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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import joblib\n",
"\n",
"obj = joblib.load('traning_zone/mini_modèle/maquillage/transformers/object.pkl')"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array(['maquillage'], dtype=object)"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"obj.inverse_transform([1])"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"from traning_zone.traitement_data.feature_engeneering_mini_modele.data_clearning import *\n",
"from traning_zone.data_import.data_importation import *"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"data"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"df = clearning_pred(*[\"1964\"])\n",
"DF = data_import(*[\"1964\"])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"obj = joblib.load('traning_zone/mini_modèle/maquillage/transformers/object.pkl')\n",
"tv = joblib.load('traning_zone/mini_modèle/maquillage/transformers/tv_transform.pkl')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(array(['confiserie de sucre'], dtype=object),\n",
" array(['confiserie'], dtype=object))"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from traning_zone.classe_prediction.classe_prediction import *\n",
"\n",
"X = [\"milka e\"] \n",
"\n",
"pred = Prediction(X)\n",
"pred.final_prediction()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"obj = joblib.load('traning_zone/modèles/transformers/object.pkl')\n",
"tv = joblib.load('traning_zone/modèles/transformers/tv_transform.pkl')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"df = pd.read_csv(\"data_maquillage.csv\")\n",
"DF = df.copy()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Unnamed: 0</th>\n",
" <th>COUNTRY_KEY</th>\n",
" <th>ITEM_DESC</th>\n",
" <th>BARCODE</th>\n",
" <th>BEM_CLASS_KEY</th>\n",
" <th>BEM_CLASS_DESC_FR</th>\n",
" <th>prediction</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0</td>\n",
" <td>FRA</td>\n",
" <td>150ML SECHE VERNIS VITRY</td>\n",
" <td>3538892526034</td>\n",
" <td>1964</td>\n",
" <td>DIVERS MAQUILLAGE</td>\n",
" <td>maquillage des ongles</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1</td>\n",
" <td>FRA</td>\n",
" <td>15COM.SOMMEIL TRIPLE ACTI.PURE</td>\n",
" <td>3701056803443</td>\n",
" <td>1964</td>\n",
" <td>DIVERS MAQUILLAGE</td>\n",
" <td>maquillage</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2</td>\n",
" <td>FRA</td>\n",
" <td>2 EPONG.DEMAQUILLER N°42 SANOD</td>\n",
" <td>3701509580426</td>\n",
" <td>1964</td>\n",
" <td>DIVERS MAQUILLAGE</td>\n",
" <td>autres produits maquillage</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>3</td>\n",
" <td>FRA</td>\n",
" <td>200ML DIFF PFUM FIGUE CDP</td>\n",
" <td>3551780164033</td>\n",
" <td>1964</td>\n",
" <td>DIVERS MAQUILLAGE</td>\n",
" <td>maquillage</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>4</td>\n",
" <td>FRA</td>\n",
" <td>2PCS EPONGE DEMAQUILLANTE</td>\n",
" <td>3276558220253</td>\n",
" <td>1964</td>\n",
" <td>DIVERS MAQUILLAGE</td>\n",
" <td>autres produits maquillage</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Unnamed: 0 COUNTRY_KEY ITEM_DESC BARCODE \\\n",
"0 0 FRA 150ML SECHE VERNIS VITRY 3538892526034 \n",
"1 1 FRA 15COM.SOMMEIL TRIPLE ACTI.PURE 3701056803443 \n",
"2 2 FRA 2 EPONG.DEMAQUILLER N°42 SANOD 3701509580426 \n",
"3 3 FRA 200ML DIFF PFUM FIGUE CDP 3551780164033 \n",
"4 4 FRA 2PCS EPONGE DEMAQUILLANTE 3276558220253 \n",
"\n",
" BEM_CLASS_KEY BEM_CLASS_DESC_FR prediction \n",
"0 1964 DIVERS MAQUILLAGE maquillage des ongles \n",
"1 1964 DIVERS MAQUILLAGE maquillage \n",
"2 1964 DIVERS MAQUILLAGE autres produits maquillage \n",
"3 1964 DIVERS MAQUILLAGE maquillage \n",
"4 1964 DIVERS MAQUILLAGE autres produits maquillage "
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.head()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"X = df.ITEM_DESC\n",
"tv_x = tv.transform(X)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"Model = joblib.load('traning_zone/hyper_modèles/LogisticRegression/LogisticRegression.pkl')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([ 4, 12, 8, 17, 4, 4, 4, 2, 8, 12, 9, 17, 18, 4, 4, 11, 9,\n",
" 9, 13, 18, 18, 13, 18, 18, 4, 4, 18, 6, 6, 18, 4, 17, 4, 13,\n",
" 13, 13, 9, 9, 9, 18, 18, 18, 18, 18, 18, 4, 17, 17, 17, 17, 17,\n",
" 17, 17, 17, 17, 5, 5, 12, 12, 13, 9, 9, 9, 9, 9, 9, 18, 4,\n",
" 6, 11, 11, 11, 4, 4, 9, 4, 9, 9, 9, 9, 9, 9, 9, 9, 18,\n",
" 2, 18, 4, 18, 18, 18, 9, 2, 11, 2, 9])"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"y_pred = Model.predict(tv_x)\n",
"y_pred"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array(['confiserie', 'premiers soins', 'hygiène féminine intime',\n",
" 'soins du corps', 'confiserie', 'confiserie', 'confiserie',\n",
" 'bain douches savons', 'hygiène féminine intime', 'premiers soins',\n",
" 'maquillage', 'soins du corps', 'soins du visage', 'confiserie',\n",
" 'confiserie', 'parfums', 'maquillage', 'maquillage',\n",
" 'produits diététiques', 'soins du visage', 'soins du visage',\n",
" 'produits diététiques', 'soins du visage', 'soins du visage',\n",
" 'confiserie', 'confiserie', 'soins du visage',\n",
" 'hygiène bucco dentaire', 'hygiène bucco dentaire',\n",
" 'soins du visage', 'confiserie', 'soins du corps', 'confiserie',\n",
" 'produits diététiques', 'produits diététiques',\n",
" 'produits diététiques', 'maquillage', 'maquillage', 'maquillage',\n",
" 'soins du visage', 'soins du visage', 'soins du visage',\n",
" 'soins du visage', 'soins du visage', 'soins du visage',\n",
" 'confiserie', 'soins du corps', 'soins du corps', 'soins du corps',\n",
" 'soins du corps', 'soins du corps', 'soins du corps',\n",
" 'soins du corps', 'soins du corps', 'soins du corps',\n",
" 'fruits et jus de fruits surgelés',\n",
" 'fruits et jus de fruits surgelés', 'premiers soins',\n",
" 'premiers soins', 'produits diététiques', 'maquillage',\n",
" 'maquillage', 'maquillage', 'maquillage', 'maquillage',\n",
" 'maquillage', 'soins du visage', 'confiserie',\n",
" 'hygiène bucco dentaire', 'parfums', 'parfums', 'parfums',\n",
" 'confiserie', 'confiserie', 'maquillage', 'confiserie',\n",
" 'maquillage', 'maquillage', 'maquillage', 'maquillage',\n",
" 'maquillage', 'maquillage', 'maquillage', 'maquillage',\n",
" 'soins du visage', 'bain douches savons', 'soins du visage',\n",
" 'confiserie', 'soins du visage', 'soins du visage',\n",
" 'soins du visage', 'maquillage', 'bain douches savons', 'parfums',\n",
" 'bain douches savons', 'maquillage'], dtype=object)"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"Y = obj.inverse_transform(y_pred)\n",
"Y"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array(['alimentation infantile', 'bain douches savons',\n",
" 'coloration cheveux', 'confiserie',\n",
" 'fruits et jus de fruits surgelés', 'hygiène bucco dentaire',\n",
" 'hygiène bébé', 'hygiène féminine intime', 'maquillage', 'oeufs',\n",
" 'parfums', 'premiers soins', 'produits diététiques',\n",
" 'produits solaires', 'shampooings', 'soins cheveux',\n",
" 'soins du corps', 'soins du visage'], dtype=object)"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"y = [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18]\n",
"y = obj.inverse_transform(y)\n",
"y"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"DF[\"Prediction\"] = Y"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Unnamed: 0</th>\n",
" <th>COUNTRY_KEY</th>\n",
" <th>ITEM_DESC</th>\n",
" <th>BARCODE</th>\n",
" <th>BEM_CLASS_KEY</th>\n",
" <th>BEM_CLASS_DESC_FR</th>\n",
" <th>prediction</th>\n",
" <th>Prediction</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0</td>\n",
" <td>FRA</td>\n",
" <td>150ML SECHE VERNIS VITRY</td>\n",
" <td>3538892526034</td>\n",
" <td>1964</td>\n",
" <td>DIVERS MAQUILLAGE</td>\n",
" <td>maquillage des ongles</td>\n",
" <td>confiserie</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1</td>\n",
" <td>FRA</td>\n",
" <td>15COM.SOMMEIL TRIPLE ACTI.PURE</td>\n",
" <td>3701056803443</td>\n",
" <td>1964</td>\n",
" <td>DIVERS MAQUILLAGE</td>\n",
" <td>maquillage</td>\n",
" <td>premiers soins</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2</td>\n",
" <td>FRA</td>\n",
" <td>2 EPONG.DEMAQUILLER N°42 SANOD</td>\n",
" <td>3701509580426</td>\n",
" <td>1964</td>\n",
" <td>DIVERS MAQUILLAGE</td>\n",
" <td>autres produits maquillage</td>\n",
" <td>hygiène féminine intime</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>3</td>\n",
" <td>FRA</td>\n",
" <td>200ML DIFF PFUM FIGUE CDP</td>\n",
" <td>3551780164033</td>\n",
" <td>1964</td>\n",
" <td>DIVERS MAQUILLAGE</td>\n",
" <td>maquillage</td>\n",
" <td>soins du corps</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>4</td>\n",
" <td>FRA</td>\n",
" <td>2PCS EPONGE DEMAQUILLANTE</td>\n",
" <td>3276558220253</td>\n",
" <td>1964</td>\n",
" <td>DIVERS MAQUILLAGE</td>\n",
" <td>autres produits maquillage</td>\n",
" <td>confiserie</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",
" </tr>\n",
" <tr>\n",
" <th>91</th>\n",
" <td>91</td>\n",
" <td>FRA</td>\n",
" <td>TAILLE CRAYON JUMBO EYE CARE</td>\n",
" <td>3532665009106</td>\n",
" <td>1964</td>\n",
" <td>DIVERS MAQUILLAGE</td>\n",
" <td>maquillage des yeux</td>\n",
" <td>maquillage</td>\n",
" </tr>\n",
" <tr>\n",
" <th>92</th>\n",
" <td>92</td>\n",
" <td>FRA</td>\n",
" <td>TROUSSE CM + GEL + SAVON C419</td>\n",
" <td>3433425316024</td>\n",
" <td>1964</td>\n",
" <td>DIVERS MAQUILLAGE</td>\n",
" <td>autres produits maquillage</td>\n",
" <td>bain douches savons</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93</th>\n",
" <td>93</td>\n",
" <td>FRA</td>\n",
" <td>TROUSSE CM BOI ROSE OSM C419</td>\n",
" <td>3433425315928</td>\n",
" <td>1964</td>\n",
" <td>DIVERS MAQUILLAGE</td>\n",
" <td>autres produits maquillage</td>\n",
" <td>parfums</td>\n",
" </tr>\n",
" <tr>\n",
" <th>94</th>\n",
" <td>94</td>\n",
" <td>FRA</td>\n",
" <td>TRSE CM+GELHYDRO+SAVON GR C419</td>\n",
" <td>3433425316079</td>\n",
" <td>1964</td>\n",
" <td>DIVERS MAQUILLAGE</td>\n",
" <td>autres produits maquillage</td>\n",
" <td>bain douches savons</td>\n",
" </tr>\n",
" <tr>\n",
" <th>95</th>\n",
" <td>95</td>\n",
" <td>FRA</td>\n",
" <td>ZAP FAP NACRE 106 BIO 3G</td>\n",
" <td>3700756601069</td>\n",
" <td>1964</td>\n",
" <td>DIVERS MAQUILLAGE</td>\n",
" <td>maquillage</td>\n",
" <td>maquillage</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>96 rows × 8 columns</p>\n",
"</div>"
],
"text/plain": [
" Unnamed: 0 COUNTRY_KEY ITEM_DESC BARCODE \\\n",
"0 0 FRA 150ML SECHE VERNIS VITRY 3538892526034 \n",
"1 1 FRA 15COM.SOMMEIL TRIPLE ACTI.PURE 3701056803443 \n",
"2 2 FRA 2 EPONG.DEMAQUILLER N°42 SANOD 3701509580426 \n",
"3 3 FRA 200ML DIFF PFUM FIGUE CDP 3551780164033 \n",
"4 4 FRA 2PCS EPONGE DEMAQUILLANTE 3276558220253 \n",
".. ... ... ... ... \n",
"91 91 FRA TAILLE CRAYON JUMBO EYE CARE 3532665009106 \n",
"92 92 FRA TROUSSE CM + GEL + SAVON C419 3433425316024 \n",
"93 93 FRA TROUSSE CM BOI ROSE OSM C419 3433425315928 \n",
"94 94 FRA TRSE CM+GELHYDRO+SAVON GR C419 3433425316079 \n",
"95 95 FRA ZAP FAP NACRE 106 BIO 3G 3700756601069 \n",
"\n",
" BEM_CLASS_KEY BEM_CLASS_DESC_FR prediction \\\n",
"0 1964 DIVERS MAQUILLAGE maquillage des ongles \n",
"1 1964 DIVERS MAQUILLAGE maquillage \n",
"2 1964 DIVERS MAQUILLAGE autres produits maquillage \n",
"3 1964 DIVERS MAQUILLAGE maquillage \n",
"4 1964 DIVERS MAQUILLAGE autres produits maquillage \n",
".. ... ... ... \n",
"91 1964 DIVERS MAQUILLAGE maquillage des yeux \n",
"92 1964 DIVERS MAQUILLAGE autres produits maquillage \n",
"93 1964 DIVERS MAQUILLAGE autres produits maquillage \n",
"94 1964 DIVERS MAQUILLAGE autres produits maquillage \n",
"95 1964 DIVERS MAQUILLAGE maquillage \n",
"\n",
" Prediction \n",
"0 confiserie \n",
"1 premiers soins \n",
"2 hygiène féminine intime \n",
"3 soins du corps \n",
"4 confiserie \n",
".. ... \n",
"91 maquillage \n",
"92 bain douches savons \n",
"93 parfums \n",
"94 bain douches savons \n",
"95 maquillage \n",
"\n",
"[96 rows x 8 columns]"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"DF"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"DF.to_csv(\"data_maquillage.csv\")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
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|