Mayank_Maiti_Lookalike.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "3980a245",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  CustomerID        CustomerName         Region  SignupDate\n",
      "0      C0001    Lawrence Carroll  South America  2022-07-10\n",
      "1      C0002      Elizabeth Lutz           Asia  2022-02-13\n",
      "2      C0003      Michael Rivera  South America  2024-03-07\n",
      "3      C0004  Kathleen Rodriguez  South America  2022-10-09\n",
      "4      C0005         Laura Weber           Asia  2022-08-15\n",
      "  ProductID              ProductName     Category   Price\n",
      "0      P001     ActiveWear Biography        Books  169.30\n",
      "1      P002    ActiveWear Smartwatch  Electronics  346.30\n",
      "2      P003  ComfortLiving Biography        Books   44.12\n",
      "3      P004            BookWorld Rug   Home Decor   95.69\n",
      "4      P005          TechPro T-Shirt     Clothing  429.31\n",
      "  TransactionID CustomerID ProductID TransactionDate  Quantity  TotalValue  \\\n",
      "0        T00001      C0199      P067      25-08-2024         1      300.68   \n",
      "1        T00112      C0146      P067      27-05-2024         1      300.68   \n",
      "2        T00166      C0127      P067      25-04-2024         1      300.68   \n",
      "3        T00272      C0087      P067      26-03-2024         2      601.36   \n",
      "4        T00363      C0070      P067      21-03-2024         3      902.04   \n",
      "\n",
      "    Price  \n",
      "0  300.68  \n",
      "1  300.68  \n",
      "2  300.68  \n",
      "3  300.68  \n",
      "4  300.68  \n"
     ]
    }
   ],
   "source": [
    "#Loading the Data sets\n",
    "import pandas as pd\n",
    "a = pd.read_csv(\"E:/DA_Projects/2/Customers.csv\")\n",
    "b = pd.read_csv(\"E:/DA_Projects/2/Products.csv\")\n",
    "c=pd.read_csv(\"E:/DA_Projects/2/Transactions.csv\")\n",
    "\n",
    "print(customers.head())\n",
    "print(products.head())\n",
    "print(transactions.head())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "6210594a",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Merging the Data \n",
    "merged_data = pd.merge(a, c, on='CustomerID')  \n",
    "merged_data.to_csv(\"E:/DA_Projects/2/merged_data.csv\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "952fda25",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Merging the Data \n",
    "d=\"E:/DA_Projects/2/merged_data.csv\"\n",
    "merged_data = pd.merge(a, c, on='CustomerID')  \n",
    "merged_data.to_csv(\"E:/DA_Projects/2/merged_data.csv\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "feaf6d65",
   "metadata": {},
   "outputs": [],
   "source": [
    "d=\"E:/DA_Projects/2/merged_data.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "d229a0bc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Basic Info:\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1000 entries, 0 to 999\n",
      "Data columns (total 13 columns):\n",
      " #   Column           Non-Null Count  Dtype  \n",
      "---  ------           --------------  -----  \n",
      " 0   TransactionID    1000 non-null   object \n",
      " 1   CustomerID       1000 non-null   object \n",
      " 2   ProductID        1000 non-null   object \n",
      " 3   TransactionDate  1000 non-null   object \n",
      " 4   Quantity         1000 non-null   int64  \n",
      " 5   TotalValue       1000 non-null   float64\n",
      " 6   Price_x          1000 non-null   float64\n",
      " 7   CustomerName     1000 non-null   object \n",
      " 8   Region           1000 non-null   object \n",
      " 9   SignupDate       1000 non-null   object \n",
      " 10  ProductName      1000 non-null   object \n",
      " 11  Category         1000 non-null   object \n",
      " 12  Price_y          1000 non-null   float64\n",
      "dtypes: float64(3), int64(1), object(9)\n",
      "memory usage: 101.7+ KB\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "file_path = d\n",
    "df = pd.read_csv(file_path)\n",
    "print(\"Basic Info:\")\n",
    "print(df.info())  \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "9db2c07d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from sklearn.preprocessing import LabelEncoder, StandardScaler\n",
    "from sklearn.neighbors import NearestNeighbors\n",
    "\n",
    "file_path = d  \n",
    "df = pd.read_csv(file_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "3a0a2177",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Creatin a KNN Model based on the Features given below by calculating the Euclidian distance\n",
    "features = [\"ProductID\", \"Quantity\", \"TotalValue\", \"Region\"]\n",
    "df_knn = df[[\"CustomerID\"] + features].copy()  \n",
    "\n",
    "label_encoders = {}\n",
    "for col in [\"ProductID\", \"Region\"]:\n",
    "    le = LabelEncoder()\n",
    "    df_knn[col] = le.fit_transform(df_knn[col])\n",
    "    label_encoders[col] = le \n",
    "\n",
    "scaler = StandardScaler()\n",
    "df_knn[[\"Quantity\", \"TotalValue\"]] = scaler.fit_transform(df_knn[[\"Quantity\", \"TotalValue\"]])\n",
    "\n",
    "knn = NearestNeighbors(n_neighbors=3, metric=\"euclidean\")\n",
    "knn.fit(df_knn.drop(columns=[\"CustomerID\"])) \n",
    "def find_similar_customers(new_data, knn_model, label_encoders, scaler, df_original):\n",
    "    for col in [\"ProductID\", \"Region\"]:\n",
    "        if new_data[col] in label_encoders[col].classes_:\n",
    "            new_data[col] = label_encoders[col].transform([new_data[col]])[0]\n",
    "        else:\n",
    "            print(f\"Warning: {col} value '{new_data[col]}' not in training data. Using unknown encoding.\")\n",
    "            new_data[col] = -1  \n",
    "\n",
    "    new_data_scaled = scaler.transform([[new_data[\"Quantity\"], new_data[\"TotalValue\"]]])\n",
    "\n",
    "    input_vector = [[new_data[\"ProductID\"], new_data_scaled[0][0], new_data_scaled[0][1], new_data[\"Region\"]]]\n",
    "    distances, indices = knn_model.kneighbors(input_vector)\n",
    "    similar_customers = df_original.iloc[indices[0]][[\"CustomerID\", \"ProductID\", \"Quantity\", \"TotalValue\", \"Region\"]].copy()\n",
    "    similar_customers[\"Similarity Score\"] = 1 / (1 + distances[0])  \n",
    "    return similar_customers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "e66d44df",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Enter ProductID: PO62\n",
      "Enter Quantity: 5\n",
      "Enter Total Value: 1870\n",
      "Enter Region: Asia\n",
      "Warning: ProductID value 'PO62' not in training data. Using unknown encoding.\n",
      "\n",
      "Top 3 Similar Customers:\n",
      "    CustomerID  ProductID  Quantity  TotalValue  Region  Similarity Score\n",
      "839      C0067          1  1.309264    1.410443       2          0.242399\n",
      "645      C0024          0  1.309264   -0.025960       2          0.226539\n",
      "651      C0017          0  0.414347   -0.369439       1          0.218182\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but StandardScaler was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "#Testing the model on Custom Transaction Data And finding the similarity Score\n",
    "product_id = input(\"Enter ProductID: \")\n",
    "quantity = float(input(\"Enter Quantity: \"))\n",
    "total_value = float(input(\"Enter Total Value: \"))\n",
    "region = input(\"Enter Region: \")\n",
    "\n",
    "new_customer = {\n",
    "    \"ProductID\": product_id,\n",
    "    \"Quantity\": quantity,\n",
    "    \"TotalValue\": total_value,\n",
    "    \"Region\": region\n",
    "}\n",
    "similar_customers = find_similar_customers(new_customer, knn, label_encoders, scaler, df_knn)\n",
    "print(\"\\nTop 3 Similar Customers:\")\n",
    "print(similar_customers)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "c735d7a1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lookalike.csv saved successfully at: E:/DA_Projects/2/Lookalike.csv\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n",
      "C:\\Users\\mayan\\anaconda3\\lib\\site-packages\\sklearn\\base.py:450: UserWarning: X does not have valid feature names, but NearestNeighbors was fitted with feature names\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "#Finding the similarity Model for a Given Set of Customers C0001 to C0020\n",
    "features = [\"ProductID\", \"Quantity\", \"TotalValue\", \"Region\"]\n",
    "df_knn = df[[\"CustomerID\"] + features].copy()  # Keep CustomerID for reference\n",
    "df_knn = df_knn[df_knn[\"CustomerID\"].between(\"C0001\", \"C0020\")].reset_index(drop=True)\n",
    "\n",
    "label_encoders = {}\n",
    "for col in [\"ProductID\", \"Region\"]:\n",
    "    le = LabelEncoder()\n",
    "    df_knn[col] = le.fit_transform(df_knn[col])\n",
    "    label_encoders[col] = le  \n",
    "\n",
    "scaler = StandardScaler()\n",
    "df_knn[[\"Quantity\", \"TotalValue\"]] = scaler.fit_transform(df_knn[[\"Quantity\", \"TotalValue\"]])\n",
    "knn = NearestNeighbors(n_neighbors=4, metric=\"euclidean\")  \n",
    "knn.fit(df_knn.drop(columns=[\"CustomerID\"]))\n",
    "\n",
    "lookalike_map = {}\n",
    "\n",
    "for idx, row in df_knn.iterrows():\n",
    "    customer_id = row[\"CustomerID\"]\n",
    "    customer_vector = row.drop(\"CustomerID\").values.reshape(1, -1)\n",
    "    distances, indices = knn.kneighbors(customer_vector)\n",
    "    similar_customers = []\n",
    "    for i in range(1, 4):  # Start from 1 to exclude self (0th index)\n",
    "        similar_customer_id = df_knn.iloc[indices[0][i]][\"CustomerID\"]\n",
    "        similarity_score = round(1 / (1 + distances[0][i]), 4)  # Convert distance to similarity score\n",
    "        similar_customers.append((similar_customer_id, similarity_score))\n",
    "    lookalike_map[customer_id] = similar_customers\n",
    "\n",
    "lookalike_df = pd.DataFrame({\"CustomerID\": lookalike_map.keys(), \"Lookalikes\": [str(v) for v in lookalike_map.values()]})\n",
    "lookalike_df[\"CustomerID_numeric\"] = lookalike_df[\"CustomerID\"].str.extract(\"(\\d+)\").astype(int)\n",
    "lookalike_df = lookalike_df.sort_values(by=\"CustomerID_numeric\").drop(columns=\"CustomerID_numeric\")\n",
    "\n",
    "# Save to file\n",
    "output_file = \"E:/DA_Projects/2/Lookalike.csv\"\n",
    "lookalike_df.to_csv(output_file, index=False)\n",
    "\n",
    "print(f\"Lookalike.csv saved successfully at: {output_file}\")\n"
   ]
  }
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