter,Informations nutritionnelles à com...</td>\n      <td>fr:filet-de-boeuf</td>\n      <td>Filet-de-boeuf</td>\n      <td>http://fr.openfoodfacts.org/images/products/00...</td>\n      <td>http://fr.openfoodfacts.org/images/products/00...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>48</th>\n      <td>27205</td>\n      <td>http://world-fr.openfoodfacts.org/produit/0000...</td>\n      <td>tacinte</td>\n      <td>1458238630</td>\n      <td>2016-03-17T18:17:10Z</td>\n      <td>1458238638</td>\n      <td>2016-03-17T18:17:18Z</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>en:FR</td>\n      <td>en:france</td>\n      <td>France</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>en:to-be-completed, en:nutrition-facts-to-be-c...</td>\n      <td>en:to-be-completed,en:nutrition-facts-to-be-co...</td>\n      <td>A compléter,Informations nutritionnelles à com...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>http://fr.openfoodfacts.org/images/products/00...</td>\n      <td>http://fr.openfoodfacts.org/images/products/00...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>136</th>\n      <td>39259</td>\n      <td>http://world-fr.openfoodfacts.org/produit/0000...</td>\n      <td>tacinte</td>\n      <td>1422221773</td>\n      <td>2015-01-25T21:36:13Z</td>\n      <td>1473538082</td>\n      <td>2016-09-10T20:08:02Z</td>\n      <td>Twix x2</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Roissy,France</td>\n      <td>NaN</td>\n      <td>France</td>\n      <td>en:france</td>\n      <td>France</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>unknown</td>\n      <td>unknown</td>\n      <td>en:to-be-completed, en:nutrition-facts-to-be-c...</td>\n      <td>en:to-be-completed,en:nutrition-facts-to-be-co...</td>\n      <td>A compléter,Informations nutritionnelles à com...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>http://fr.openfoodfacts.org/images/products/00...</td>\n      <td>http://fr.openfoodfacts.org/images/products/00...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>182</th>\n      <td>5200016</td>\n      <td>http://world-fr.openfoodfacts.org/produit/0000...</td>\n      <td>sigoise</td>\n      <td>1441186657</td>\n      <td>2015-09-02T09:37:37Z</td>\n      <td>1442570752</td>\n      <td>2015-09-18T10:05:52Z</td>\n      <td>lentilles vertes</td>\n      <td>NaN</td>\n      <td>1 kg</td>\n      <td>Sachet plastique</td>\n      <td>sachet-plastique</td>\n      <td>Bertrand Lejeune</td>\n      <td>bertrand-lejeune</td>\n      <td>Aliments et boissons à base de végétaux,Alimen...</td>\n      <td>en:plant-based-foods-and-beverages,en:plant-ba...</td>\n      <td>Aliments et boissons à base de végétaux,Alimen...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>AB</td>\n      <td>en:organic,en:eu-organic,fr:ab-agriculture-bio...</td>\n      <td>Bio,Bio européen,AB Agriculture Biologique</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>France</td>\n      <td>en:france</td>\n      <td>France</td>\n      <td>lentilles vertes</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0.0</td>\n      <td>[ lentilles-vertes -&gt; fr:lentilles-vertes  ] ...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0.0</td>\n      <td>NaN</td>\n      <td>0.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Cereals and potatoes</td>\n      <td>Legumes</td>\n      <td>en:to-be-completed, en:nutrition-facts-to-be-c...</td>\n      <td>en:to-be-completed,en:nutrition-facts-to-be-co...</td>\n      <td>A compléter,Informations nutritionnelles à com...</td>\n      <td>en:plant-based-foods-and-beverages</td>\n      <td>Aliments et boissons à base de végétaux</td>\n      <td>http://fr.openfoodfacts.org/images/products/00...</td>\n      <td>http://fr.openfoodfacts.org/images/products/00...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"len(Data_fr)","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:02.140108Z","iopub.execute_input":"2022-12-05T11:01:02.141246Z","iopub.status.idle":"2022-12-05T11:01:02.149645Z","shell.execute_reply.started":"2022-12-05T11:01:02.141203Z","shell.execute_reply":"2022-12-05T11:01:02.148241Z"},"trusted":true},"execution_count":1325,"outputs":[{"execution_count":1325,"output_type":"execute_result","data":{"text/plain":"94271"},"metadata":{}}]},{"cell_type":"code","source":"Data_fr['categories_fr'] = np.where((Data_fr['categories_fr'].isnull()==True), \"unknown\", \n                                 np.where(Data_fr['categories_fr'] == \"\", \"unknown\", Data_fr['categories_fr']))\nData_fr['main_category_fr'] = np.where((Data_fr['main_category_fr'].isnull()==True), \"unknown\", \n                                 np.where(Data_fr['main_category_fr'] == \"\", \"unknown\", Data_fr['main_category_fr']))\nData_fr['pnns_groups_1'] = np.where((Data_fr['pnns_groups_1'].isnull()==True), \"unknown\", \n                                 np.where(Data_fr['pnns_groups_1'] == \"\", \"unknown\", Data_fr['pnns_groups_1']))\nData_fr['pnns_groups_2'] = np.where((Data_fr['pnns_groups_2'].isnull()==True), \"unknown\", \n                                 np.where(Data_fr['pnns_groups_2'] == \"\", \"unknown\", Data_fr['pnns_groups_2']))","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:02.155263Z","iopub.execute_input":"2022-12-05T11:01:02.155711Z","iopub.status.idle":"2022-12-05T11:01:02.235023Z","shell.execute_reply.started":"2022-12-05T11:01:02.155674Z","shell.execute_reply":"2022-12-05T11:01:02.233820Z"},"trusted":true},"execution_count":1326,"outputs":[]},{"cell_type":"code","source":"for i in Data_fr['pnns_groups_1'].unique():\n    print (i)","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:02.236760Z","iopub.execute_input":"2022-12-05T11:01:02.237160Z","iopub.status.idle":"2022-12-05T11:01:02.251546Z","shell.execute_reply.started":"2022-12-05T11:01:02.237128Z","shell.execute_reply":"2022-12-05T11:01:02.250233Z"},"trusted":true},"execution_count":1327,"outputs":[{"name":"stdout","text":"unknown\nCereals and potatoes\nSugary snacks\nBeverages\nFish Meat Eggs\nFruits and vegetables\nComposite foods\nSalty snacks\nFat and sauces\nMilk and dairy products\nfruits-and-vegetables\nsugary-snacks\ncereals-and-potatoes\n","output_type":"stream"}]},{"cell_type":"code","source":"Data_fr = Data_fr[~Data_fr.pnns_groups_1.isin([\"nan\"])]\nData_fr = Data_fr[~Data_fr.pnns_groups_2.isin([\"nan\"])]","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:02.253248Z","iopub.execute_input":"2022-12-05T11:01:02.254299Z","iopub.status.idle":"2022-12-05T11:01:02.585734Z","shell.execute_reply.started":"2022-12-05T11:01:02.254261Z","shell.execute_reply":"2022-12-05T11:01:02.584391Z"},"trusted":true},"execution_count":1328,"outputs":[]},{"cell_type":"code","source":"Data_fr[Data_fr['pnns_groups_1'].str.contains('nan')==False]","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:02.587489Z","iopub.execute_input":"2022-12-05T11:01:02.587869Z","iopub.status.idle":"2022-12-05T11:01:02.939646Z","shell.execute_reply.started":"2022-12-05T11:01:02.587836Z","shell.execute_reply":"2022-12-05T11:01:02.938282Z"},"trusted":true},"execution_count":1329,"outputs":[{"execution_count":1329,"output_type":"execute_result","data":{"text/plain":"                 code                                                url  \\\n0                3087  http://world-fr.openfoodfacts.org/produit/0000...   \n46              24600  http://world-fr.openfoodfacts.org/produit/0000...   \n48              27205  http://world-fr.openfoodfacts.org/produit/0000...   \n136             39259  http://world-fr.openfoodfacts.org/produit/0000...   \n182           5200016  http://world-fr.openfoodfacts.org/produit/0000...   \n...               ...                                                ...   \n320761  9906410000009  http://world-fr.openfoodfacts.org/produit/9906...   \n320763       99111250  http://world-fr.openfoodfacts.org/produit/9911...   \n320764           9918  http://world-fr.openfoodfacts.org/produit/9918...   \n320765  9935010000003  http://world-fr.openfoodfacts.org/produit/9935...   \n320770  9980282863788  http://world-fr.openfoodfacts.org/produit/9980...   \n\n                           creator   created_t      created_datetime  \\\n0       openfoodfacts-contributors  1474103866  2016-09-17T09:17:46Z   \n46                 date-limite-app  1434530704  2015-06-17T08:45:04Z   \n48                         tacinte  1458238630  2016-03-17T18:17:10Z   \n136                        tacinte  1422221773  2015-01-25T21:36:13Z   \n182                        sigoise  1441186657  2015-09-02T09:37:37Z   \n...                            ...         ...                   ...   \n320761                  agamitsudo  1373480408  2013-07-10T18:20:08Z   \n320763                    balooval  1367163039  2013-04-28T15:30:39Z   \n320764                  woshilapin  1430167954  2015-04-27T20:52:34Z   \n320765                    sebleouf  1446293229  2015-10-31T12:07:09Z   \n320770  openfoodfacts-contributors  1492340089  2017-04-16T10:54:49Z   \n\n       last_modified_t last_modified_datetime                product_name  \\\n0           1474103893   2016-09-17T09:18:13Z          Farine de blé noir   \n46          1434535914   2015-06-17T10:11:54Z               Filet de bœuf   \n48          1458238638   2016-03-17T18:17:18Z                         NaN   \n136         1473538082   2016-09-10T20:08:02Z                     Twix x2   \n182         1442570752   2015-09-18T10:05:52Z           lentilles vertes    \n...                ...                    ...                         ...   \n320761      1451851215   2016-01-03T20:00:15Z   Roussette du Bugey (2011)   \n320763      1371690556   2013-06-20T01:09:16Z          Thé vert Earl grey   \n320764      1430167992   2015-04-27T20:53:12Z  Cheese cake thé vert, yuzu   \n320765      1446376839   2015-11-01T11:20:39Z              Rillette d'oie   \n320770      1492340089   2017-04-16T10:54:49Z    Tomates aux Vermicelles    \n\n               generic_name quantity           packaging      packaging_tags  \\\n0                       NaN      1kg                 NaN                 NaN   \n46                      NaN  2.46 kg           plastique           plastique   \n48                      NaN      NaN                 NaN                 NaN   \n136                     NaN      NaN                 NaN                 NaN   \n182                     NaN    1 kg     Sachet plastique    sachet-plastique   \n...                     ...      ...                 ...                 ...   \n320761  Vins blanc du Bugey   750 ml  Bouteille en verre  bouteille-en-verre   \n320763    thé bio équitable     50 g        boîte,carton        boite,carton   \n320764                  NaN      NaN                 NaN                 NaN   \n320765                  NaN    180 g           Pot,Verre           pot,verre   \n320770                  NaN      67g                 NaN                 NaN   \n\n                       brands            brands_tags  \\\n0             Ferme t'y R'nao        ferme-t-y-r-nao   \n46                        NaN                    NaN   \n48                        NaN                    NaN   \n136                       NaN                    NaN   \n182          Bertrand Lejeune       bertrand-lejeune   \n...                       ...                    ...   \n320761     Roussette du Bugey     roussette-du-bugey   \n320763                Lobodis                lobodis   \n320764                    NaN                    NaN   \n320765  Sans marque,D.Lambert  sans-marque,d-lambert   \n320770                  Knorr                  knorr   \n\n                                               categories  \\\n0                                                     NaN   \n46                                          Filet de bœuf   \n48                                                    NaN   \n136                                                   NaN   \n182     Aliments et boissons à base de végétaux,Alimen...   \n...                                                   ...   \n320761  Boissons,Boissons alcoolisées,Vins,Vins blancs...   \n320763                                         thés verts   \n320764                                                NaN   \n320765  Viandes,Produits à tartiner,Charcuteries,Produ...   \n320770                                                NaN   \n\n                                          categories_tags  \\\n0                                                     NaN   \n46                                      fr:filet-de-boeuf   \n48                                                    NaN   \n136                                                   NaN   \n182     en:plant-based-foods-and-beverages,en:plant-ba...   \n...                                                   ...   \n320761  en:beverages,en:alcoholic-beverages,en:wines,e...   \n320763  en:plant-based-foods-and-beverages,en:beverage...   \n320764                                                NaN   \n320765  en:meats,en:spreads,en:prepared-meats,en:salte...   \n320770                                                NaN   \n\n                                            categories_fr            origins  \\\n0                                                 unknown                NaN   \n46                                         Filet-de-boeuf                NaN   \n48                                                unknown                NaN   \n136                                               unknown                NaN   \n182     Aliments et boissons à base de végétaux,Alimen...                NaN   \n...                                                   ...                ...   \n320761  Boissons,Boissons alcoolisées,Vins,Vins frança...  Flaxieu,Bugey,Ain   \n320763  Aliments et boissons à base de végétaux,Boisso...                NaN   \n320764                                            unknown                NaN   \n320765  Viandes,Produits à tartiner,Charcuteries,Produ...                NaN   \n320770                                            unknown                NaN   \n\n             origins_tags manufacturing_places manufacturing_places_tags  \\\n0                     NaN                  NaN                       NaN   \n46                    NaN                  NaN                       NaN   \n48                    NaN                  NaN                       NaN   \n136                   NaN                  NaN                       NaN   \n182                   NaN                  NaN                       NaN   \n...                   ...                  ...                       ...   \n320761  flaxieu,bugey,ain                  NaN                       NaN   \n320763                NaN                  NaN                       NaN   \n320764                NaN                  NaN                       NaN   \n320765                NaN                  NaN                       NaN   \n320770                NaN                  NaN                       NaN   \n\n                              labels  \\\n0                                NaN   \n46                               NaN   \n48                               NaN   \n136                              NaN   \n182                               AB   \n...                              ...   \n320761                           AOC   \n320763  AB,Bio européen,Max Havelaar   \n320764                           NaN   \n320765                           NaN   \n320770                           NaN   \n\n                                              labels_tags  \\\n0                                                     NaN   \n46                                                    NaN   \n48                                                    NaN   \n136                                                   NaN   \n182     en:organic,en:eu-organic,fr:ab-agriculture-bio...   \n...                                                   ...   \n320761                                             fr:aoc   \n320763  en:fair-trade,en:organic,en:eu-organic,en:max-...   \n320764                                                NaN   \n320765                                                NaN   \n320770                                                NaN   \n\n                                                labels_fr emb_codes  \\\n0                                                     NaN       NaN   \n46                                                    NaN       NaN   \n48                                                    NaN       NaN   \n136                                                   NaN       NaN   \n182            Bio,Bio européen,AB Agriculture Biologique       NaN   \n...                                                   ...       ...   \n320761                                                AOC       NaN   \n320763  Commerce équitable,Bio,Bio européen,Max Havela...       NaN   \n320764                                                NaN       NaN   \n320765                                                NaN       NaN   \n320770                                                NaN       NaN   \n\n       emb_codes_tags first_packaging_code_geo cities cities_tags  \\\n0                 NaN                      NaN    NaN         NaN   \n46                NaN                      NaN    NaN         NaN   \n48                NaN                      NaN    NaN         NaN   \n136               NaN                      NaN    NaN         NaN   \n182               NaN                      NaN    NaN         NaN   \n...               ...                      ...    ...         ...   \n320761            NaN                      NaN    NaN         NaN   \n320763            NaN                      NaN    NaN         NaN   \n320764            NaN                      NaN    NaN         NaN   \n320765            NaN                      NaN    NaN         NaN   \n320770            NaN                      NaN    NaN         NaN   \n\n                        purchase_places      stores countries countries_tags  \\\n0                                   NaN         NaN     en:FR      en:france   \n46                                  NaN         NaN    France      en:france   \n48                                  NaN         NaN     en:FR      en:france   \n136                       Roissy,France         NaN    France      en:france   \n182                                 NaN         NaN    France      en:france   \n...                                 ...         ...       ...            ...   \n320761  France,Châtillon-sur-Chalaronne  La Marande    France      en:france   \n320763                              NaN         NaN    France      en:france   \n320764                              NaN         NaN     en:FR      en:france   \n320765                              NaN         NaN    France      en:france   \n320770                              NaN         NaN     en:FR      en:france   \n\n       countries_fr                                   ingredients_text  \\\n0            France                                                NaN   \n46           France                                                NaN   \n48           France                                                NaN   \n136          France                                                NaN   \n182          France                                   lentilles vertes   \n...             ...                                                ...   \n320761       France                                                NaN   \n320763       France  thé vert, arôme naturel bergamote avec autres ...   \n320764       France                                                NaN   \n320765       France  viande d'oie, graisse de canard, épices, sel, ...   \n320770       France                                                NaN   \n\n       allergens allergens_fr                           traces  \\\n0            NaN          NaN                              NaN   \n46           NaN          NaN                              NaN   \n48           NaN          NaN                              NaN   \n136          NaN          NaN                              NaN   \n182          NaN          NaN                              NaN   \n...          ...          ...                              ...   \n320761       NaN          NaN  Anhydride sulfureux et sulfites   \n320763       NaN          NaN                              NaN   \n320764       NaN          NaN                              NaN   \n320765       NaN          NaN                              NaN   \n320770       NaN          NaN                              NaN   \n\n                             traces_tags                        traces_fr  \\\n0                                    NaN                              NaN   \n46                                   NaN                              NaN   \n48                                   NaN                              NaN   \n136                                  NaN                              NaN   \n182                                  NaN                              NaN   \n...                                  ...                              ...   \n320761  en:sulphur-dioxide-and-sulphites  Anhydride sulfureux et sulfites   \n320763                               NaN                              NaN   \n320764                               NaN                              NaN   \n320765                               NaN                              NaN   \n320770                               NaN                              NaN   \n\n       serving_size  additives_n  \\\n0               NaN          NaN   \n46              NaN          NaN   \n48              NaN          NaN   \n136             NaN          NaN   \n182             NaN          0.0   \n...             ...          ...   \n320761          NaN          NaN   \n320763          NaN          0.0   \n320764          NaN          NaN   \n320765          NaN          0.0   \n320770          NaN          NaN   \n\n                                                additives additives_tags  \\\n0                                                     NaN            NaN   \n46                                                    NaN            NaN   \n48                                                    NaN            NaN   \n136                                                   NaN            NaN   \n182      [ lentilles-vertes -> fr:lentilles-vertes  ] ...            NaN   \n...                                                   ...            ...   \n320761                                                NaN            NaN   \n320763   [ the-vert -> fr:the-vert  ]  [ the -> fr:the...            NaN   \n320764                                                NaN            NaN   \n320765   [ viande-d-oie -> fr:viande-d-oie  ]  [ viand...            NaN   \n320770                                                NaN            NaN   \n\n       additives_fr  ingredients_from_palm_oil_n  \\\n0               NaN                          NaN   \n46              NaN                          NaN   \n48              NaN                          NaN   \n136             NaN                          NaN   \n182             NaN                          0.0   \n...             ...                          ...   \n320761          NaN                          NaN   \n320763          NaN                          0.0   \n320764          NaN                          NaN   \n320765          NaN                          0.0   \n320770          NaN                          NaN   \n\n       ingredients_from_palm_oil_tags  \\\n0                                 NaN   \n46                                NaN   \n48                                NaN   \n136                               NaN   \n182                               NaN   \n...                               ...   \n320761                            NaN   \n320763                            NaN   \n320764                            NaN   \n320765                            NaN   \n320770                            NaN   \n\n        ingredients_that_may_be_from_palm_oil_n  \\\n0                                           NaN   \n46                                          NaN   \n48                                          NaN   \n136                                         NaN   \n182                                         0.0   \n...                                         ...   \n320761                                      NaN   \n320763                                      0.0   \n320764                                      NaN   \n320765                                      0.0   \n320770                                      NaN   \n\n       ingredients_that_may_be_from_palm_oil_tags nutrition_grade_fr  \\\n0                                             NaN                NaN   \n46                                            NaN                NaN   \n48                                            NaN                NaN   \n136                                           NaN                NaN   \n182                                           NaN                NaN   \n...                                           ...                ...   \n320761                                        NaN                NaN   \n320763                                        NaN                  c   \n320764                                        NaN                NaN   \n320765                                        NaN                NaN   \n320770                                        NaN                NaN   \n\n               pnns_groups_1          pnns_groups_2  \\\n0                    unknown                unknown   \n46                   unknown                unknown   \n48                   unknown                unknown   \n136                  unknown                unknown   \n182     Cereals and potatoes                Legumes   \n...                      ...                    ...   \n320761               unknown    Alcoholic beverages   \n320763             Beverages  Non-sugared beverages   \n320764               unknown                unknown   \n320765        Fish Meat Eggs         Processed meat   \n320770               unknown                unknown   \n\n                                                   states  \\\n0       en:to-be-completed, en:nutrition-facts-to-be-c...   \n46      en:to-be-completed, en:nutrition-facts-to-be-c...   \n48      en:to-be-completed, en:nutrition-facts-to-be-c...   \n136     en:to-be-completed, en:nutrition-facts-to-be-c...   \n182     en:to-be-completed, en:nutrition-facts-to-be-c...   \n...                                                   ...   \n320761  en:to-be-completed, en:nutrition-facts-complet...   \n320763  en:to-be-checked, en:complete, en:nutrition-fa...   \n320764  en:to-be-completed, en:nutrition-facts-to-be-c...   \n320765  en:to-be-checked, en:complete, en:nutrition-fa...   \n320770  en:to-be-completed, en:nutrition-facts-to-be-c...   \n\n                                              states_tags  \\\n0       en:to-be-completed,en:nutrition-facts-to-be-co...   \n46      en:to-be-completed,en:nutrition-facts-to-be-co...   \n48      en:to-be-completed,en:nutrition-facts-to-be-co...   \n136     en:to-be-completed,en:nutrition-facts-to-be-co...   \n182     en:to-be-completed,en:nutrition-facts-to-be-co...   \n...                                                   ...   \n320761  en:to-be-completed,en:nutrition-facts-complete...   \n320763  en:to-be-checked,en:complete,en:nutrition-fact...   \n320764  en:to-be-completed,en:nutrition-facts-to-be-co...   \n320765  en:to-be-checked,en:complete,en:nutrition-fact...   \n320770  en:to-be-completed,en:nutrition-facts-to-be-co...   \n\n                                                states_fr  \\\n0       A compléter,Informations nutritionnelles à com...   \n46      A compléter,Informations nutritionnelles à com...   \n48      A compléter,Informations nutritionnelles à com...   \n136     A compléter,Informations nutritionnelles à com...   \n182     A compléter,Informations nutritionnelles à com...   \n...                                                   ...   \n320761  A compléter,Informations nutritionnelles compl...   \n320763  A vérifier,Complet,Informations nutritionnelle...   \n320764  A compléter,Informations nutritionnelles à com...   \n320765  A vérifier,Complet,Informations nutritionnelle...   \n320770  A compléter,Informations nutritionnelles à com...   \n\n                             main_category  \\\n0                                      NaN   \n46                       fr:filet-de-boeuf   \n48                                     NaN   \n136                                    NaN   \n182     en:plant-based-foods-and-beverages   \n...                                    ...   \n320761                        en:beverages   \n320763                       en:green-teas   \n320764                                 NaN   \n320765                   en:salted-spreads   \n320770                                 NaN   \n\n                               main_category_fr  \\\n0                                       unknown   \n46                               Filet-de-boeuf   \n48                                      unknown   \n136                                     unknown   \n182     Aliments et boissons à base de végétaux   \n...                                         ...   \n320761                                 Boissons   \n320763                               Thés verts   \n320764                                  unknown   \n320765                Produits à tartiner salés   \n320770                                  unknown   \n\n                                                image_url  \\\n0                                                     NaN   \n46      http://fr.openfoodfacts.org/images/products/00...   \n48      http://fr.openfoodfacts.org/images/products/00...   \n136     http://fr.openfoodfacts.org/images/products/00...   \n182     http://fr.openfoodfacts.org/images/products/00...   \n...                                                   ...   \n320761  http://fr.openfoodfacts.org/images/products/99...   \n320763  http://fr.openfoodfacts.org/images/products/99...   \n320764  http://fr.openfoodfacts.org/images/products/99...   \n320765  http://fr.openfoodfacts.org/images/products/99...   \n320770                                                NaN   \n\n                                          image_small_url  energy_100g  \\\n0                                                     NaN          NaN   \n46      http://fr.openfoodfacts.org/images/products/00...          NaN   \n48      http://fr.openfoodfacts.org/images/products/00...          NaN   \n136     http://fr.openfoodfacts.org/images/products/00...          NaN   \n182     http://fr.openfoodfacts.org/images/products/00...          NaN   \n...                                                   ...          ...   \n320761  http://fr.openfoodfacts.org/images/products/99...          NaN   \n320763  http://fr.openfoodfacts.org/images/products/99...         21.0   \n320764  http://fr.openfoodfacts.org/images/products/99...          NaN   \n320765  http://fr.openfoodfacts.org/images/products/99...          NaN   \n320770                                                NaN          NaN   \n\n        energy-from-fat_100g  fat_100g  saturated-fat_100g  \\\n0                        NaN       NaN                 NaN   \n46                       NaN       NaN                 NaN   \n48                       NaN       NaN                 NaN   \n136                      NaN       NaN                 NaN   \n182                      NaN       NaN                 NaN   \n...                      ...       ...                 ...   \n320761                   NaN       NaN                 NaN   \n320763                   NaN       0.2                 0.2   \n320764                   NaN       NaN                 NaN   \n320765                   NaN       NaN                 NaN   \n320770                   NaN       NaN                 NaN   \n\n        caprylic-acid_100g  capric-acid_100g  lauric-acid_100g  \\\n0                      NaN               NaN               NaN   \n46                     NaN               NaN               NaN   \n48                     NaN               NaN               NaN   \n136                    NaN               NaN               NaN   \n182                    NaN               NaN               NaN   \n...                    ...               ...               ...   \n320761                 NaN               NaN               NaN   \n320763                 NaN               NaN               NaN   \n320764                 NaN               NaN               NaN   \n320765                 NaN               NaN               NaN   \n320770                 NaN               NaN               NaN   \n\n        myristic-acid_100g  palmitic-acid_100g  stearic-acid_100g  \\\n0                      NaN                 NaN                NaN   \n46                     NaN                 NaN                NaN   \n48                     NaN                 NaN                NaN   \n136                    NaN                 NaN                NaN   \n182                    NaN                 NaN                NaN   \n...                    ...                 ...                ...   \n320761                 NaN                 NaN                NaN   \n320763                 NaN                 NaN                NaN   \n320764                 NaN                 NaN                NaN   \n320765                 NaN                 NaN                NaN   \n320770                 NaN                 NaN                NaN   \n\n        arachidic-acid_100g  behenic-acid_100g  montanic-acid_100g  \\\n0                       NaN                NaN                 NaN   \n46                      NaN                NaN                 NaN   \n48                      NaN                NaN                 NaN   \n136                     NaN                NaN                 NaN   \n182                     NaN                NaN                 NaN   \n...                     ...                ...                 ...   \n320761                  NaN                NaN                 NaN   \n320763                  NaN                NaN                 NaN   \n320764                  NaN                NaN                 NaN   \n320765                  NaN                NaN                 NaN   \n320770                  NaN                NaN                 NaN   \n\n        monounsaturated-fat_100g  polyunsaturated-fat_100g  omega-3-fat_100g  \\\n0                            NaN                       NaN               NaN   \n46                           NaN                       NaN               NaN   \n48                           NaN                       NaN               NaN   \n136                          NaN                       NaN               NaN   \n182                          NaN                       NaN               NaN   \n...                          ...                       ...               ...   \n320761                       NaN                       NaN               NaN   \n320763                       NaN                       NaN               NaN   \n320764                       NaN                       NaN               NaN   \n320765                       NaN                       NaN               NaN   \n320770                       NaN                       NaN               NaN   \n\n        alpha-linolenic-acid_100g  eicosapentaenoic-acid_100g  \\\n0                             NaN                         NaN   \n46                            NaN                         NaN   \n48                            NaN                         NaN   \n136                           NaN                         NaN   \n182                           NaN                         NaN   \n...                           ...                         ...   \n320761                        NaN                         NaN   \n320763                        NaN                         NaN   \n320764                        NaN                         NaN   \n320765                        NaN                         NaN   \n320770                        NaN                         NaN   \n\n        docosahexaenoic-acid_100g  omega-6-fat_100g  linoleic-acid_100g  \\\n0                             NaN               NaN                 NaN   \n46                            NaN               NaN                 NaN   \n48                            NaN               NaN                 NaN   \n136                           NaN               NaN                 NaN   \n182                           NaN               NaN                 NaN   \n...                           ...               ...                 ...   \n320761                        NaN               NaN                 NaN   \n320763                        NaN               NaN                 NaN   \n320764                        NaN               NaN                 NaN   \n320765                        NaN               NaN                 NaN   \n320770                        NaN               NaN                 NaN   \n\n        arachidonic-acid_100g  gamma-linolenic-acid_100g  \\\n0                         NaN                        NaN   \n46                        NaN                        NaN   \n48                        NaN                        NaN   \n136                       NaN                        NaN   \n182                       NaN                        NaN   \n...                       ...                        ...   \n320761                    NaN                        NaN   \n320763                    NaN                        NaN   \n320764                    NaN                        NaN   \n320765                    NaN                        NaN   \n320770                    NaN                        NaN   \n\n        dihomo-gamma-linolenic-acid_100g  omega-9-fat_100g  oleic-acid_100g  \\\n0                                    NaN               NaN              NaN   \n46                                   NaN               NaN              NaN   \n48                                   NaN               NaN              NaN   \n136                                  NaN               NaN              NaN   \n182                                  NaN               NaN              NaN   \n...                                  ...               ...              ...   \n320761                               NaN               NaN              NaN   \n320763                               NaN               NaN              NaN   \n320764                               NaN               NaN              NaN   \n320765                               NaN               NaN              NaN   \n320770                               NaN               NaN              NaN   \n\n        gondoic-acid_100g  trans-fat_100g  cholesterol_100g  \\\n0                     NaN             NaN               NaN   \n46                    NaN             NaN               NaN   \n48                    NaN             NaN               NaN   \n136                   NaN             NaN               NaN   \n182                   NaN             NaN               NaN   \n...                   ...             ...               ...   \n320761                NaN             NaN               NaN   \n320763                NaN             NaN               NaN   \n320764                NaN             NaN               NaN   \n320765                NaN             NaN               NaN   \n320770                NaN             NaN               NaN   \n\n        carbohydrates_100g  sugars_100g  sucrose_100g  glucose_100g  \\\n0                      NaN          NaN           NaN           NaN   \n46                     NaN          NaN           NaN           NaN   \n48                     NaN          NaN           NaN           NaN   \n136                    NaN          NaN           NaN           NaN   \n182                    NaN          NaN           NaN           NaN   \n...                    ...          ...           ...           ...   \n320761                 NaN          NaN           NaN           NaN   \n320763                 0.5          0.5           NaN           NaN   \n320764                 NaN          NaN           NaN           NaN   \n320765                 NaN          NaN           NaN           NaN   \n320770                 NaN          NaN           NaN           NaN   \n\n        fructose_100g  lactose_100g  maltose_100g  maltodextrins_100g  \\\n0                 NaN           NaN           NaN                 NaN   \n46                NaN           NaN           NaN                 NaN   \n48                NaN           NaN           NaN                 NaN   \n136               NaN           NaN           NaN                 NaN   \n182               NaN           NaN           NaN                 NaN   \n...               ...           ...           ...                 ...   \n320761            NaN           NaN           NaN                 NaN   \n320763            NaN           NaN           NaN                 NaN   \n320764            NaN           NaN           NaN                 NaN   \n320765            NaN           NaN           NaN                 NaN   \n320770            NaN           NaN           NaN                 NaN   \n\n        starch_100g  polyols_100g  fiber_100g  proteins_100g  casein_100g  \\\n0               NaN           NaN         NaN            NaN          NaN   \n46              NaN           NaN         NaN            NaN          NaN   \n48              NaN           NaN         NaN            NaN          NaN   \n136             NaN           NaN         NaN            NaN          NaN   \n182             NaN           NaN         NaN            NaN          NaN   \n...             ...           ...         ...            ...          ...   \n320761          NaN           NaN         NaN            NaN          NaN   \n320763          NaN           NaN         0.2            0.5          NaN   \n320764          NaN           NaN         NaN            NaN          NaN   \n320765          NaN           NaN         NaN            NaN          NaN   \n320770          NaN           NaN         NaN            NaN          NaN   \n\n        serum-proteins_100g  nucleotides_100g  salt_100g  sodium_100g  \\\n0                       NaN               NaN        NaN          NaN   \n46                      NaN               NaN        NaN          NaN   \n48                      NaN               NaN        NaN          NaN   \n136                     NaN               NaN        NaN          NaN   \n182                     NaN               NaN        NaN          NaN   \n...                     ...               ...        ...          ...   \n320761                  NaN               NaN        NaN          NaN   \n320763                  NaN               NaN     0.0254         0.01   \n320764                  NaN               NaN        NaN          NaN   \n320765                  NaN               NaN        NaN          NaN   \n320770                  NaN               NaN        NaN          NaN   \n\n        alcohol_100g  vitamin-a_100g  beta-carotene_100g  vitamin-d_100g  \\\n0                NaN             NaN                 NaN             NaN   \n46               NaN             NaN                 NaN             NaN   \n48               NaN             NaN                 NaN             NaN   \n136              NaN             NaN                 NaN             NaN   \n182              NaN             NaN                 NaN             NaN   \n...              ...             ...                 ...             ...   \n320761          12.0             NaN                 NaN             NaN   \n320763           NaN             NaN                 NaN             NaN   \n320764           NaN             NaN                 NaN             NaN   \n320765           NaN             NaN                 NaN             NaN   \n320770           NaN             NaN                 NaN             NaN   \n\n        vitamin-e_100g  vitamin-k_100g  vitamin-c_100g  vitamin-b1_100g  \\\n0                  NaN             NaN             NaN              NaN   \n46                 NaN             NaN             NaN              NaN   \n48                 NaN             NaN             NaN              NaN   \n136                NaN             NaN             NaN              NaN   \n182                NaN             NaN             NaN              NaN   \n...                ...             ...             ...              ...   \n320761             NaN             NaN             NaN              NaN   \n320763             NaN             NaN             NaN              NaN   \n320764             NaN             NaN             NaN              NaN   \n320765             NaN             NaN             NaN              NaN   \n320770             NaN             NaN             NaN              NaN   \n\n        vitamin-b2_100g  vitamin-pp_100g  vitamin-b6_100g  vitamin-b9_100g  \\\n0                   NaN              NaN              NaN              NaN   \n46                  NaN              NaN              NaN              NaN   \n48                  NaN              NaN              NaN              NaN   \n136                 NaN              NaN              NaN              NaN   \n182                 NaN              NaN              NaN              NaN   \n...                 ...              ...              ...              ...   \n320761              NaN              NaN              NaN              NaN   \n320763              NaN              NaN              NaN              NaN   \n320764              NaN              NaN              NaN              NaN   \n320765              NaN              NaN              NaN              NaN   \n320770              NaN              NaN              NaN              NaN   \n\n        folates_100g  vitamin-b12_100g  biotin_100g  pantothenic-acid_100g  \\\n0                NaN               NaN          NaN                    NaN   \n46               NaN               NaN          NaN                    NaN   \n48               NaN               NaN          NaN                    NaN   \n136              NaN               NaN          NaN                    NaN   \n182              NaN               NaN          NaN                    NaN   \n...              ...               ...          ...                    ...   \n320761           NaN               NaN          NaN                    NaN   \n320763           NaN               NaN          NaN                    NaN   \n320764           NaN               NaN          NaN                    NaN   \n320765           NaN               NaN          NaN                    NaN   \n320770           NaN               NaN          NaN                    NaN   \n\n        silica_100g  bicarbonate_100g  potassium_100g  chloride_100g  \\\n0               NaN               NaN             NaN            NaN   \n46              NaN               NaN             NaN            NaN   \n48              NaN               NaN             NaN            NaN   \n136             NaN               NaN             NaN            NaN   \n182             NaN               NaN             NaN            NaN   \n...             ...               ...             ...            ...   \n320761          NaN               NaN             NaN            NaN   \n320763          NaN               NaN             NaN            NaN   \n320764          NaN               NaN             NaN            NaN   \n320765          NaN               NaN             NaN            NaN   \n320770          NaN               NaN             NaN            NaN   \n\n        calcium_100g  phosphorus_100g  iron_100g  magnesium_100g  zinc_100g  \\\n0                NaN              NaN        NaN             NaN        NaN   \n46               NaN              NaN        NaN             NaN        NaN   \n48               NaN              NaN        NaN             NaN        NaN   \n136              NaN              NaN        NaN             NaN        NaN   \n182              NaN              NaN        NaN             NaN        NaN   \n...              ...              ...        ...             ...        ...   \n320761           NaN              NaN        NaN             NaN        NaN   \n320763           NaN              NaN        NaN             NaN        NaN   \n320764           NaN              NaN        NaN             NaN        NaN   \n320765           NaN              NaN        NaN             NaN        NaN   \n320770           NaN              NaN        NaN             NaN        NaN   \n\n        copper_100g  manganese_100g  fluoride_100g  selenium_100g  \\\n0               NaN             NaN            NaN            NaN   \n46              NaN             NaN            NaN            NaN   \n48              NaN             NaN            NaN            NaN   \n136             NaN             NaN            NaN            NaN   \n182             NaN             NaN            NaN            NaN   \n...             ...             ...            ...            ...   \n320761          NaN             NaN            NaN            NaN   \n320763          NaN             NaN            NaN            NaN   \n320764          NaN             NaN            NaN            NaN   \n320765          NaN             NaN            NaN            NaN   \n320770          NaN             NaN            NaN            NaN   \n\n        chromium_100g  molybdenum_100g  iodine_100g  caffeine_100g  \\\n0                 NaN              NaN          NaN            NaN   \n46                NaN              NaN          NaN            NaN   \n48                NaN              NaN          NaN            NaN   \n136               NaN              NaN          NaN            NaN   \n182               NaN              NaN          NaN            NaN   \n...               ...              ...          ...            ...   \n320761            NaN              NaN          NaN            NaN   \n320763            NaN              NaN          NaN            NaN   \n320764            NaN              NaN          NaN            NaN   \n320765            NaN              NaN          NaN            NaN   \n320770            NaN              NaN          NaN            NaN   \n\n        taurine_100g  ph_100g  fruits-vegetables-nuts_100g  \\\n0                NaN      NaN                          NaN   \n46               NaN      NaN                          NaN   \n48               NaN      NaN                          NaN   \n136              NaN      NaN                          NaN   \n182              NaN      NaN                          NaN   \n...              ...      ...                          ...   \n320761           NaN      NaN                          NaN   \n320763           NaN      NaN                          NaN   \n320764           NaN      NaN                          NaN   \n320765           NaN      NaN                          NaN   \n320770           NaN      NaN                          NaN   \n\n        collagen-meat-protein-ratio_100g  cocoa_100g  carbon-footprint_100g  \\\n0                                    NaN         NaN                    NaN   \n46                                   NaN         NaN                    NaN   \n48                                   NaN         NaN                    NaN   \n136                                  NaN         NaN                    NaN   \n182                                  NaN         NaN                    NaN   \n...                                  ...         ...                    ...   \n320761                               NaN         NaN                    NaN   \n320763                               NaN         NaN                    NaN   \n320764                               NaN         NaN                    NaN   \n320765                               NaN         NaN                    NaN   \n320770                               NaN         NaN                    NaN   \n\n        nutrition-score-fr_100g  nutrition-score-uk_100g  \n0                           NaN                      NaN  \n46                          NaN                      NaN  \n48                          NaN                      NaN  \n136                         NaN                      NaN  \n182                         NaN                      NaN  \n...                         ...                      ...  \n320761                      NaN                      NaN  \n320763                      2.0                      0.0  \n320764                      NaN                      NaN  \n320765                      NaN                      NaN  \n320770                      NaN                      NaN  \n\n[94271 rows x 146 columns]","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>code</th>\n      <th>url</th>\n      <th>creator</th>\n      <th>created_t</th>\n      <th>created_datetime</th>\n      <th>last_modified_t</th>\n      <th>last_modified_datetime</th>\n      <th>product_name</th>\n      <th>generic_name</th>\n      <th>quantity</th>\n      <th>packaging</th>\n      <th>packaging_tags</th>\n      <th>brands</th>\n      <th>brands_tags</th>\n      <th>categories</th>\n      <th>categories_tags</th>\n      <th>categories_fr</th>\n      <th>origins</th>\n      <th>origins_tags</th>\n      <th>manufacturing_places</th>\n      <th>manufacturing_places_tags</th>\n      <th>labels</th>\n      <th>labels_tags</th>\n      <th>labels_fr</th>\n      <th>emb_codes</th>\n      <th>emb_codes_tags</th>\n      <th>first_packaging_code_geo</th>\n      <th>cities</th>\n      <th>cities_tags</th>\n      <th>purchase_places</th>\n      <th>stores</th>\n      <th>countries</th>\n      <th>countries_tags</th>\n      <th>countries_fr</th>\n      <th>ingredients_text</th>\n      <th>allergens</th>\n      <th>allergens_fr</th>\n      <th>traces</th>\n      <th>traces_tags</th>\n      <th>traces_fr</th>\n      <th>serving_size</th>\n      <th>additives_n</th>\n      <th>additives</th>\n      <th>additives_tags</th>\n      <th>additives_fr</th>\n      <th>ingredients_from_palm_oil_n</th>\n      <th>ingredients_from_palm_oil_tags</th>\n      <th>ingredients_that_may_be_from_palm_oil_n</th>\n      <th>ingredients_that_may_be_from_palm_oil_tags</th>\n      <th>nutrition_grade_fr</th>\n      <th>pnns_groups_1</th>\n      <th>pnns_groups_2</th>\n      <th>states</th>\n      <th>states_tags</th>\n      <th>states_fr</th>\n      <th>main_category</th>\n      <th>main_category_fr</th>\n      <th>image_url</th>\n      <th>image_small_url</th>\n      <th>energy_100g</th>\n      <th>energy-from-fat_100g</th>\n      <th>fat_100g</th>\n      <th>saturated-fat_100g</th>\n      <th>caprylic-acid_100g</th>\n      <th>capric-acid_100g</th>\n      <th>lauric-acid_100g</th>\n      <th>myristic-acid_100g</th>\n      <th>palmitic-acid_100g</th>\n      <th>stearic-acid_100g</th>\n      <th>arachidic-acid_100g</th>\n      <th>behenic-acid_100g</th>\n      <th>montanic-acid_100g</th>\n      <th>monounsaturated-fat_100g</th>\n      <th>polyunsaturated-fat_100g</th>\n      <th>omega-3-fat_100g</th>\n      <th>alpha-linolenic-acid_100g</th>\n      <th>eicosapentaenoic-acid_100g</th>\n      <th>docosahexaenoic-acid_100g</th>\n      <th>omega-6-fat_100g</th>\n      <th>linoleic-acid_100g</th>\n      <th>arachidonic-acid_100g</th>\n      <th>gamma-linolenic-acid_100g</th>\n      <th>dihomo-gamma-linolenic-acid_100g</th>\n      <th>omega-9-fat_100g</th>\n      <th>oleic-acid_100g</th>\n      <th>gondoic-acid_100g</th>\n      <th>trans-fat_100g</th>\n      <th>cholesterol_100g</th>\n      <th>carbohydrates_100g</th>\n      <th>sugars_100g</th>\n      <th>sucrose_100g</th>\n      <th>glucose_100g</th>\n      <th>fructose_100g</th>\n      <th>lactose_100g</th>\n      <th>maltose_100g</th>\n      <th>maltodextrins_100g</th>\n      <th>starch_100g</th>\n      <th>polyols_100g</th>\n      <th>fiber_100g</th>\n      <th>proteins_100g</th>\n      <th>casein_100g</th>\n      <th>serum-proteins_100g</th>\n      <th>nucleotides_100g</th>\n      <th>salt_100g</th>\n      <th>sodium_100g</th>\n      <th>alcohol_100g</th>\n      <th>vitamin-a_100g</th>\n      <th>beta-carotene_100g</th>\n      <th>vitamin-d_100g</th>\n      <th>vitamin-e_100g</th>\n      <th>vitamin-k_100g</th>\n      <th>vitamin-c_100g</th>\n      <th>vitamin-b1_100g</th>\n      <th>vitamin-b2_100g</th>\n      <th>vitamin-pp_100g</th>\n      <th>vitamin-b6_100g</th>\n      <th>vitamin-b9_100g</th>\n      <th>folates_100g</th>\n      <th>vitamin-b12_100g</th>\n      <th>biotin_100g</th>\n      <th>pantothenic-acid_100g</th>\n      <th>silica_100g</th>\n      <th>bicarbonate_100g</th>\n      <th>potassium_100g</th>\n      <th>chloride_100g</th>\n      <th>calcium_100g</th>\n      <th>phosphorus_100g</th>\n      <th>iron_100g</th>\n      <th>magnesium_100g</th>\n      <th>zinc_100g</th>\n      <th>copper_100g</th>\n      <th>manganese_100g</th>\n      <th>fluoride_100g</th>\n      <th>selenium_100g</th>\n      <th>chromium_100g</th>\n      <th>molybdenum_100g</th>\n      <th>iodine_100g</th>\n      <th>caffeine_100g</th>\n      <th>taurine_100g</th>\n      <th>ph_100g</th>\n      <th>fruits-vegetables-nuts_100g</th>\n      <th>collagen-meat-protein-ratio_100g</th>\n      <th>cocoa_100g</th>\n      <th>carbon-footprint_100g</th>\n      <th>nutrition-score-fr_100g</th>\n      <th>nutrition-score-uk_100g</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>3087</td>\n      <td>http://world-fr.openfoodfacts.org/produit/0000...</td>\n      <td>openfoodfacts-contributors</td>\n      <td>1474103866</td>\n      <td>2016-09-17T09:17:46Z</td>\n      <td>1474103893</td>\n      <td>2016-09-17T09:18:13Z</td>\n      <td>Farine de blé noir</td>\n      <td>NaN</td>\n      <td>1kg</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Ferme t'y R'nao</td>\n      <td>ferme-t-y-r-nao</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>unknown</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>en:FR</td>\n      <td>en:france</td>\n      <td>France</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>unknown</td>\n      <td>unknown</td>\n      <td>en:to-be-completed, en:nutrition-facts-to-be-c...</td>\n      <td>en:to-be-completed,en:nutrition-facts-to-be-co...</td>\n      <td>A compléter,Informations nutritionnelles à com...</td>\n      <td>NaN</td>\n      <td>unknown</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>46</th>\n      <td>24600</td>\n      <td>http://world-fr.openfoodfacts.org/produit/0000...</td>\n      <td>date-limite-app</td>\n      <td>1434530704</td>\n      <td>2015-06-17T08:45:04Z</td>\n      <td>1434535914</td>\n      <td>2015-06-17T10:11:54Z</td>\n      <td>Filet de bœuf</td>\n      <td>NaN</td>\n      <td>2.46 kg</td>\n      <td>plastique</td>\n      <td>plastique</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Filet de bœuf</td>\n      <td>fr:filet-de-boeuf</td>\n      <td>Filet-de-boeuf</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>France</td>\n      <td>en:france</td>\n      <td>France</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>unknown</td>\n      <td>unknown</td>\n      <td>en:to-be-completed, en:nutrition-facts-to-be-c...</td>\n      <td>en:to-be-completed,en:nutrition-facts-to-be-co...</td>\n      <td>A compléter,Informations nutritionnelles à com...</td>\n      <td>fr:filet-de-boeuf</td>\n      <td>Filet-de-boeuf</td>\n      <td>http://fr.openfoodfacts.org/images/products/00...</td>\n      <td>http://fr.openfoodfacts.org/images/products/00...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>48</th>\n      <td>27205</td>\n      <td>http://world-fr.openfoodfacts.org/produit/0000...</td>\n      <td>tacinte</td>\n      <td>1458238630</td>\n      <td>2016-03-17T18:17:10Z</td>\n      <td>1458238638</td>\n      <td>2016-03-17T18:17:18Z</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>unknown</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>en:FR</td>\n      <td>en:france</td>\n      <td>France</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>unknown</td>\n      <td>unknown</td>\n      <td>en:to-be-completed, en:nutrition-facts-to-be-c...</td>\n      <td>en:to-be-completed,en:nutrition-facts-to-be-co...</td>\n      <td>A compléter,Informations nutritionnelles à com...</td>\n      <td>NaN</td>\n      <td>unknown</td>\n      <td>http://fr.openfoodfacts.org/images/products/00...</td>\n      <td>http://fr.openfoodfacts.org/images/products/00...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>136</th>\n      <td>39259</td>\n      <td>http://world-fr.openfoodfacts.org/produit/0000...</td>\n      <td>tacinte</td>\n      <td>1422221773</td>\n      <td>2015-01-25T21:36:13Z</td>\n      <td>1473538082</td>\n      <td>2016-09-10T20:08:02Z</td>\n      <td>Twix x2</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>unknown</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Roissy,France</td>\n      <td>NaN</td>\n      <td>France</td>\n      <td>en:france</td>\n      <td>France</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>unknown</td>\n      <td>unknown</td>\n      <td>en:to-be-completed, en:nutrition-facts-to-be-c...</td>\n      <td>en:to-be-completed,en:nutrition-facts-to-be-co...</td>\n      <td>A compléter,Informations nutritionnelles à com...</td>\n      <td>NaN</td>\n      <td>unknown</td>\n      <td>http://fr.openfoodfacts.org/images/products/00...</td>\n      <td>http://fr.openfoodfacts.org/images/products/00...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>182</th>\n      <td>5200016</td>\n      <td>http://world-fr.openfoodfacts.org/produit/0000...</td>\n      <td>sigoise</td>\n      <td>1441186657</td>\n      <td>2015-09-02T09:37:37Z</td>\n      <td>1442570752</td>\n      <td>2015-09-18T10:05:52Z</td>\n      <td>lentilles vertes</td>\n      <td>NaN</td>\n      <td>1 kg</td>\n      <td>Sachet plastique</td>\n      <td>sachet-plastique</td>\n      <td>Bertrand Lejeune</td>\n      <td>bertrand-lejeune</td>\n      <td>Aliments et boissons à base de végétaux,Alimen...</td>\n      <td>en:plant-based-foods-and-beverages,en:plant-ba...</td>\n      <td>Aliments et boissons à base de végétaux,Alimen...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>AB</td>\n      <td>en:organic,en:eu-organic,fr:ab-agriculture-bio...</td>\n      <td>Bio,Bio européen,AB Agriculture Biologique</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>France</td>\n      <td>en:france</td>\n      <td>France</td>\n      <td>lentilles vertes</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0.0</td>\n      <td>[ lentilles-vertes -&gt; fr:lentilles-vertes  ] ...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0.0</td>\n      <td>NaN</td>\n      <td>0.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Cereals and potatoes</td>\n      <td>Legumes</td>\n      <td>en:to-be-completed, en:nutrition-facts-to-be-c...</td>\n      <td>en:to-be-completed,en:nutrition-facts-to-be-co...</td>\n      <td>A compléter,Informations nutritionnelles à com...</td>\n      <td>en:plant-based-foods-and-beverages</td>\n      <td>Aliments et boissons à base de végétaux</td>\n      <td>http://fr.openfoodfacts.org/images/products/00...</td>\n      <td>http://fr.openfoodfacts.org/images/products/00...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</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      <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      <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      <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      <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      <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      <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      <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>320761</th>\n      <td>9906410000009</td>\n      <td>http://world-fr.openfoodfacts.org/produit/9906...</td>\n      <td>agamitsudo</td>\n      <td>1373480408</td>\n      <td>2013-07-10T18:20:08Z</td>\n      <td>1451851215</td>\n      <td>2016-01-03T20:00:15Z</td>\n      <td>Roussette du Bugey (2011)</td>\n      <td>Vins blanc du Bugey</td>\n      <td>750 ml</td>\n      <td>Bouteille en verre</td>\n      <td>bouteille-en-verre</td>\n      <td>Roussette du Bugey</td>\n      <td>roussette-du-bugey</td>\n      <td>Boissons,Boissons alcoolisées,Vins,Vins blancs...</td>\n      <td>en:beverages,en:alcoholic-beverages,en:wines,e...</td>\n      <td>Boissons,Boissons alcoolisées,Vins,Vins frança...</td>\n      <td>Flaxieu,Bugey,Ain</td>\n      <td>flaxieu,bugey,ain</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>AOC</td>\n      <td>fr:aoc</td>\n      <td>AOC</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>France,Châtillon-sur-Chalaronne</td>\n      <td>La Marande</td>\n      <td>France</td>\n      <td>en:france</td>\n      <td>France</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Anhydride sulfureux et sulfites</td>\n      <td>en:sulphur-dioxide-and-sulphites</td>\n      <td>Anhydride sulfureux et sulfites</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>unknown</td>\n      <td>Alcoholic beverages</td>\n      <td>en:to-be-completed, en:nutrition-facts-complet...</td>\n      <td>en:to-be-completed,en:nutrition-facts-complete...</td>\n      <td>A compléter,Informations nutritionnelles compl...</td>\n      <td>en:beverages</td>\n      <td>Boissons</td>\n      <td>http://fr.openfoodfacts.org/images/products/99...</td>\n      <td>http://fr.openfoodfacts.org/images/products/99...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>12.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>320763</th>\n      <td>99111250</td>\n      <td>http://world-fr.openfoodfacts.org/produit/9911...</td>\n      <td>balooval</td>\n      <td>1367163039</td>\n      <td>2013-04-28T15:30:39Z</td>\n      <td>1371690556</td>\n      <td>2013-06-20T01:09:16Z</td>\n      <td>Thé vert Earl grey</td>\n      <td>thé bio équitable</td>\n      <td>50 g</td>\n      <td>boîte,carton</td>\n      <td>boite,carton</td>\n      <td>Lobodis</td>\n      <td>lobodis</td>\n      <td>thés verts</td>\n      <td>en:plant-based-foods-and-beverages,en:beverage...</td>\n      <td>Aliments et boissons à base de végétaux,Boisso...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>AB,Bio européen,Max Havelaar</td>\n      <td>en:fair-trade,en:organic,en:eu-organic,en:max-...</td>\n      <td>Commerce équitable,Bio,Bio européen,Max Havela...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>France</td>\n      <td>en:france</td>\n      <td>France</td>\n      <td>thé vert, arôme naturel bergamote avec autres ...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0.0</td>\n      <td>[ the-vert -&gt; fr:the-vert  ]  [ the -&gt; fr:the...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0.0</td>\n      <td>NaN</td>\n      <td>0.0</td>\n      <td>NaN</td>\n      <td>c</td>\n      <td>Beverages</td>\n      <td>Non-sugared beverages</td>\n      <td>en:to-be-checked, en:complete, en:nutrition-fa...</td>\n      <td>en:to-be-checked,en:complete,en:nutrition-fact...</td>\n      <td>A vérifier,Complet,Informations nutritionnelle...</td>\n      <td>en:green-teas</td>\n      <td>Thés verts</td>\n      <td>http://fr.openfoodfacts.org/images/products/99...</td>\n      <td>http://fr.openfoodfacts.org/images/products/99...</td>\n      <td>21.0</td>\n      <td>NaN</td>\n      <td>0.2</td>\n      <td>0.2</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0.5</td>\n      <td>0.5</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0.2</td>\n      <td>0.5</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0.0254</td>\n      <td>0.01</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>2.0</td>\n      <td>0.0</td>\n    </tr>\n    <tr>\n      <th>320764</th>\n      <td>9918</td>\n      <td>http://world-fr.openfoodfacts.org/produit/9918...</td>\n      <td>woshilapin</td>\n      <td>1430167954</td>\n      <td>2015-04-27T20:52:34Z</td>\n      <td>1430167992</td>\n      <td>2015-04-27T20:53:12Z</td>\n      <td>Cheese cake thé vert, yuzu</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>unknown</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>en:FR</td>\n      <td>en:france</td>\n      <td>France</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>unknown</td>\n      <td>unknown</td>\n      <td>en:to-be-completed, en:nutrition-facts-to-be-c...</td>\n      <td>en:to-be-completed,en:nutrition-facts-to-be-co...</td>\n      <td>A compléter,Informations nutritionnelles à com...</td>\n      <td>NaN</td>\n      <td>unknown</td>\n      <td>http://fr.openfoodfacts.org/images/products/99...</td>\n      <td>http://fr.openfoodfacts.org/images/products/99...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>320765</th>\n      <td>9935010000003</td>\n      <td>http://world-fr.openfoodfacts.org/produit/9935...</td>\n      <td>sebleouf</td>\n      <td>1446293229</td>\n      <td>2015-10-31T12:07:09Z</td>\n      <td>1446376839</td>\n      <td>2015-11-01T11:20:39Z</td>\n      <td>Rillette d'oie</td>\n      <td>NaN</td>\n      <td>180 g</td>\n      <td>Pot,Verre</td>\n      <td>pot,verre</td>\n      <td>Sans marque,D.Lambert</td>\n      <td>sans-marque,d-lambert</td>\n      <td>Viandes,Produits à tartiner,Charcuteries,Produ...</td>\n      <td>en:meats,en:spreads,en:prepared-meats,en:salte...</td>\n      <td>Viandes,Produits à tartiner,Charcuteries,Produ...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>France</td>\n      <td>en:france</td>\n      <td>France</td>\n      <td>viande d'oie, graisse de canard, épices, sel, ...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0.0</td>\n      <td>[ viande-d-oie -&gt; fr:viande-d-oie  ]  [ viand...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0.0</td>\n      <td>NaN</td>\n      <td>0.0</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Fish Meat Eggs</td>\n      <td>Processed meat</td>\n      <td>en:to-be-checked, en:complete, en:nutrition-fa...</td>\n      <td>en:to-be-checked,en:complete,en:nutrition-fact...</td>\n      <td>A vérifier,Complet,Informations nutritionnelle...</td>\n      <td>en:salted-spreads</td>\n      <td>Produits à tartiner salés</td>\n      <td>http://fr.openfoodfacts.org/images/products/99...</td>\n      <td>http://fr.openfoodfacts.org/images/products/99...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>320770</th>\n      <td>9980282863788</td>\n      <td>http://world-fr.openfoodfacts.org/produit/9980...</td>\n      <td>openfoodfacts-contributors</td>\n      <td>1492340089</td>\n      <td>2017-04-16T10:54:49Z</td>\n      <td>1492340089</td>\n      <td>2017-04-16T10:54:49Z</td>\n      <td>Tomates aux Vermicelles</td>\n      <td>NaN</td>\n      <td>67g</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Knorr</td>\n      <td>knorr</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>unknown</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>en:FR</td>\n      <td>en:france</td>\n      <td>France</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>unknown</td>\n      <td>unknown</td>\n      <td>en:to-be-completed, en:nutrition-facts-to-be-c...</td>\n      <td>en:to-be-completed,en:nutrition-facts-to-be-co...</td>\n      <td>A compléter,Informations nutritionnelles à com...</td>\n      <td>NaN</td>\n      <td>unknown</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n  </tbody>\n</table>\n<p>94271 rows × 146 columns</p>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"Data_fr[Data_fr['pnns_groups_2'].str.contains('nan')==False].head(2)","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:02.941315Z","iopub.execute_input":"2022-12-05T11:01:02.941783Z","iopub.status.idle":"2022-12-05T11:01:03.226398Z","shell.execute_reply.started":"2022-12-05T11:01:02.941737Z","shell.execute_reply":"2022-12-05T11:01:03.225055Z"},"trusted":true},"execution_count":1330,"outputs":[{"execution_count":1330,"output_type":"execute_result","data":{"text/plain":"     code                                                url  \\\n0    3087  http://world-fr.openfoodfacts.org/produit/0000...   \n46  24600  http://world-fr.openfoodfacts.org/produit/0000...   \n\n                       creator   created_t      created_datetime  \\\n0   openfoodfacts-contributors  1474103866  2016-09-17T09:17:46Z   \n46             date-limite-app  1434530704  2015-06-17T08:45:04Z   \n\n   last_modified_t last_modified_datetime        product_name generic_name  \\\n0       1474103893   2016-09-17T09:18:13Z  Farine de blé noir          NaN   \n46      1434535914   2015-06-17T10:11:54Z       Filet de bœuf          NaN   \n\n   quantity  packaging packaging_tags           brands      brands_tags  \\\n0       1kg        NaN            NaN  Ferme t'y R'nao  ferme-t-y-r-nao   \n46  2.46 kg  plastique      plastique              NaN              NaN   \n\n       categories    categories_tags   categories_fr origins origins_tags  \\\n0             NaN                NaN         unknown     NaN          NaN   \n46  Filet de bœuf  fr:filet-de-boeuf  Filet-de-boeuf     NaN          NaN   \n\n   manufacturing_places manufacturing_places_tags labels labels_tags  \\\n0                   NaN                       NaN    NaN         NaN   \n46                  NaN                       NaN    NaN         NaN   \n\n   labels_fr emb_codes emb_codes_tags first_packaging_code_geo cities  \\\n0        NaN       NaN            NaN                      NaN    NaN   \n46       NaN       NaN            NaN                      NaN    NaN   \n\n   cities_tags purchase_places stores countries countries_tags countries_fr  \\\n0          NaN             NaN    NaN     en:FR      en:france       France   \n46         NaN             NaN    NaN    France      en:france       France   \n\n   ingredients_text allergens allergens_fr traces traces_tags traces_fr  \\\n0               NaN       NaN          NaN    NaN         NaN       NaN   \n46              NaN       NaN          NaN    NaN         NaN       NaN   \n\n   serving_size  additives_n additives additives_tags additives_fr  \\\n0           NaN          NaN       NaN            NaN          NaN   \n46          NaN          NaN       NaN            NaN          NaN   \n\n    ingredients_from_palm_oil_n ingredients_from_palm_oil_tags  \\\n0                           NaN                            NaN   \n46                          NaN                            NaN   \n\n    ingredients_that_may_be_from_palm_oil_n  \\\n0                                       NaN   \n46                                      NaN   \n\n   ingredients_that_may_be_from_palm_oil_tags nutrition_grade_fr  \\\n0                                         NaN                NaN   \n46                                        NaN                NaN   \n\n   pnns_groups_1 pnns_groups_2  \\\n0        unknown       unknown   \n46       unknown       unknown   \n\n                                               states  \\\n0   en:to-be-completed, en:nutrition-facts-to-be-c...   \n46  en:to-be-completed, en:nutrition-facts-to-be-c...   \n\n                                          states_tags  \\\n0   en:to-be-completed,en:nutrition-facts-to-be-co...   \n46  en:to-be-completed,en:nutrition-facts-to-be-co...   \n\n                                            states_fr      main_category  \\\n0   A compléter,Informations nutritionnelles à com...                NaN   \n46  A compléter,Informations nutritionnelles à com...  fr:filet-de-boeuf   \n\n   main_category_fr                                          image_url  \\\n0           unknown                                                NaN   \n46   Filet-de-boeuf  http://fr.openfoodfacts.org/images/products/00...   \n\n                                      image_small_url  energy_100g  \\\n0                                                 NaN          NaN   \n46  http://fr.openfoodfacts.org/images/products/00...          NaN   \n\n    energy-from-fat_100g  fat_100g  saturated-fat_100g  caprylic-acid_100g  \\\n0                    NaN       NaN                 NaN                 NaN   \n46                   NaN       NaN                 NaN                 NaN   \n\n    capric-acid_100g  lauric-acid_100g  myristic-acid_100g  \\\n0                NaN               NaN                 NaN   \n46               NaN               NaN                 NaN   \n\n    palmitic-acid_100g  stearic-acid_100g  arachidic-acid_100g  \\\n0                  NaN                NaN                  NaN   \n46                 NaN                NaN                  NaN   \n\n    behenic-acid_100g  montanic-acid_100g  monounsaturated-fat_100g  \\\n0                 NaN                 NaN                       NaN   \n46                NaN                 NaN                       NaN   \n\n    polyunsaturated-fat_100g  omega-3-fat_100g  alpha-linolenic-acid_100g  \\\n0                        NaN               NaN                        NaN   \n46                       NaN               NaN                        NaN   \n\n    eicosapentaenoic-acid_100g  docosahexaenoic-acid_100g  omega-6-fat_100g  \\\n0                          NaN                        NaN               NaN   \n46                         NaN                        NaN               NaN   \n\n    linoleic-acid_100g  arachidonic-acid_100g  gamma-linolenic-acid_100g  \\\n0                  NaN                    NaN                        NaN   \n46                 NaN                    NaN                        NaN   \n\n    dihomo-gamma-linolenic-acid_100g  omega-9-fat_100g  oleic-acid_100g  \\\n0                                NaN               NaN              NaN   \n46                               NaN               NaN              NaN   \n\n    gondoic-acid_100g  trans-fat_100g  cholesterol_100g  carbohydrates_100g  \\\n0                 NaN             NaN               NaN                 NaN   \n46                NaN             NaN               NaN                 NaN   \n\n    sugars_100g  sucrose_100g  glucose_100g  fructose_100g  lactose_100g  \\\n0           NaN           NaN           NaN            NaN           NaN   \n46          NaN           NaN           NaN            NaN           NaN   \n\n    maltose_100g  maltodextrins_100g  starch_100g  polyols_100g  fiber_100g  \\\n0            NaN                 NaN          NaN           NaN         NaN   \n46           NaN                 NaN          NaN           NaN         NaN   \n\n    proteins_100g  casein_100g  serum-proteins_100g  nucleotides_100g  \\\n0             NaN          NaN                  NaN               NaN   \n46            NaN          NaN                  NaN               NaN   \n\n    salt_100g  sodium_100g  alcohol_100g  vitamin-a_100g  beta-carotene_100g  \\\n0         NaN          NaN           NaN             NaN                 NaN   \n46        NaN          NaN           NaN             NaN                 NaN   \n\n    vitamin-d_100g  vitamin-e_100g  vitamin-k_100g  vitamin-c_100g  \\\n0              NaN             NaN             NaN             NaN   \n46             NaN             NaN             NaN             NaN   \n\n    vitamin-b1_100g  vitamin-b2_100g  vitamin-pp_100g  vitamin-b6_100g  \\\n0               NaN              NaN              NaN              NaN   \n46              NaN              NaN              NaN              NaN   \n\n    vitamin-b9_100g  folates_100g  vitamin-b12_100g  biotin_100g  \\\n0               NaN           NaN               NaN          NaN   \n46              NaN           NaN               NaN          NaN   \n\n    pantothenic-acid_100g  silica_100g  bicarbonate_100g  potassium_100g  \\\n0                     NaN          NaN               NaN             NaN   \n46                    NaN          NaN               NaN             NaN   \n\n    chloride_100g  calcium_100g  phosphorus_100g  iron_100g  magnesium_100g  \\\n0             NaN           NaN              NaN        NaN             NaN   \n46            NaN           NaN              NaN        NaN             NaN   \n\n    zinc_100g  copper_100g  manganese_100g  fluoride_100g  selenium_100g  \\\n0         NaN          NaN             NaN            NaN            NaN   \n46        NaN          NaN             NaN            NaN            NaN   \n\n    chromium_100g  molybdenum_100g  iodine_100g  caffeine_100g  taurine_100g  \\\n0             NaN              NaN          NaN            NaN           NaN   \n46            NaN              NaN          NaN            NaN           NaN   \n\n    ph_100g  fruits-vegetables-nuts_100g  collagen-meat-protein-ratio_100g  \\\n0       NaN                          NaN                               NaN   \n46      NaN                          NaN                               NaN   \n\n    cocoa_100g  carbon-footprint_100g  nutrition-score-fr_100g  \\\n0          NaN                    NaN                      NaN   \n46         NaN                    NaN                      NaN   \n\n    nutrition-score-uk_100g  \n0                       NaN  \n46                      NaN  ","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>code</th>\n      <th>url</th>\n      <th>creator</th>\n      <th>created_t</th>\n      <th>created_datetime</th>\n      <th>last_modified_t</th>\n      <th>last_modified_datetime</th>\n      <th>product_name</th>\n      <th>generic_name</th>\n      <th>quantity</th>\n      <th>packaging</th>\n      <th>packaging_tags</th>\n      <th>brands</th>\n      <th>brands_tags</th>\n      <th>categories</th>\n      <th>categories_tags</th>\n      <th>categories_fr</th>\n      <th>origins</th>\n      <th>origins_tags</th>\n      <th>manufacturing_places</th>\n      <th>manufacturing_places_tags</th>\n      <th>labels</th>\n      <th>labels_tags</th>\n      <th>labels_fr</th>\n      <th>emb_codes</th>\n      <th>emb_codes_tags</th>\n      <th>first_packaging_code_geo</th>\n      <th>cities</th>\n      <th>cities_tags</th>\n      <th>purchase_places</th>\n      <th>stores</th>\n      <th>countries</th>\n      <th>countries_tags</th>\n      <th>countries_fr</th>\n      <th>ingredients_text</th>\n      <th>allergens</th>\n      <th>allergens_fr</th>\n      <th>traces</th>\n      <th>traces_tags</th>\n      <th>traces_fr</th>\n      <th>serving_size</th>\n      <th>additives_n</th>\n      <th>additives</th>\n      <th>additives_tags</th>\n      <th>additives_fr</th>\n      <th>ingredients_from_palm_oil_n</th>\n      <th>ingredients_from_palm_oil_tags</th>\n      <th>ingredients_that_may_be_from_palm_oil_n</th>\n      <th>ingredients_that_may_be_from_palm_oil_tags</th>\n      <th>nutrition_grade_fr</th>\n      <th>pnns_groups_1</th>\n      <th>pnns_groups_2</th>\n      <th>states</th>\n      <th>states_tags</th>\n      <th>states_fr</th>\n      <th>main_category</th>\n      <th>main_category_fr</th>\n      <th>image_url</th>\n      <th>image_small_url</th>\n      <th>energy_100g</th>\n      <th>energy-from-fat_100g</th>\n      <th>fat_100g</th>\n      <th>saturated-fat_100g</th>\n      <th>caprylic-acid_100g</th>\n      <th>capric-acid_100g</th>\n      <th>lauric-acid_100g</th>\n      <th>myristic-acid_100g</th>\n      <th>palmitic-acid_100g</th>\n      <th>stearic-acid_100g</th>\n      <th>arachidic-acid_100g</th>\n      <th>behenic-acid_100g</th>\n      <th>montanic-acid_100g</th>\n      <th>monounsaturated-fat_100g</th>\n      <th>polyunsaturated-fat_100g</th>\n      <th>omega-3-fat_100g</th>\n      <th>alpha-linolenic-acid_100g</th>\n      <th>eicosapentaenoic-acid_100g</th>\n      <th>docosahexaenoic-acid_100g</th>\n      <th>omega-6-fat_100g</th>\n      <th>linoleic-acid_100g</th>\n      <th>arachidonic-acid_100g</th>\n      <th>gamma-linolenic-acid_100g</th>\n      <th>dihomo-gamma-linolenic-acid_100g</th>\n      <th>omega-9-fat_100g</th>\n      <th>oleic-acid_100g</th>\n      <th>gondoic-acid_100g</th>\n      <th>trans-fat_100g</th>\n      <th>cholesterol_100g</th>\n      <th>carbohydrates_100g</th>\n      <th>sugars_100g</th>\n      <th>sucrose_100g</th>\n      <th>glucose_100g</th>\n      <th>fructose_100g</th>\n      <th>lactose_100g</th>\n      <th>maltose_100g</th>\n      <th>maltodextrins_100g</th>\n      <th>starch_100g</th>\n      <th>polyols_100g</th>\n      <th>fiber_100g</th>\n      <th>proteins_100g</th>\n      <th>casein_100g</th>\n      <th>serum-proteins_100g</th>\n      <th>nucleotides_100g</th>\n      <th>salt_100g</th>\n      <th>sodium_100g</th>\n      <th>alcohol_100g</th>\n      <th>vitamin-a_100g</th>\n      <th>beta-carotene_100g</th>\n      <th>vitamin-d_100g</th>\n      <th>vitamin-e_100g</th>\n      <th>vitamin-k_100g</th>\n      <th>vitamin-c_100g</th>\n      <th>vitamin-b1_100g</th>\n      <th>vitamin-b2_100g</th>\n      <th>vitamin-pp_100g</th>\n      <th>vitamin-b6_100g</th>\n      <th>vitamin-b9_100g</th>\n      <th>folates_100g</th>\n      <th>vitamin-b12_100g</th>\n      <th>biotin_100g</th>\n      <th>pantothenic-acid_100g</th>\n      <th>silica_100g</th>\n      <th>bicarbonate_100g</th>\n      <th>potassium_100g</th>\n      <th>chloride_100g</th>\n      <th>calcium_100g</th>\n      <th>phosphorus_100g</th>\n      <th>iron_100g</th>\n      <th>magnesium_100g</th>\n      <th>zinc_100g</th>\n      <th>copper_100g</th>\n      <th>manganese_100g</th>\n      <th>fluoride_100g</th>\n      <th>selenium_100g</th>\n      <th>chromium_100g</th>\n      <th>molybdenum_100g</th>\n      <th>iodine_100g</th>\n      <th>caffeine_100g</th>\n      <th>taurine_100g</th>\n      <th>ph_100g</th>\n      <th>fruits-vegetables-nuts_100g</th>\n      <th>collagen-meat-protein-ratio_100g</th>\n      <th>cocoa_100g</th>\n      <th>carbon-footprint_100g</th>\n      <th>nutrition-score-fr_100g</th>\n      <th>nutrition-score-uk_100g</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>3087</td>\n      <td>http://world-fr.openfoodfacts.org/produit/0000...</td>\n      <td>openfoodfacts-contributors</td>\n      <td>1474103866</td>\n      <td>2016-09-17T09:17:46Z</td>\n      <td>1474103893</td>\n      <td>2016-09-17T09:18:13Z</td>\n      <td>Farine de blé noir</td>\n      <td>NaN</td>\n      <td>1kg</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Ferme t'y R'nao</td>\n      <td>ferme-t-y-r-nao</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>unknown</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>en:FR</td>\n      <td>en:france</td>\n      <td>France</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>unknown</td>\n      <td>unknown</td>\n      <td>en:to-be-completed, en:nutrition-facts-to-be-c...</td>\n      <td>en:to-be-completed,en:nutrition-facts-to-be-co...</td>\n      <td>A compléter,Informations nutritionnelles à com...</td>\n      <td>NaN</td>\n      <td>unknown</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>46</th>\n      <td>24600</td>\n      <td>http://world-fr.openfoodfacts.org/produit/0000...</td>\n      <td>date-limite-app</td>\n      <td>1434530704</td>\n      <td>2015-06-17T08:45:04Z</td>\n      <td>1434535914</td>\n      <td>2015-06-17T10:11:54Z</td>\n      <td>Filet de bœuf</td>\n      <td>NaN</td>\n      <td>2.46 kg</td>\n      <td>plastique</td>\n      <td>plastique</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Filet de bœuf</td>\n      <td>fr:filet-de-boeuf</td>\n      <td>Filet-de-boeuf</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>France</td>\n      <td>en:france</td>\n      <td>France</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>unknown</td>\n      <td>unknown</td>\n      <td>en:to-be-completed, en:nutrition-facts-to-be-c...</td>\n      <td>en:to-be-completed,en:nutrition-facts-to-be-co...</td>\n      <td>A compléter,Informations nutritionnelles à com...</td>\n      <td>fr:filet-de-boeuf</td>\n      <td>Filet-de-boeuf</td>\n      <td>http://fr.openfoodfacts.org/images/products/00...</td>\n      <td>http://fr.openfoodfacts.org/images/products/00...</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"Data_fr = Data_fr[~((Data_fr['product_name'].isnull()) \n                        & ((Data_fr.pnns_groups_1 == \"unknown\") \n                           | (Data_fr.main_category_fr == \"unknown\")))]","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:03.228046Z","iopub.execute_input":"2022-12-05T11:01:03.228417Z","iopub.status.idle":"2022-12-05T11:01:03.390137Z","shell.execute_reply.started":"2022-12-05T11:01:03.228378Z","shell.execute_reply":"2022-12-05T11:01:03.388814Z"},"trusted":true},"execution_count":1331,"outputs":[]},{"cell_type":"code","source":"# supprimer les lignes qui contiennent \"unknown\" pnns_groups_1\n# Data_fr[((Data_fr.pnns_groups_1.isin([\"unknown\"]) & (Data_fr.main_category_fr == \"unknown\") &\n#               (Data_fr.pnns_groups_2 == \"unknown\") & (Data_fr.main_category_fr == \"unknown\"))].shape[0]\n         \n         \nData_fr[((Data_fr.pnns_groups_1 == \"unknown\") & (Data_fr.main_category_fr == \"unknown\") &\n  (Data_fr.pnns_groups_2 == \"unknown\") & (Data_fr.main_category_fr == \"unknown\"))].shape[0]","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:03.391707Z","iopub.execute_input":"2022-12-05T11:01:03.392078Z","iopub.status.idle":"2022-12-05T11:01:03.481074Z","shell.execute_reply.started":"2022-12-05T11:01:03.392045Z","shell.execute_reply":"2022-12-05T11:01:03.479937Z"},"trusted":true},"execution_count":1332,"outputs":[{"execution_count":1332,"output_type":"execute_result","data":{"text/plain":"29079"},"metadata":{}}]},{"cell_type":"code","source":"# supprimer les lignes qui contiennent \"unknown\" en pnns_groups_2\n# supprimer les lignes qui contiennent \"unknown\" pnns_groups_1\nData_fr = Data_fr[~Data_fr.pnns_groups_1.isin([\"unknown\"])]\nData_fr = Data_fr[~Data_fr.pnns_groups_2.isin([\"unknown\"])]","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:03.482696Z","iopub.execute_input":"2022-12-05T11:01:03.483037Z","iopub.status.idle":"2022-12-05T11:01:03.703557Z","shell.execute_reply.started":"2022-12-05T11:01:03.482999Z","shell.execute_reply":"2022-12-05T11:01:03.702324Z"},"trusted":true},"execution_count":1333,"outputs":[]},{"cell_type":"code","source":"# Data_fr = Data_fr[~Data_fr.pnns_groups_1.isin([\"nan\"])]\n# Data_fr = Data_fr[~Data_fr.pnns_groups_2.isin([\"nan\"])]","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:03.704998Z","iopub.execute_input":"2022-12-05T11:01:03.705330Z","iopub.status.idle":"2022-12-05T11:01:03.709843Z","shell.execute_reply.started":"2022-12-05T11:01:03.705299Z","shell.execute_reply":"2022-12-05T11:01:03.708501Z"},"trusted":true},"execution_count":1334,"outputs":[]},{"cell_type":"code","source":"# correct feature names\nData_fr[\"pnns_groups_1\"] = Data_fr[\"pnns_groups_1\"].str.lower().str.replace('-', ' ')\nData_fr['pnns_groups_1'].unique()","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:03.711461Z","iopub.execute_input":"2022-12-05T11:01:03.711925Z","iopub.status.idle":"2022-12-05T11:01:03.775042Z","shell.execute_reply.started":"2022-12-05T11:01:03.711882Z","shell.execute_reply":"2022-12-05T11:01:03.773654Z"},"trusted":true},"execution_count":1335,"outputs":[{"execution_count":1335,"output_type":"execute_result","data":{"text/plain":"array(['cereals and potatoes', 'sugary snacks', 'beverages',\n       'fish meat eggs', 'fruits and vegetables', 'composite foods',\n       'salty snacks', 'fat and sauces', 'milk and dairy products'],\n      dtype=object)"},"metadata":{}}]},{"cell_type":"code","source":"for i in Data_fr['pnns_groups_2'].unique():\n    print (i)","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:03.776766Z","iopub.execute_input":"2022-12-05T11:01:03.777127Z","iopub.status.idle":"2022-12-05T11:01:03.787207Z","shell.execute_reply.started":"2022-12-05T11:01:03.777088Z","shell.execute_reply":"2022-12-05T11:01:03.785859Z"},"trusted":true},"execution_count":1336,"outputs":[{"name":"stdout","text":"Legumes\nBiscuits and cakes\nSweets\nNon-sugared beverages\nSweetened beverages\nMeat\nSoups\nSandwich\nAppetizers\nDressings and sauces\nChocolate products\nDried fruits\nNuts\nOne-dish meals\nCheese\nFruits\nFats\nPizza pies and quiche\nVegetables\nBreakfast cereals\nCereals\nFruit juices\nvegetables\nIce cream\nMilk and yogurt\nBread\nFish and seafood\npastries\nProcessed meat\nDairy desserts\nArtificially sweetened beverages\nFruit nectars\nPotatoes\nEggs\nSalty and fatty products\nfruits\nlegumes\ncereals\n","output_type":"stream"}]},{"cell_type":"markdown","source":"On voit ici que certaines catégories sont présentes plusieurs fois mais orthographiées différement :\n\n- 'fruits-and-vegetables' et 'Fruits and vegetables'\n- 'vegetables' et 'Vegetables'\n\n\nNous allons donc corriger le problème:","metadata":{}},{"cell_type":"code","source":"# correct feature names\nData_fr[\"pnns_groups_2\"] = Data_fr[\"pnns_groups_2\"].str.replace('vegetables', 'Vegetables')\nData_fr['pnns_groups_2'].unique()","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:03.789054Z","iopub.execute_input":"2022-12-05T11:01:03.789670Z","iopub.status.idle":"2022-12-05T11:01:03.838262Z","shell.execute_reply.started":"2022-12-05T11:01:03.789622Z","shell.execute_reply":"2022-12-05T11:01:03.837269Z"},"trusted":true},"execution_count":1337,"outputs":[{"execution_count":1337,"output_type":"execute_result","data":{"text/plain":"array(['Legumes', 'Biscuits and cakes', 'Sweets', 'Non-sugared beverages',\n       'Sweetened beverages', 'Meat', 'Soups', 'Sandwich', 'Appetizers',\n       'Dressings and sauces', 'Chocolate products', 'Dried fruits',\n       'Nuts', 'One-dish meals', 'Cheese', 'Fruits', 'Fats',\n       'Pizza pies and quiche', 'Vegetables', 'Breakfast cereals',\n       'Cereals', 'Fruit juices', 'Ice cream', 'Milk and yogurt', 'Bread',\n       'Fish and seafood', 'pastries', 'Processed meat', 'Dairy desserts',\n       'Artificially sweetened beverages', 'Fruit nectars', 'Potatoes',\n       'Eggs', 'Salty and fatty products', 'fruits', 'legumes', 'cereals'],\n      dtype=object)"},"metadata":{}}]},{"cell_type":"code","source":"Data_fr.isna().mean()","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:03.839600Z","iopub.execute_input":"2022-12-05T11:01:03.840009Z","iopub.status.idle":"2022-12-05T11:01:04.019795Z","shell.execute_reply.started":"2022-12-05T11:01:03.839977Z","shell.execute_reply":"2022-12-05T11:01:04.018619Z"},"trusted":true},"execution_count":1338,"outputs":[{"execution_count":1338,"output_type":"execute_result","data":{"text/plain":"code                                0.000000\nurl                                 0.000000\ncreator                             0.000000\ncreated_t                           0.000000\ncreated_datetime                    0.000000\n                                      ...   \ncollagen-meat-protein-ratio_100g    0.996740\ncocoa_100g                          0.988449\ncarbon-footprint_100g               0.996841\nnutrition-score-fr_100g             0.239913\nnutrition-score-uk_100g             0.239913\nLength: 146, dtype: float64"},"metadata":{}}]},{"cell_type":"code","source":"#Combien des valeur manquants dans notre df\nData_fr.isnull().sum() / len(Data)*100","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:04.021527Z","iopub.execute_input":"2022-12-05T11:01:04.022272Z","iopub.status.idle":"2022-12-05T11:01:04.202934Z","shell.execute_reply.started":"2022-12-05T11:01:04.022214Z","shell.execute_reply":"2022-12-05T11:01:04.201648Z"},"trusted":true},"execution_count":1339,"outputs":[{"execution_count":1339,"output_type":"execute_result","data":{"text/plain":"code                                 0.000000\nurl                                  0.000000\ncreator                              0.000000\ncreated_t                            0.000000\ncreated_datetime                     0.000000\n                                      ...    \ncollagen-meat-protein-ratio_100g    15.441186\ncocoa_100g                          15.312746\ncarbon-footprint_100g               15.442744\nnutrition-score-fr_100g              3.716659\nnutrition-score-uk_100g              3.716659\nLength: 146, dtype: float64"},"metadata":{}}]},{"cell_type":"code","source":"Data_fr.shape","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:04.205476Z","iopub.execute_input":"2022-12-05T11:01:04.205873Z","iopub.status.idle":"2022-12-05T11:01:04.213301Z","shell.execute_reply.started":"2022-12-05T11:01:04.205841Z","shell.execute_reply":"2022-12-05T11:01:04.211925Z"},"trusted":true},"execution_count":1340,"outputs":[{"execution_count":1340,"output_type":"execute_result","data":{"text/plain":"(49693, 146)"},"metadata":{}}]},{"cell_type":"code","source":"def get_feature_wrt_tr(tr):\n    \"\"\"\n    Function that selects features which has \n    fullness rate greater than threshold\n\n    Parameters:\n    ----------\n    tr: float, fullness rate threshold\n\n    Return:\n    ------\n    selected_features: pd.Series, selected features pandas series \n    \"\"\"\n    null_values = Data_fr.isna().mean()\n    selected_features = null_values[null_values <= tr]\n    return selected_features","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:04.215017Z","iopub.execute_input":"2022-12-05T11:01:04.216126Z","iopub.status.idle":"2022-12-05T11:01:04.223090Z","shell.execute_reply.started":"2022-12-05T11:01:04.216086Z","shell.execute_reply":"2022-12-05T11:01:04.221822Z"},"trusted":true},"execution_count":1341,"outputs":[]},{"cell_type":"code","source":"get_feature_wrt_tr(0.2)","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:04.224658Z","iopub.execute_input":"2022-12-05T11:01:04.225054Z","iopub.status.idle":"2022-12-05T11:01:04.413258Z","shell.execute_reply.started":"2022-12-05T11:01:04.225019Z","shell.execute_reply":"2022-12-05T11:01:04.411849Z"},"trusted":true},"execution_count":1342,"outputs":[{"execution_count":1342,"output_type":"execute_result","data":{"text/plain":"code                                       0.000000\nurl                                        0.000000\ncreator                                    0.000000\ncreated_t                                  0.000000\ncreated_datetime                           0.000000\nlast_modified_t                            0.000000\nlast_modified_datetime                     0.000000\nproduct_name                               0.004508\nquantity                                   0.051255\npackaging                                  0.089147\npackaging_tags                             0.089127\nbrands                                     0.009217\nbrands_tags                                0.009237\ncategories                                 0.000000\ncategories_tags                            0.000000\ncategories_fr                              0.000000\ncountries                                  0.000000\ncountries_tags                             0.000000\ncountries_fr                               0.000000\ningredients_text                           0.152597\nadditives_n                                0.152597\nadditives                                  0.152738\ningredients_from_palm_oil_n                0.152597\ningredients_that_may_be_from_palm_oil_n    0.152597\npnns_groups_1                              0.000000\npnns_groups_2                              0.000000\nstates                                     0.000000\nstates_tags                                0.000000\nstates_fr                                  0.000000\nmain_category                              0.000000\nmain_category_fr                           0.000000\nenergy_100g                                0.192965\nproteins_100g                              0.196949\ndtype: float64"},"metadata":{}}]},{"cell_type":"code","source":"Data_fr=Data_fr.drop(['url', 'creator', 'created_t', 'created_datetime', 'last_modified_t', 'last_modified_datetime', 'brands', 'brands_tags', 'categories_tags','countries', 'countries_fr', 'states', 'states_tags', 'states_fr'], axis=1)","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:04.414793Z","iopub.execute_input":"2022-12-05T11:01:04.415155Z","iopub.status.idle":"2022-12-05T11:01:04.483580Z","shell.execute_reply.started":"2022-12-05T11:01:04.415123Z","shell.execute_reply":"2022-12-05T11:01:04.482287Z"},"trusted":true},"execution_count":1343,"outputs":[]},{"cell_type":"code","source":"# Data_fr=Data_fr.drop(['url', 'code', 'creator', 'created_t', 'created_datetime', 'last_modified_t', 'last_modified_datetime', 'brands', 'brands_tags', 'categories_tags','countries', 'countries_fr', 'states', 'states_tags', 'states_fr'], axis=1)","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:04.492342Z","iopub.execute_input":"2022-12-05T11:01:04.492776Z","iopub.status.idle":"2022-12-05T11:01:04.497699Z","shell.execute_reply.started":"2022-12-05T11:01:04.492724Z","shell.execute_reply":"2022-12-05T11:01:04.496406Z"},"trusted":true},"execution_count":1344,"outputs":[]},{"cell_type":"code","source":"get_feature_wrt_tr(0.4)","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:04.499373Z","iopub.execute_input":"2022-12-05T11:01:04.499968Z","iopub.status.idle":"2022-12-05T11:01:04.644208Z","shell.execute_reply.started":"2022-12-05T11:01:04.499924Z","shell.execute_reply":"2022-12-05T11:01:04.642888Z"},"trusted":true},"execution_count":1345,"outputs":[{"execution_count":1345,"output_type":"execute_result","data":{"text/plain":"code                                       0.000000\nproduct_name                               0.004508\ngeneric_name                               0.378504\nquantity                                   0.051255\npackaging                                  0.089147\npackaging_tags                             0.089127\ncategories                                 0.000000\ncategories_fr                              0.000000\npurchase_places                            0.298191\nstores                                     0.379671\ncountries_tags                             0.000000\ningredients_text                           0.152597\nadditives_n                                0.152597\nadditives                                  0.152738\ningredients_from_palm_oil_n                0.152597\ningredients_that_may_be_from_palm_oil_n    0.152597\nnutrition_grade_fr                         0.239913\npnns_groups_1                              0.000000\npnns_groups_2                              0.000000\nmain_category                              0.000000\nmain_category_fr                           0.000000\nimage_url                                  0.263598\nimage_small_url                            0.263598\nenergy_100g                                0.192965\nfat_100g                                   0.236271\nsaturated-fat_100g                         0.226873\ncarbohydrates_100g                         0.244119\nsugars_100g                                0.225545\nproteins_100g                              0.196949\nsalt_100g                                  0.224659\nsodium_100g                                0.224700\nnutrition-score-fr_100g                    0.239913\nnutrition-score-uk_100g                    0.239913\ndtype: float64"},"metadata":{}}]},{"cell_type":"code","source":"Data_fr=Data_fr.drop(['categories', 'countries_tags', 'main_category'], axis=1)","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:04.645760Z","iopub.execute_input":"2022-12-05T11:01:04.646184Z","iopub.status.idle":"2022-12-05T11:01:04.707406Z","shell.execute_reply.started":"2022-12-05T11:01:04.646148Z","shell.execute_reply":"2022-12-05T11:01:04.706071Z"},"trusted":true},"execution_count":1346,"outputs":[]},{"cell_type":"code","source":"get_feature_wrt_tr(0.45)","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:04.709872Z","iopub.execute_input":"2022-12-05T11:01:04.710334Z","iopub.status.idle":"2022-12-05T11:01:04.839967Z","shell.execute_reply.started":"2022-12-05T11:01:04.710282Z","shell.execute_reply":"2022-12-05T11:01:04.838615Z"},"trusted":true},"execution_count":1347,"outputs":[{"execution_count":1347,"output_type":"execute_result","data":{"text/plain":"code                                       0.000000\nproduct_name                               0.004508\ngeneric_name                               0.378504\nquantity                                   0.051255\npackaging                                  0.089147\npackaging_tags                             0.089127\ncategories_fr                              0.000000\npurchase_places                            0.298191\nstores                                     0.379671\ningredients_text                           0.152597\nadditives_n                                0.152597\nadditives                                  0.152738\ningredients_from_palm_oil_n                0.152597\ningredients_that_may_be_from_palm_oil_n    0.152597\nnutrition_grade_fr                         0.239913\npnns_groups_1                              0.000000\npnns_groups_2                              0.000000\nmain_category_fr                           0.000000\nimage_url                                  0.263598\nimage_small_url                            0.263598\nenergy_100g                                0.192965\nfat_100g                                   0.236271\nsaturated-fat_100g                         0.226873\ncarbohydrates_100g                         0.244119\nsugars_100g                                0.225545\nproteins_100g                              0.196949\nsalt_100g                                  0.224659\nsodium_100g                                0.224700\nnutrition-score-fr_100g                    0.239913\nnutrition-score-uk_100g                    0.239913\ndtype: float64"},"metadata":{}}]},{"cell_type":"code","source":"Data_fr=Data_fr.drop(['packaging'], axis=1)","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:04.841163Z","iopub.execute_input":"2022-12-05T11:01:04.841504Z","iopub.status.idle":"2022-12-05T11:01:04.898589Z","shell.execute_reply.started":"2022-12-05T11:01:04.841473Z","shell.execute_reply":"2022-12-05T11:01:04.897398Z"},"trusted":true},"execution_count":1348,"outputs":[]},{"cell_type":"code","source":"get_feature_wrt_tr(0.45)","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:04.899810Z","iopub.execute_input":"2022-12-05T11:01:04.900106Z","iopub.status.idle":"2022-12-05T11:01:05.025375Z","shell.execute_reply.started":"2022-12-05T11:01:04.900079Z","shell.execute_reply":"2022-12-05T11:01:05.024139Z"},"trusted":true},"execution_count":1349,"outputs":[{"execution_count":1349,"output_type":"execute_result","data":{"text/plain":"code                                       0.000000\nproduct_name                               0.004508\ngeneric_name                               0.378504\nquantity                                   0.051255\npackaging_tags                             0.089127\ncategories_fr                              0.000000\npurchase_places                            0.298191\nstores                                     0.379671\ningredients_text                           0.152597\nadditives_n                                0.152597\nadditives                                  0.152738\ningredients_from_palm_oil_n                0.152597\ningredients_that_may_be_from_palm_oil_n    0.152597\nnutrition_grade_fr                         0.239913\npnns_groups_1                              0.000000\npnns_groups_2                              0.000000\nmain_category_fr                           0.000000\nimage_url                                  0.263598\nimage_small_url                            0.263598\nenergy_100g                                0.192965\nfat_100g                                   0.236271\nsaturated-fat_100g                         0.226873\ncarbohydrates_100g                         0.244119\nsugars_100g                                0.225545\nproteins_100g                              0.196949\nsalt_100g                                  0.224659\nsodium_100g                                0.224700\nnutrition-score-fr_100g                    0.239913\nnutrition-score-uk_100g                    0.239913\ndtype: float64"},"metadata":{}}]},{"cell_type":"code","source":"Data_fr=Data_fr.drop(['nutrition-score-uk_100g'], axis=1)","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:05.026882Z","iopub.execute_input":"2022-12-05T11:01:05.027216Z","iopub.status.idle":"2022-12-05T11:01:05.084373Z","shell.execute_reply.started":"2022-12-05T11:01:05.027186Z","shell.execute_reply":"2022-12-05T11:01:05.083242Z"},"trusted":true},"execution_count":1350,"outputs":[]},{"cell_type":"code","source":"Data_fr.info()","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:05.085715Z","iopub.execute_input":"2022-12-05T11:01:05.086041Z","iopub.status.idle":"2022-12-05T11:01:05.103421Z","shell.execute_reply.started":"2022-12-05T11:01:05.086013Z","shell.execute_reply":"2022-12-05T11:01:05.101889Z"},"trusted":true},"execution_count":1351,"outputs":[{"name":"stdout","text":"<class 'pandas.core.frame.DataFrame'>\nInt64Index: 49693 entries, 182 to 320765\nColumns: 127 entries, code to nutrition-score-fr_100g\ndtypes: float64(89), object(38)\nmemory usage: 48.5+ MB\n","output_type":"stream"}]},{"cell_type":"code","source":"Data_fr = Data_fr[['carbohydrates_100g', 'fiber_100g', 'fruits-vegetables-nuts_100g','product_name','quantity','packaging_tags','categories_fr','nutrition_grade_fr','pnns_groups_1','pnns_groups_2','main_category_fr','energy_100g', 'saturated-fat_100g', 'sugars_100g', 'proteins_100g', 'salt_100g','sodium_100g', 'nutrition-score-fr_100g']]","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:05.104892Z","iopub.execute_input":"2022-12-05T11:01:05.105280Z","iopub.status.idle":"2022-12-05T11:01:05.136854Z","shell.execute_reply.started":"2022-12-05T11:01:05.105247Z","shell.execute_reply":"2022-12-05T11:01:05.135508Z"},"trusted":true},"execution_count":1352,"outputs":[]},{"cell_type":"code","source":"Data_fr.shape","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:05.138654Z","iopub.execute_input":"2022-12-05T11:01:05.139858Z","iopub.status.idle":"2022-12-05T11:01:05.152735Z","shell.execute_reply.started":"2022-12-05T11:01:05.139806Z","shell.execute_reply":"2022-12-05T11:01:05.151297Z"},"trusted":true},"execution_count":1353,"outputs":[{"execution_count":1353,"output_type":"execute_result","data":{"text/plain":"(49693, 18)"},"metadata":{}}]},{"cell_type":"code","source":"Data_fr","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:05.155675Z","iopub.execute_input":"2022-12-05T11:01:05.156071Z","iopub.status.idle":"2022-12-05T11:01:05.191919Z","shell.execute_reply.started":"2022-12-05T11:01:05.156037Z","shell.execute_reply":"2022-12-05T11:01:05.190857Z"},"trusted":true},"execution_count":1354,"outputs":[{"execution_count":1354,"output_type":"execute_result","data":{"text/plain":"        carbohydrates_100g  fiber_100g  fruits-vegetables-nuts_100g  \\\n182                    NaN         NaN                          NaN   \n184                    NaN         NaN                          NaN   \n187                    NaN         NaN                          NaN   \n188                    NaN         NaN                          NaN   \n226                   10.4         0.0                          NaN   \n...                    ...         ...                          ...   \n320751                74.8         5.9                          NaN   \n320755                 NaN         NaN                          NaN   \n320758                 NaN         NaN                          NaN   \n320763                 0.5         0.2                          NaN   \n320765                 NaN         NaN                          NaN   \n\n                                 product_name quantity  \\\n182                         lentilles vertes     1 kg    \n184         Biscuits sablés fourrage au cacao     1 kg   \n187                                       NaN   46,7 g   \n188     Thé de Noël aromatisé orange-cannelle     75 g   \n226                     Pepsi, Nouveau goût !    15 cl   \n...                                       ...      ...   \n320751    Tartines craquantes bio au sarrasin      NaN   \n320755                                    NaN      NaN   \n320758                       Miel de Camargue    250 g   \n320763                     Thé vert Earl grey     50 g   \n320765                         Rillette d'oie    180 g   \n\n                       packaging_tags  \\\n182                  sachet-plastique   \n184                      carton,boite   \n187                            carton   \n188                         aluminium   \n226                 canette-aluminium   \n...                               ...   \n320751  boite,carton,sachet,plastique   \n320755                            NaN   \n320758                    bocal,verre   \n320763                   boite,carton   \n320765                      pot,verre   \n\n                                            categories_fr nutrition_grade_fr  \\\n182     Aliments et boissons à base de végétaux,Alimen...                NaN   \n184     Snacks sucrés,Biscuits et gâteaux,Biscuits,Sablés                NaN   \n187                     Snacks sucrés,Confiseries,Bonbons                NaN   \n188     Aliments et boissons à base de végétaux,Boisso...                NaN   \n226     Boissons,Boissons gazeuses,Sodas,Sodas au cola...                  e   \n...                                                   ...                ...   \n320751  Aliments et boissons à base de végétaux,Alimen...                  a   \n320755  Produits à tartiner,Petit-déjeuners,Produits à...                NaN   \n320758  Produits à tartiner,Petit-déjeuners,Produits à...                NaN   \n320763  Aliments et boissons à base de végétaux,Boisso...                  c   \n320765  Viandes,Produits à tartiner,Charcuteries,Produ...                NaN   \n\n               pnns_groups_1          pnns_groups_2  \\\n182     cereals and potatoes                Legumes   \n184            sugary snacks     Biscuits and cakes   \n187            sugary snacks                 Sweets   \n188                beverages  Non-sugared beverages   \n226                beverages    Sweetened beverages   \n...                      ...                    ...   \n320751  cereals and potatoes                  Bread   \n320755         sugary snacks                 Sweets   \n320758         sugary snacks                 Sweets   \n320763             beverages  Non-sugared beverages   \n320765        fish meat eggs         Processed meat   \n\n                               main_category_fr  energy_100g  \\\n182     Aliments et boissons à base de végétaux          NaN   \n184                                      Sablés          NaN   \n187                                     Bonbons          NaN   \n188                                        Thés          NaN   \n226                                       Sodas        177.0   \n...                                         ...          ...   \n320751                                    Pains       1643.0   \n320755                         Pâtes à tartiner          NaN   \n320758                      Produits d'élevages          NaN   \n320763                               Thés verts         21.0   \n320765                Produits à tartiner salés          NaN   \n\n        saturated-fat_100g  sugars_100g  proteins_100g  salt_100g  \\\n182                    NaN          NaN            NaN        NaN   \n184                    NaN          NaN            NaN        NaN   \n187                    NaN          NaN            NaN        NaN   \n188                    NaN          NaN            NaN        NaN   \n226                    0.0         10.4            0.0     0.0254   \n...                    ...          ...            ...        ...   \n320751                 0.6          2.6           13.0     0.6800   \n320755                 NaN          NaN            NaN        NaN   \n320758                 NaN          NaN            NaN        NaN   \n320763                 0.2          0.5            0.5     0.0254   \n320765                 NaN          NaN            NaN        NaN   \n\n        sodium_100g  nutrition-score-fr_100g  \n182             NaN                      NaN  \n184             NaN                      NaN  \n187             NaN                      NaN  \n188             NaN                      NaN  \n226        0.010000                     13.0  \n...             ...                      ...  \n320751     0.267717                     -4.0  \n320755          NaN                      NaN  \n320758          NaN                      NaN  \n320763     0.010000                      2.0  \n320765          NaN                      NaN  \n\n[49693 rows x 18 columns]","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>carbohydrates_100g</th>\n      <th>fiber_100g</th>\n      <th>fruits-vegetables-nuts_100g</th>\n      <th>product_name</th>\n      <th>quantity</th>\n      <th>packaging_tags</th>\n      <th>categories_fr</th>\n      <th>nutrition_grade_fr</th>\n      <th>pnns_groups_1</th>\n      <th>pnns_groups_2</th>\n      <th>main_category_fr</th>\n      <th>energy_100g</th>\n      <th>saturated-fat_100g</th>\n      <th>sugars_100g</th>\n      <th>proteins_100g</th>\n      <th>salt_100g</th>\n      <th>sodium_100g</th>\n      <th>nutrition-score-fr_100g</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>182</th>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>lentilles vertes</td>\n      <td>1 kg</td>\n      <td>sachet-plastique</td>\n      <td>Aliments et boissons à base de végétaux,Alimen...</td>\n      <td>NaN</td>\n      <td>cereals and potatoes</td>\n      <td>Legumes</td>\n      <td>Aliments et boissons à base de végétaux</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>184</th>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Biscuits sablés fourrage au cacao</td>\n      <td>1 kg</td>\n      <td>carton,boite</td>\n      <td>Snacks sucrés,Biscuits et gâteaux,Biscuits,Sablés</td>\n      <td>NaN</td>\n      <td>sugary snacks</td>\n      <td>Biscuits and cakes</td>\n      <td>Sablés</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>187</th>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>46,7 g</td>\n      <td>carton</td>\n      <td>Snacks sucrés,Confiseries,Bonbons</td>\n      <td>NaN</td>\n      <td>sugary snacks</td>\n      <td>Sweets</td>\n      <td>Bonbons</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>188</th>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Thé de Noël aromatisé orange-cannelle</td>\n      <td>75 g</td>\n      <td>aluminium</td>\n      <td>Aliments et boissons à base de végétaux,Boisso...</td>\n      <td>NaN</td>\n      <td>beverages</td>\n      <td>Non-sugared beverages</td>\n      <td>Thés</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>226</th>\n      <td>10.4</td>\n      <td>0.0</td>\n      <td>NaN</td>\n      <td>Pepsi, Nouveau goût !</td>\n      <td>15 cl</td>\n      <td>canette-aluminium</td>\n      <td>Boissons,Boissons gazeuses,Sodas,Sodas au cola...</td>\n      <td>e</td>\n      <td>beverages</td>\n      <td>Sweetened beverages</td>\n      <td>Sodas</td>\n      <td>177.0</td>\n      <td>0.0</td>\n      <td>10.4</td>\n      <td>0.0</td>\n      <td>0.0254</td>\n      <td>0.010000</td>\n      <td>13.0</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    </tr>\n    <tr>\n      <th>320751</th>\n      <td>74.8</td>\n      <td>5.9</td>\n      <td>NaN</td>\n      <td>Tartines craquantes bio au sarrasin</td>\n      <td>NaN</td>\n      <td>boite,carton,sachet,plastique</td>\n      <td>Aliments et boissons à base de végétaux,Alimen...</td>\n      <td>a</td>\n      <td>cereals and potatoes</td>\n      <td>Bread</td>\n      <td>Pains</td>\n      <td>1643.0</td>\n      <td>0.6</td>\n      <td>2.6</td>\n      <td>13.0</td>\n      <td>0.6800</td>\n      <td>0.267717</td>\n      <td>-4.0</td>\n    </tr>\n    <tr>\n      <th>320755</th>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Produits à tartiner,Petit-déjeuners,Produits à...</td>\n      <td>NaN</td>\n      <td>sugary snacks</td>\n      <td>Sweets</td>\n      <td>Pâtes à tartiner</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>320758</th>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Miel de Camargue</td>\n      <td>250 g</td>\n      <td>bocal,verre</td>\n      <td>Produits à tartiner,Petit-déjeuners,Produits à...</td>\n      <td>NaN</td>\n      <td>sugary snacks</td>\n      <td>Sweets</td>\n      <td>Produits d'élevages</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>320763</th>\n      <td>0.5</td>\n      <td>0.2</td>\n      <td>NaN</td>\n      <td>Thé vert Earl grey</td>\n      <td>50 g</td>\n      <td>boite,carton</td>\n      <td>Aliments et boissons à base de végétaux,Boisso...</td>\n      <td>c</td>\n      <td>beverages</td>\n      <td>Non-sugared beverages</td>\n      <td>Thés verts</td>\n      <td>21.0</td>\n      <td>0.2</td>\n      <td>0.5</td>\n      <td>0.5</td>\n      <td>0.0254</td>\n      <td>0.010000</td>\n      <td>2.0</td>\n    </tr>\n    <tr>\n      <th>320765</th>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>Rillette d'oie</td>\n      <td>180 g</td>\n      <td>pot,verre</td>\n      <td>Viandes,Produits à tartiner,Charcuteries,Produ...</td>\n      <td>NaN</td>\n      <td>fish meat eggs</td>\n      <td>Processed meat</td>\n      <td>Produits à tartiner salés</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n  </tbody>\n</table>\n<p>49693 rows × 18 columns</p>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"import missingno as msno\n\nmsno.bar(Data_fr, figsize=(30,20), fontsize=12, labels=True);\n#msno.matrix(Data, figsize=(40,10), fontsize=18, labels=True)","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:05.193880Z","iopub.execute_input":"2022-12-05T11:01:05.194431Z","iopub.status.idle":"2022-12-05T11:01:06.776331Z","shell.execute_reply.started":"2022-12-05T11:01:05.194386Z","shell.execute_reply":"2022-12-05T11:01:06.774995Z"},"trusted":true},"execution_count":1355,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 2160x1440 with 3 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"code","source":"Data_fr.shape","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:06.777899Z","iopub.execute_input":"2022-12-05T11:01:06.778239Z","iopub.status.idle":"2022-12-05T11:01:06.785922Z","shell.execute_reply.started":"2022-12-05T11:01:06.778209Z","shell.execute_reply":"2022-12-05T11:01:06.784722Z"},"trusted":true},"execution_count":1356,"outputs":[{"execution_count":1356,"output_type":"execute_result","data":{"text/plain":"(49693, 18)"},"metadata":{}}]},{"cell_type":"code","source":"Data_fr.info()","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:06.787592Z","iopub.execute_input":"2022-12-05T11:01:06.788047Z","iopub.status.idle":"2022-12-05T11:01:06.833609Z","shell.execute_reply.started":"2022-12-05T11:01:06.788004Z","shell.execute_reply":"2022-12-05T11:01:06.832368Z"},"trusted":true},"execution_count":1357,"outputs":[{"name":"stdout","text":"<class 'pandas.core.frame.DataFrame'>\nInt64Index: 49693 entries, 182 to 320765\nData columns (total 18 columns):\n #   Column                       Non-Null Count  Dtype  \n---  ------                       --------------  -----  \n 0   carbohydrates_100g           37562 non-null  float64\n 1   fiber_100g                   24775 non-null  float64\n 2   fruits-vegetables-nuts_100g  2101 non-null   float64\n 3   product_name                 49469 non-null  object \n 4   quantity                     47146 non-null  object \n 5   packaging_tags               45264 non-null  object \n 6   categories_fr                49693 non-null  object \n 7   nutrition_grade_fr           37771 non-null  object \n 8   pnns_groups_1                49693 non-null  object \n 9   pnns_groups_2                49693 non-null  object \n 10  main_category_fr             49693 non-null  object \n 11  energy_100g                  40104 non-null  float64\n 12  saturated-fat_100g           38419 non-null  float64\n 13  sugars_100g                  38485 non-null  float64\n 14  proteins_100g                39906 non-null  float64\n 15  salt_100g                    38529 non-null  float64\n 16  sodium_100g                  38527 non-null  float64\n 17  nutrition-score-fr_100g      37771 non-null  float64\ndtypes: float64(10), object(8)\nmemory usage: 7.2+ MB\n","output_type":"stream"}]},{"cell_type":"code","source":"Data_fr.isnull().sum() / len(Data)*100","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:06.835330Z","iopub.execute_input":"2022-12-05T11:01:06.836351Z","iopub.status.idle":"2022-12-05T11:01:06.872590Z","shell.execute_reply.started":"2022-12-05T11:01:06.836303Z","shell.execute_reply":"2022-12-05T11:01:06.871390Z"},"trusted":true},"execution_count":1358,"outputs":[{"execution_count":1358,"output_type":"execute_result","data":{"text/plain":"carbohydrates_100g              3.781814\nfiber_100g                      7.768134\nfruits-vegetables-nuts_100g    14.836706\nproduct_name                    0.069832\nquantity                        0.794022\npackaging_tags                  1.380731\ncategories_fr                   0.000000\nnutrition_grade_fr              3.716659\npnns_groups_1                   0.000000\npnns_groups_2                   0.000000\nmain_category_fr                0.000000\nenergy_100g                     2.989351\nsaturated-fat_100g              3.514646\nsugars_100g                     3.494071\nproteins_100g                   3.051077\nsalt_100g                       3.480354\nsodium_100g                     3.480977\nnutrition-score-fr_100g         3.716659\ndtype: float64"},"metadata":{}}]},{"cell_type":"code","source":"Data_fr.info()","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:06.875626Z","iopub.execute_input":"2022-12-05T11:01:06.876478Z","iopub.status.idle":"2022-12-05T11:01:06.914489Z","shell.execute_reply.started":"2022-12-05T11:01:06.876441Z","shell.execute_reply":"2022-12-05T11:01:06.913194Z"},"trusted":true},"execution_count":1359,"outputs":[{"name":"stdout","text":"<class 'pandas.core.frame.DataFrame'>\nInt64Index: 49693 entries, 182 to 320765\nData columns (total 18 columns):\n #   Column                       Non-Null Count  Dtype  \n---  ------                       --------------  -----  \n 0   carbohydrates_100g           37562 non-null  float64\n 1   fiber_100g                   24775 non-null  float64\n 2   fruits-vegetables-nuts_100g  2101 non-null   float64\n 3   product_name                 49469 non-null  object \n 4   quantity                     47146 non-null  object \n 5   packaging_tags               45264 non-null  object \n 6   categories_fr                49693 non-null  object \n 7   nutrition_grade_fr           37771 non-null  object \n 8   pnns_groups_1                49693 non-null  object \n 9   pnns_groups_2                49693 non-null  object \n 10  main_category_fr             49693 non-null  object \n 11  energy_100g                  40104 non-null  float64\n 12  saturated-fat_100g           38419 non-null  float64\n 13  sugars_100g                  38485 non-null  float64\n 14  proteins_100g                39906 non-null  float64\n 15  salt_100g                    38529 non-null  float64\n 16  sodium_100g                  38527 non-null  float64\n 17  nutrition-score-fr_100g      37771 non-null  float64\ndtypes: float64(10), object(8)\nmemory usage: 7.2+ MB\n","output_type":"stream"}]},{"cell_type":"markdown","source":"# Valeurs manquantes ou aberrantes","metadata":{"execution":{"iopub.status.busy":"2022-12-03T15:40:50.829636Z","iopub.execute_input":"2022-12-03T15:40:50.830243Z","iopub.status.idle":"2022-12-03T15:40:50.836657Z","shell.execute_reply.started":"2022-12-03T15:40:50.830172Z","shell.execute_reply":"2022-12-03T15:40:50.834996Z"}}},{"cell_type":"code","source":"# remplacer les categorical NAN par la mediane \ncategorical_features = list(Data_fr.select_dtypes(include=[object]).columns)\ncategorical_features\n\nfor col in categorical_features:\n    Data_fr[col].fillna(Data_fr[col].mode()[0], inplace=True)","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:06.915696Z","iopub.execute_input":"2022-12-05T11:01:06.916011Z","iopub.status.idle":"2022-12-05T11:01:07.030827Z","shell.execute_reply.started":"2022-12-05T11:01:06.915983Z","shell.execute_reply":"2022-12-05T11:01:07.029622Z"},"trusted":true},"execution_count":1360,"outputs":[]},{"cell_type":"code","source":"Data_fr.describe()","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:07.032203Z","iopub.execute_input":"2022-12-05T11:01:07.032588Z","iopub.status.idle":"2022-12-05T11:01:07.109011Z","shell.execute_reply.started":"2022-12-05T11:01:07.032530Z","shell.execute_reply":"2022-12-05T11:01:07.107834Z"},"trusted":true},"execution_count":1361,"outputs":[{"execution_count":1361,"output_type":"execute_result","data":{"text/plain":"       carbohydrates_100g    fiber_100g  fruits-vegetables-nuts_100g  \\\ncount        37562.000000  24775.000000                  2101.000000   \nmean            26.814572      2.560032                    39.218001   \nstd             27.291814      3.676652                    30.637054   \nmin              0.000000      0.000000                     0.000000   \n25%              3.700000      0.300000                    10.000000   \n50%             13.300000      1.600000                    40.000000   \n75%             52.400000      3.400000                    60.000000   \nmax            190.000000     86.200000                   100.000000   \n\n        energy_100g  saturated-fat_100g   sugars_100g  proteins_100g  \\\ncount  40104.000000        38419.000000  38485.000000   39906.000000   \nmean    1081.844878            5.295938     12.577069       7.692452   \nstd      797.683603            8.386928     18.397312       7.411182   \nmin        0.000000            0.000000     -0.100000       0.000000   \n25%      391.000000            0.250000      1.000000       1.500000   \n50%      980.000000            1.800000      3.800000       6.000000   \n75%     1621.000000            7.200000     15.000000      11.000000   \nmax    18700.000000          210.000000    105.000000      86.000000   \n\n          salt_100g   sodium_100g  nutrition-score-fr_100g  \ncount  38529.000000  38527.000000             37771.000000  \nmean       0.881023      0.346876                 8.266077  \nstd        1.817336      0.715321                 9.045316  \nmin        0.000000      0.000000               -15.000000  \n25%        0.066040      0.026100                 1.000000  \n50%        0.580000      0.228346                 8.000000  \n75%        1.219200      0.480000                15.000000  \nmax      211.000000     83.000000                40.000000  ","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>carbohydrates_100g</th>\n      <th>fiber_100g</th>\n      <th>fruits-vegetables-nuts_100g</th>\n      <th>energy_100g</th>\n      <th>saturated-fat_100g</th>\n      <th>sugars_100g</th>\n      <th>proteins_100g</th>\n      <th>salt_100g</th>\n      <th>sodium_100g</th>\n      <th>nutrition-score-fr_100g</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>count</th>\n      <td>37562.000000</td>\n      <td>24775.000000</td>\n      <td>2101.000000</td>\n      <td>40104.000000</td>\n      <td>38419.000000</td>\n      <td>38485.000000</td>\n      <td>39906.000000</td>\n      <td>38529.000000</td>\n      <td>38527.000000</td>\n      <td>37771.000000</td>\n    </tr>\n    <tr>\n      <th>mean</th>\n      <td>26.814572</td>\n      <td>2.560032</td>\n      <td>39.218001</td>\n      <td>1081.844878</td>\n      <td>5.295938</td>\n      <td>12.577069</td>\n      <td>7.692452</td>\n      <td>0.881023</td>\n      <td>0.346876</td>\n      <td>8.266077</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>27.291814</td>\n      <td>3.676652</td>\n      <td>30.637054</td>\n      <td>797.683603</td>\n      <td>8.386928</td>\n      <td>18.397312</td>\n      <td>7.411182</td>\n      <td>1.817336</td>\n      <td>0.715321</td>\n      <td>9.045316</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>-0.100000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>-15.000000</td>\n    </tr>\n    <tr>\n      <th>25%</th>\n      <td>3.700000</td>\n      <td>0.300000</td>\n      <td>10.000000</td>\n      <td>391.000000</td>\n      <td>0.250000</td>\n      <td>1.000000</td>\n      <td>1.500000</td>\n      <td>0.066040</td>\n      <td>0.026100</td>\n      <td>1.000000</td>\n    </tr>\n    <tr>\n      <th>50%</th>\n      <td>13.300000</td>\n      <td>1.600000</td>\n      <td>40.000000</td>\n      <td>980.000000</td>\n      <td>1.800000</td>\n      <td>3.800000</td>\n      <td>6.000000</td>\n      <td>0.580000</td>\n      <td>0.228346</td>\n      <td>8.000000</td>\n    </tr>\n    <tr>\n      <th>75%</th>\n      <td>52.400000</td>\n      <td>3.400000</td>\n      <td>60.000000</td>\n      <td>1621.000000</td>\n      <td>7.200000</td>\n      <td>15.000000</td>\n      <td>11.000000</td>\n      <td>1.219200</td>\n      <td>0.480000</td>\n      <td>15.000000</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>190.000000</td>\n      <td>86.200000</td>\n      <td>100.000000</td>\n      <td>18700.000000</td>\n      <td>210.000000</td>\n      <td>105.000000</td>\n      <td>86.000000</td>\n      <td>211.000000</td>\n      <td>83.000000</td>\n      <td>40.000000</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"Data_fr.shape","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:07.110940Z","iopub.execute_input":"2022-12-05T11:01:07.111579Z","iopub.status.idle":"2022-12-05T11:01:07.119611Z","shell.execute_reply.started":"2022-12-05T11:01:07.111519Z","shell.execute_reply":"2022-12-05T11:01:07.118269Z"},"trusted":true},"execution_count":1362,"outputs":[{"execution_count":1362,"output_type":"execute_result","data":{"text/plain":"(49693, 18)"},"metadata":{}}]},{"cell_type":"code","source":"# Seleccioner les parametres numeriques \nnumerical_features = list(Data_fr.select_dtypes(include=[\"float64\",\"int64\"]).columns)\n\n#On supprime les nutriscores qui eux peuvent être négatifs\nnumerical_features.remove('nutrition-score-fr_100g')","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:07.122372Z","iopub.execute_input":"2022-12-05T11:01:07.123584Z","iopub.status.idle":"2022-12-05T11:01:07.134328Z","shell.execute_reply.started":"2022-12-05T11:01:07.123495Z","shell.execute_reply":"2022-12-05T11:01:07.132817Z"},"trusted":true},"execution_count":1363,"outputs":[]},{"cell_type":"code","source":"datas_cleaned = Data_fr[~((Data_fr.product_name.isnull()) \n                        & ((Data_fr.pnns_groups_1 == \"unknown\") \n                           | (Data_fr.main_category_fr == \"unknown\")))]","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:07.137045Z","iopub.execute_input":"2022-12-05T11:01:07.137615Z","iopub.status.idle":"2022-12-05T11:01:07.173841Z","shell.execute_reply.started":"2022-12-05T11:01:07.137544Z","shell.execute_reply":"2022-12-05T11:01:07.172615Z"},"trusted":true},"execution_count":1364,"outputs":[]},{"cell_type":"code","source":"datas_cleaned.shape","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:07.175839Z","iopub.execute_input":"2022-12-05T11:01:07.176607Z","iopub.status.idle":"2022-12-05T11:01:07.184036Z","shell.execute_reply.started":"2022-12-05T11:01:07.176533Z","shell.execute_reply":"2022-12-05T11:01:07.183135Z"},"trusted":true},"execution_count":1365,"outputs":[{"execution_count":1365,"output_type":"execute_result","data":{"text/plain":"(49693, 18)"},"metadata":{}}]},{"cell_type":"code","source":"#Supprime les lignes dont toutes les numerical_features sont à 0 ou nulles\ndatas_cleaned = datas_cleaned.loc[~((datas_cleaned[numerical_features]==0) | (datas_cleaned[numerical_features].isnull())).all(axis=1)]\ndatas_cleaned.shape","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:07.185466Z","iopub.execute_input":"2022-12-05T11:01:07.186102Z","iopub.status.idle":"2022-12-05T11:01:07.218478Z","shell.execute_reply.started":"2022-12-05T11:01:07.186066Z","shell.execute_reply":"2022-12-05T11:01:07.217250Z"},"trusted":true},"execution_count":1366,"outputs":[{"execution_count":1366,"output_type":"execute_result","data":{"text/plain":"(40311, 18)"},"metadata":{}}]},{"cell_type":"code","source":"#On supprime les lignes contenant des valeurs négatives et des max aberrants\ndatas_cleaned = datas_cleaned[~(datas_cleaned[numerical_features] < 0).any(axis=1)]\ndatas_cleaned = datas_cleaned[~(datas_cleaned[numerical_features].isin([999999,9999999])).any(axis=1)]","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:07.220065Z","iopub.execute_input":"2022-12-05T11:01:07.220476Z","iopub.status.idle":"2022-12-05T11:01:07.261303Z","shell.execute_reply.started":"2022-12-05T11:01:07.220443Z","shell.execute_reply":"2022-12-05T11:01:07.259895Z"},"trusted":true},"execution_count":1367,"outputs":[]},{"cell_type":"code","source":"g_100g_features = ['carbohydrates_100g','fiber_100g','fruits-vegetables-nuts_100g','energy_100g','saturated-fat_100g','sugars_100g','proteins_100g','salt_100g','sodium_100g','nutrition-score-fr_100g']\n\ndatas_cleaned = datas_cleaned[~(datas_cleaned[g_100g_features] > 100).any(axis=1)]","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:07.263128Z","iopub.execute_input":"2022-12-05T11:01:07.263692Z","iopub.status.idle":"2022-12-05T11:01:07.276202Z","shell.execute_reply.started":"2022-12-05T11:01:07.263655Z","shell.execute_reply":"2022-12-05T11:01:07.274983Z"},"trusted":true},"execution_count":1368,"outputs":[]},{"cell_type":"markdown","source":"valeurs de sodium_100g qui ne peuvent pas être supérieurs à salt_100g","metadata":{}},{"cell_type":"code","source":"datas_cleaned = datas_cleaned[~(datas_cleaned['sodium_100g'] > datas_cleaned['salt_100g'])]","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:07.278076Z","iopub.execute_input":"2022-12-05T11:01:07.278744Z","iopub.status.idle":"2022-12-05T11:01:07.286921Z","shell.execute_reply.started":"2022-12-05T11:01:07.278707Z","shell.execute_reply":"2022-12-05T11:01:07.285940Z"},"trusted":true},"execution_count":1369,"outputs":[]},{"cell_type":"markdown","source":"Densité d'energie maximales pour 100g sont de 3700 kJ/100g (source Wikipedia)","metadata":{}},{"cell_type":"code","source":"datas_cleaned = datas_cleaned[~(datas_cleaned['energy_100g'] > 3700)]","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:07.288037Z","iopub.execute_input":"2022-12-05T11:01:07.289574Z","iopub.status.idle":"2022-12-05T11:01:07.301915Z","shell.execute_reply.started":"2022-12-05T11:01:07.289509Z","shell.execute_reply":"2022-12-05T11:01:07.300482Z"},"trusted":true},"execution_count":1370,"outputs":[]},{"cell_type":"code","source":"datas_cleaned.shape","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:07.303987Z","iopub.execute_input":"2022-12-05T11:01:07.304641Z","iopub.status.idle":"2022-12-05T11:01:07.314300Z","shell.execute_reply.started":"2022-12-05T11:01:07.304602Z","shell.execute_reply":"2022-12-05T11:01:07.313070Z"},"trusted":true},"execution_count":1371,"outputs":[{"execution_count":1371,"output_type":"execute_result","data":{"text/plain":"(1764, 18)"},"metadata":{}}]},{"cell_type":"code","source":"datas_cleaned.describe()","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:07.315798Z","iopub.execute_input":"2022-12-05T11:01:07.316620Z","iopub.status.idle":"2022-12-05T11:01:07.365634Z","shell.execute_reply.started":"2022-12-05T11:01:07.316542Z","shell.execute_reply":"2022-12-05T11:01:07.364496Z"},"trusted":true},"execution_count":1372,"outputs":[{"execution_count":1372,"output_type":"execute_result","data":{"text/plain":"       carbohydrates_100g   fiber_100g  fruits-vegetables-nuts_100g  \\\ncount         1380.000000  1049.000000                   198.000000   \nmean             2.647152     0.989899                    43.649495   \nstd              6.561278     1.195807                    29.503837   \nmin              0.000000     0.000000                     0.000000   \n25%              0.500000     0.000000                    18.000000   \n50%              1.500000     0.700000                    50.000000   \n75%              3.000000     1.900000                    60.000000   \nmax            100.000000    18.000000                   100.000000   \n\n       energy_100g  saturated-fat_100g  sugars_100g  proteins_100g  \\\ncount  1509.000000         1392.000000  1469.000000    1521.000000   \nmean     53.766772            0.210709     3.893436       0.992761   \nstd      34.893891            1.574758    11.881980       1.994765   \nmin       0.000000            0.000000     0.000000       0.000000   \n25%      17.000000            0.000000     0.200000       0.000000   \n50%      63.000000            0.000000     0.800000       0.500000   \n75%      83.000000            0.100000     2.700000       1.300000   \nmax     100.000000           24.000000   100.000000      27.500000   \n\n         salt_100g  sodium_100g  nutrition-score-fr_100g  \ncount  1495.000000  1494.000000              1332.000000  \nmean      0.387443     0.152610                 0.131381  \nstd       0.962007     0.378856                 4.399646  \nmin       0.000000     0.000000               -11.000000  \n25%       0.007620     0.003000                -4.000000  \n50%       0.040000     0.015748                 1.000000  \n75%       0.594720     0.235071                 2.000000  \nmax      18.000000     7.086614                20.000000  ","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>carbohydrates_100g</th>\n      <th>fiber_100g</th>\n      <th>fruits-vegetables-nuts_100g</th>\n      <th>energy_100g</th>\n      <th>saturated-fat_100g</th>\n      <th>sugars_100g</th>\n      <th>proteins_100g</th>\n      <th>salt_100g</th>\n      <th>sodium_100g</th>\n      <th>nutrition-score-fr_100g</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>count</th>\n      <td>1380.000000</td>\n      <td>1049.000000</td>\n      <td>198.000000</td>\n      <td>1509.000000</td>\n      <td>1392.000000</td>\n      <td>1469.000000</td>\n      <td>1521.000000</td>\n      <td>1495.000000</td>\n      <td>1494.000000</td>\n      <td>1332.000000</td>\n    </tr>\n    <tr>\n      <th>mean</th>\n      <td>2.647152</td>\n      <td>0.989899</td>\n      <td>43.649495</td>\n      <td>53.766772</td>\n      <td>0.210709</td>\n      <td>3.893436</td>\n      <td>0.992761</td>\n      <td>0.387443</td>\n      <td>0.152610</td>\n      <td>0.131381</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>6.561278</td>\n      <td>1.195807</td>\n      <td>29.503837</td>\n      <td>34.893891</td>\n      <td>1.574758</td>\n      <td>11.881980</td>\n      <td>1.994765</td>\n      <td>0.962007</td>\n      <td>0.378856</td>\n      <td>4.399646</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>-11.000000</td>\n    </tr>\n    <tr>\n      <th>25%</th>\n      <td>0.500000</td>\n      <td>0.000000</td>\n      <td>18.000000</td>\n      <td>17.000000</td>\n      <td>0.000000</td>\n      <td>0.200000</td>\n      <td>0.000000</td>\n      <td>0.007620</td>\n      <td>0.003000</td>\n      <td>-4.000000</td>\n    </tr>\n    <tr>\n      <th>50%</th>\n      <td>1.500000</td>\n      <td>0.700000</td>\n      <td>50.000000</td>\n      <td>63.000000</td>\n      <td>0.000000</td>\n      <td>0.800000</td>\n      <td>0.500000</td>\n      <td>0.040000</td>\n      <td>0.015748</td>\n      <td>1.000000</td>\n    </tr>\n    <tr>\n      <th>75%</th>\n      <td>3.000000</td>\n      <td>1.900000</td>\n      <td>60.000000</td>\n      <td>83.000000</td>\n      <td>0.100000</td>\n      <td>2.700000</td>\n      <td>1.300000</td>\n      <td>0.594720</td>\n      <td>0.235071</td>\n      <td>2.000000</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>100.000000</td>\n      <td>18.000000</td>\n      <td>100.000000</td>\n      <td>100.000000</td>\n      <td>24.000000</td>\n      <td>100.000000</td>\n      <td>27.500000</td>\n      <td>18.000000</td>\n      <td>7.086614</td>\n      <td>20.000000</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"markdown","source":"Il est important de standardiser les échantillons avant le test, sinon une distribution normale avec une moyenne et/ou une variation différente échouera","metadata":{}},{"cell_type":"code","source":"# Normalisation de donnes \ndef norm_to_zero_one(datas_cleaned):\n    return (datas_cleaned - datas_cleaned.min()) * 1.0 / (datas_cleaned.max() - datas_cleaned.min())","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:07.367122Z","iopub.execute_input":"2022-12-05T11:01:07.367495Z","iopub.status.idle":"2022-12-05T11:01:07.373957Z","shell.execute_reply.started":"2022-12-05T11:01:07.367460Z","shell.execute_reply":"2022-12-05T11:01:07.372662Z"},"trusted":true},"execution_count":1373,"outputs":[]},{"cell_type":"code","source":"# df normalise with NaN\n\ndatas = numeric_data = datas_cleaned.select_dtypes(include=[np.number]).apply(norm_to_zero_one)\ncategorical_data = datas_cleaned.select_dtypes(exclude=[np.number])","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:07.375967Z","iopub.execute_input":"2022-12-05T11:01:07.376653Z","iopub.status.idle":"2022-12-05T11:01:07.401229Z","shell.execute_reply.started":"2022-12-05T11:01:07.376605Z","shell.execute_reply":"2022-12-05T11:01:07.400069Z"},"trusted":true},"execution_count":1374,"outputs":[]},{"cell_type":"code","source":"datas_cleaned = pd.merge(categorical_data, datas, left_index=True, right_index=True)","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:07.402859Z","iopub.execute_input":"2022-12-05T11:01:07.403244Z","iopub.status.idle":"2022-12-05T11:01:07.415778Z","shell.execute_reply.started":"2022-12-05T11:01:07.403208Z","shell.execute_reply":"2022-12-05T11:01:07.414831Z"},"trusted":true},"execution_count":1375,"outputs":[{"execution_count":1375,"output_type":"execute_result","data":{"text/plain":"product_name                      0\nquantity                          0\npackaging_tags                    0\ncategories_fr                     0\nnutrition_grade_fr                0\npnns_groups_1                     0\npnns_groups_2                     0\nmain_category_fr                  0\ncarbohydrates_100g              384\nfiber_100g                      715\nfruits-vegetables-nuts_100g    1566\nenergy_100g                     255\nsaturated-fat_100g              372\nsugars_100g                     295\nproteins_100g                   243\nsalt_100g                       269\nsodium_100g                     270\nnutrition-score-fr_100g         432\ndtype: int64"},"metadata":{}}]},{"cell_type":"markdown","source":"Ont va regarder si la distribuition sui une loi normale, ce que nous aiderai a prendre une decision relativement a methode d'impotation des valeurs manquantes. ","metadata":{}},{"cell_type":"code","source":"import scipy.stats as stats\nimport warnings\nwarnings.filterwarnings('ignore')\n\nsns.set_style(\"whitegrid\")\nfig = plt.figure(figsize=(21,30))\n\nsub = 0\nfor i in range(len(numerical_features)):\n    fig.add_subplot(4,3,i+1)\n    \n    left, width = 0, 1\n    bottom, height = 0, 1\n    right = left + width\n    top = bottom + height\n    \n    colonne = numerical_features[i]\n    kstest = stats.kstest(datas_cleaned[colonne].notnull(),'norm', mode='asymp')\n    ax = sns.distplot(datas_cleaned[colonne], fit=stats.norm, kde=False)\n    ax.set_title(\"Distribution vs loi normale : {}\".format(colonne))\n    ax.text(right, top, 'Test Kolmogorov-Smirnov\\n Pvalue: {:.2} \\n Stat :{:.2} '.format(kstest.pvalue, kstest.statistic),\n            horizontalalignment='right',\n            verticalalignment='top',\n            style='italic', transform=ax.transAxes, fontsize = 12,\n            bbox={'facecolor':'#00afe6', 'alpha':0.5, 'pad':0})\n    sub += 1\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:07.417437Z","iopub.execute_input":"2022-12-05T11:01:07.417829Z","iopub.status.idle":"2022-12-05T11:01:10.461124Z","shell.execute_reply.started":"2022-12-05T11:01:07.417794Z","shell.execute_reply":"2022-12-05T11:01:10.459933Z"},"trusted":true},"execution_count":1376,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1512x2160 with 9 Axes>","image/png":"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\n"},"metadata":{}}]},{"cell_type":"markdown","source":"En se basant sur les projections obtenus et les résultats des tests de Kolmogorov-Smirnov (Pvalue < au niveau de test de 5%) on rejette donc l'hypothèse de normalité des distributions de ces variables. Il serait donc inexacte d'imputer les valeurs manquantes par la moyenne.\nPour toute les distribuitions que ne suivent pas la loi gaussiene, nous allons imputer avec l'algorithme des K Nearest Neighbours (KNN).","metadata":{}},{"cell_type":"markdown","source":"Valeurs Manquantes ","metadata":{}},{"cell_type":"code","source":"datas_cleaned[numerical_features].isnull().sum().sort_values(ascending=False)","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:10.463113Z","iopub.execute_input":"2022-12-05T11:01:10.463852Z","iopub.status.idle":"2022-12-05T11:01:10.477953Z","shell.execute_reply.started":"2022-12-05T11:01:10.463806Z","shell.execute_reply":"2022-12-05T11:01:10.476404Z"},"trusted":true},"execution_count":1377,"outputs":[{"execution_count":1377,"output_type":"execute_result","data":{"text/plain":"fruits-vegetables-nuts_100g    1566\nfiber_100g                      715\ncarbohydrates_100g              384\nsaturated-fat_100g              372\nsugars_100g                     295\nsodium_100g                     270\nsalt_100g                       269\nenergy_100g                     255\nproteins_100g                   243\ndtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"datas_cleaned[numerical_features].shape","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:10.479382Z","iopub.execute_input":"2022-12-05T11:01:10.480164Z","iopub.status.idle":"2022-12-05T11:01:10.492294Z","shell.execute_reply.started":"2022-12-05T11:01:10.479905Z","shell.execute_reply":"2022-12-05T11:01:10.491048Z"},"trusted":true},"execution_count":1378,"outputs":[{"execution_count":1378,"output_type":"execute_result","data":{"text/plain":"(1764, 9)"},"metadata":{}}]},{"cell_type":"code","source":"datas_cleaned[numerical_features].dropna(axis=0, how=\"all\")","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:10.495621Z","iopub.execute_input":"2022-12-05T11:01:10.495970Z","iopub.status.idle":"2022-12-05T11:01:10.522234Z","shell.execute_reply.started":"2022-12-05T11:01:10.495938Z","shell.execute_reply":"2022-12-05T11:01:10.520683Z"},"trusted":true},"execution_count":1379,"outputs":[{"execution_count":1379,"output_type":"execute_result","data":{"text/plain":"        carbohydrates_100g  fiber_100g  fruits-vegetables-nuts_100g  \\\n20776                0.030    0.050000                          NaN   \n20832                0.034    0.044444                          NaN   \n20834                0.030    0.044444                          NaN   \n27150                0.015         NaN                          0.0   \n36080                0.008    0.005556                          NaN   \n...                    ...         ...                          ...   \n318340               0.000    0.000000                          NaN   \n318360                 NaN    0.000000                          NaN   \n318393                 NaN    0.000000                          NaN   \n318394                 NaN    0.000000                          NaN   \n320763               0.005    0.011111                          NaN   \n\n        energy_100g  saturated-fat_100g  sugars_100g  proteins_100g  \\\n20776         0.880            0.000000        0.000       0.043636   \n20832         0.210            0.000000        0.031       0.043636   \n20834         0.800            0.000000        0.030       0.040000   \n27150         0.420            0.000000        0.015       0.000000   \n36080         0.290            0.004167        0.008       0.003636   \n...             ...                 ...          ...            ...   \n318340        0.018            0.000000        0.000       0.000000   \n318360        0.840            0.000000        0.046       0.000000   \n318393        0.790            0.000000        0.044       0.000000   \n318394        0.790            0.000000        0.045       0.000000   \n320763        0.210            0.008333        0.005       0.018182   \n\n        salt_100g  sodium_100g  \n20776    0.005556     0.005556  \n20832    0.005556     0.005556  \n20834    0.007222     0.007222  \n27150    0.002222     0.002222  \n36080    0.002778     0.002778  \n...           ...          ...  \n318340   0.003333     0.003333  \n318360   0.000000     0.000000  \n318393   0.034444     0.034444  \n318394   0.002778     0.002778  \n320763   0.001411     0.001411  \n\n[1764 rows x 9 columns]","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>carbohydrates_100g</th>\n      <th>fiber_100g</th>\n      <th>fruits-vegetables-nuts_100g</th>\n      <th>energy_100g</th>\n      <th>saturated-fat_100g</th>\n      <th>sugars_100g</th>\n      <th>proteins_100g</th>\n      <th>salt_100g</th>\n      <th>sodium_100g</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>20776</th>\n      <td>0.030</td>\n      <td>0.050000</td>\n      <td>NaN</td>\n      <td>0.880</td>\n      <td>0.000000</td>\n      <td>0.000</td>\n      <td>0.043636</td>\n      <td>0.005556</td>\n      <td>0.005556</td>\n    </tr>\n    <tr>\n      <th>20832</th>\n      <td>0.034</td>\n      <td>0.044444</td>\n      <td>NaN</td>\n      <td>0.210</td>\n      <td>0.000000</td>\n      <td>0.031</td>\n      <td>0.043636</td>\n      <td>0.005556</td>\n      <td>0.005556</td>\n    </tr>\n    <tr>\n      <th>20834</th>\n      <td>0.030</td>\n      <td>0.044444</td>\n      <td>NaN</td>\n      <td>0.800</td>\n      <td>0.000000</td>\n      <td>0.030</td>\n      <td>0.040000</td>\n      <td>0.007222</td>\n      <td>0.007222</td>\n    </tr>\n    <tr>\n      <th>27150</th>\n      <td>0.015</td>\n      <td>NaN</td>\n      <td>0.0</td>\n      <td>0.420</td>\n      <td>0.000000</td>\n      <td>0.015</td>\n      <td>0.000000</td>\n      <td>0.002222</td>\n      <td>0.002222</td>\n    </tr>\n    <tr>\n      <th>36080</th>\n      <td>0.008</td>\n      <td>0.005556</td>\n      <td>NaN</td>\n      <td>0.290</td>\n      <td>0.004167</td>\n      <td>0.008</td>\n      <td>0.003636</td>\n      <td>0.002778</td>\n      <td>0.002778</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    </tr>\n    <tr>\n      <th>318340</th>\n      <td>0.000</td>\n      <td>0.000000</td>\n      <td>NaN</td>\n      <td>0.018</td>\n      <td>0.000000</td>\n      <td>0.000</td>\n      <td>0.000000</td>\n      <td>0.003333</td>\n      <td>0.003333</td>\n    </tr>\n    <tr>\n      <th>318360</th>\n      <td>NaN</td>\n      <td>0.000000</td>\n      <td>NaN</td>\n      <td>0.840</td>\n      <td>0.000000</td>\n      <td>0.046</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n    </tr>\n    <tr>\n      <th>318393</th>\n      <td>NaN</td>\n      <td>0.000000</td>\n      <td>NaN</td>\n      <td>0.790</td>\n      <td>0.000000</td>\n      <td>0.044</td>\n      <td>0.000000</td>\n      <td>0.034444</td>\n      <td>0.034444</td>\n    </tr>\n    <tr>\n      <th>318394</th>\n      <td>NaN</td>\n      <td>0.000000</td>\n      <td>NaN</td>\n      <td>0.790</td>\n      <td>0.000000</td>\n      <td>0.045</td>\n      <td>0.000000</td>\n      <td>0.002778</td>\n      <td>0.002778</td>\n    </tr>\n    <tr>\n      <th>320763</th>\n      <td>0.005</td>\n      <td>0.011111</td>\n      <td>NaN</td>\n      <td>0.210</td>\n      <td>0.008333</td>\n      <td>0.005</td>\n      <td>0.018182</td>\n      <td>0.001411</td>\n      <td>0.001411</td>\n    </tr>\n  </tbody>\n</table>\n<p>1764 rows × 9 columns</p>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"datas_cleaned[numerical_features].isnull().sum().sort_values(ascending=False)","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:10.523774Z","iopub.execute_input":"2022-12-05T11:01:10.524097Z","iopub.status.idle":"2022-12-05T11:01:10.535699Z","shell.execute_reply.started":"2022-12-05T11:01:10.524067Z","shell.execute_reply":"2022-12-05T11:01:10.534419Z"},"trusted":true},"execution_count":1380,"outputs":[{"execution_count":1380,"output_type":"execute_result","data":{"text/plain":"fruits-vegetables-nuts_100g    1566\nfiber_100g                      715\ncarbohydrates_100g              384\nsaturated-fat_100g              372\nsugars_100g                     295\nsodium_100g                     270\nsalt_100g                       269\nenergy_100g                     255\nproteins_100g                   243\ndtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"# KNN pour les autres variables\nfrom sklearn.impute import KNNImputer\n\n# On entraine le modèle d'imputation sur un échantillon de données\nknn_features = ['carbohydrates_100g','sodium_100g','saturated-fat_100g','fiber_100g', 'fruits-vegetables-nuts_100g', 'nutrition-score-fr_100g', 'salt_100g','energy_100g','proteins_100g', 'sugars_100g']\nsample_datas = datas_cleaned[knn_features].sample(frac=0.80, random_state=1)\nimputer = KNNImputer(n_neighbors=5, missing_values=np.nan)\nimputer.fit(sample_datas)","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:10.537653Z","iopub.execute_input":"2022-12-05T11:01:10.538490Z","iopub.status.idle":"2022-12-05T11:01:10.554749Z","shell.execute_reply.started":"2022-12-05T11:01:10.538445Z","shell.execute_reply":"2022-12-05T11:01:10.553361Z"},"trusted":true},"execution_count":1381,"outputs":[{"execution_count":1381,"output_type":"execute_result","data":{"text/plain":"KNNImputer()"},"metadata":{}}]},{"cell_type":"code","source":"# Puis on applique le modèle sur l'ensemble des données\ndatas_imputed = imputer.transform(datas_cleaned[knn_features])\ndf_datas_imputed = pd.DataFrame(datas_imputed, columns=knn_features)","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:10.556579Z","iopub.execute_input":"2022-12-05T11:01:10.556928Z","iopub.status.idle":"2022-12-05T11:01:10.838791Z","shell.execute_reply.started":"2022-12-05T11:01:10.556897Z","shell.execute_reply":"2022-12-05T11:01:10.837457Z"},"trusted":true},"execution_count":1382,"outputs":[]},{"cell_type":"code","source":"for col_knn in knn_features:\n    datas_cleaned[col_knn] = df_datas_imputed[col_knn].values","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:10.840732Z","iopub.execute_input":"2022-12-05T11:01:10.841177Z","iopub.status.idle":"2022-12-05T11:01:10.849234Z","shell.execute_reply.started":"2022-12-05T11:01:10.841135Z","shell.execute_reply":"2022-12-05T11:01:10.848211Z"},"trusted":true},"execution_count":1383,"outputs":[]},{"cell_type":"code","source":"# datas_cleaned.iloc[np.where(datas_cleaned['energy_100g'].isnull())[0]]","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:10.850626Z","iopub.execute_input":"2022-12-05T11:01:10.851280Z","iopub.status.idle":"2022-12-05T11:01:10.861743Z","shell.execute_reply.started":"2022-12-05T11:01:10.851247Z","shell.execute_reply":"2022-12-05T11:01:10.860457Z"},"trusted":true},"execution_count":1384,"outputs":[]},{"cell_type":"code","source":"sns.set_style(\"whitegrid\")\nfig = plt.figure(figsize=(21,20))\n\nsub = 0\nfor i in range(len(numerical_features)):\n    fig.add_subplot(4,3,i+1)\n    colonne = numerical_features[i]\n    kstest = stats.kstest(datas_cleaned[colonne].notnull(),'norm')\n    ax = sns.distplot(datas_cleaned[colonne], fit=stats.norm, kde=False)\n    ax.set_title(\"Distribution vs loi normale : {}\".format(colonne))\n    sub += 1\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:10.865357Z","iopub.execute_input":"2022-12-05T11:01:10.865815Z","iopub.status.idle":"2022-12-05T11:01:13.200543Z","shell.execute_reply.started":"2022-12-05T11:01:10.865779Z","shell.execute_reply":"2022-12-05T11:01:13.199220Z"},"trusted":true},"execution_count":1385,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1512x1440 with 9 Axes>","image/png":"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\n"},"metadata":{}}]},{"cell_type":"markdown","source":"La distribuition n'ai pas change apres l'imputation","metadata":{}},{"cell_type":"code","source":"datas_cleaned.isnull().sum().sort_values(ascending=False)","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:13.202154Z","iopub.execute_input":"2022-12-05T11:01:13.202524Z","iopub.status.idle":"2022-12-05T11:01:13.216514Z","shell.execute_reply.started":"2022-12-05T11:01:13.202490Z","shell.execute_reply":"2022-12-05T11:01:13.215623Z"},"trusted":true},"execution_count":1386,"outputs":[{"execution_count":1386,"output_type":"execute_result","data":{"text/plain":"product_name                   0\nquantity                       0\nsodium_100g                    0\nsalt_100g                      0\nproteins_100g                  0\nsugars_100g                    0\nsaturated-fat_100g             0\nenergy_100g                    0\nfruits-vegetables-nuts_100g    0\nfiber_100g                     0\ncarbohydrates_100g             0\nmain_category_fr               0\npnns_groups_2                  0\npnns_groups_1                  0\nnutrition_grade_fr             0\ncategories_fr                  0\npackaging_tags                 0\nnutrition-score-fr_100g        0\ndtype: int64"},"metadata":{}}]},{"cell_type":"markdown","source":"Nous avons tout les donnes reemplis apres l'application de knn imputer ","metadata":{}},{"cell_type":"code","source":"datas_cleaned.shape","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:13.217789Z","iopub.execute_input":"2022-12-05T11:01:13.218711Z","iopub.status.idle":"2022-12-05T11:01:13.226583Z","shell.execute_reply.started":"2022-12-05T11:01:13.218659Z","shell.execute_reply":"2022-12-05T11:01:13.225133Z"},"trusted":true},"execution_count":1387,"outputs":[{"execution_count":1387,"output_type":"execute_result","data":{"text/plain":"(1764, 18)"},"metadata":{}}]},{"cell_type":"code","source":"datas_cleaned.to_parquet('datas_cleaned.parquet.gzip',compression='gzip')","metadata":{"execution":{"iopub.status.busy":"2022-12-05T11:01:13.228278Z","iopub.execute_input":"2022-12-05T11:01:13.229434Z","iopub.status.idle":"2022-12-05T11:01:13.263126Z","shell.execute_reply.started":"2022-12-05T11:01:13.229392Z","shell.execute_reply":"2022-12-05T11:01:13.262063Z"},"trusted":true},"execution_count":1388,"outputs":[]}]}