diff --git a/[lab-feature-engineering] Sara.ipynb b/[lab-feature-engineering] Sara.ipynb
new file mode 100644
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@@ -0,0 +1,468 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "223d1eaf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore')\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "b15ef0f9",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "data = pd.read_csv('learningSet.txt')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "24a2bbdf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Check for null values in the numerical columns.\n",
+    "# Use appropriate methods to clean the columns GEOCODE2, WEALTH1, ADI, DMA,and MSA.\n",
+    "# Use appropriate EDA technique where ever necessary."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "19df8494",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "categorical = data.select_dtypes(object)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "c9432d74",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "numerical = data.select_dtypes(include=np.number)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "6159f49a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "95412 481\n"
+     ]
+    }
+   ],
+   "source": [
+    "num_rows, num_columns = data.shape\n",
+    "print(num_rows, num_columns)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "7138c17d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "95412 74\n"
+     ]
+    }
+   ],
+   "source": [
+    "num_rows, num_columns = categorical.shape\n",
+    "print(num_rows, num_columns)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "68b33e4c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "95412 407\n"
+     ]
+    }
+   ],
+   "source": [
+    "num_rows, num_columns = numerical.shape\n",
+    "print(num_rows, num_columns)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "816f5ee7",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Null values by column:\n",
+      "ODATEDW         0\n",
+      "TCODE           0\n",
+      "DOB             0\n",
+      "AGE         23665\n",
+      "NUMCHLD     83026\n",
+      "            ...  \n",
+      "TARGET_B        0\n",
+      "TARGET_D        0\n",
+      "HPHONE_D        0\n",
+      "RFA_2F          0\n",
+      "CLUSTER2      132\n",
+      "Length: 407, dtype: int64\n"
+     ]
+    }
+   ],
+   "source": [
+    "null_values_by_column = numerical.isnull().sum()\n",
+    "\n",
+    "print(\"Null values by column:\")\n",
+    "print(null_values_by_column)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "b5d8313d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "A    34484\n",
+      "B    28505\n",
+      "D    16580\n",
+      "C    15524\n",
+      "       187\n",
+      "Name: GEOCODE2, dtype: int64\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "132"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "print(categorical['GEOCODE2'].value_counts())\n",
+    "categorical['GEOCODE2'].isna().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "847f5f21",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "9.0    7585\n",
+      "8.0    6793\n",
+      "7.0    6198\n",
+      "6.0    5825\n",
+      "5.0    5280\n",
+      "4.0    4810\n",
+      "3.0    4237\n",
+      "2.0    4085\n",
+      "1.0    3454\n",
+      "0.0    2413\n",
+      "Name: WEALTH1, dtype: int64\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "44732"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "print(data['WEALTH1'].value_counts())\n",
+    "data['WEALTH1'].isna().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "951ea68a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "13.0     7296\n",
+      "51.0     4622\n",
+      "65.0     3765\n",
+      "57.0     2836\n",
+      "105.0    2617\n",
+      "         ... \n",
+      "651.0       1\n",
+      "103.0       1\n",
+      "601.0       1\n",
+      "161.0       1\n",
+      "147.0       1\n",
+      "Name: ADI, Length: 204, dtype: int64\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "132"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "print(data['ADI'].value_counts())\n",
+    "data['ADI'].isna().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "95a21202",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "803.0    7296\n",
+      "602.0    4632\n",
+      "807.0    3765\n",
+      "505.0    2839\n",
+      "819.0    2588\n",
+      "         ... \n",
+      "569.0       1\n",
+      "554.0       1\n",
+      "584.0       1\n",
+      "552.0       1\n",
+      "516.0       1\n",
+      "Name: DMA, Length: 206, dtype: int64\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "132"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "print(data['DMA'].value_counts())\n",
+    "data['DMA'].isna().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "a7c3dc40",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.0       21333\n",
+      "4480.0     4606\n",
+      "1600.0     4059\n",
+      "2160.0     2586\n",
+      "520.0      1685\n",
+      "          ...  \n",
+      "9140.0        1\n",
+      "3200.0        1\n",
+      "9280.0        1\n",
+      "743.0         1\n",
+      "8480.0        1\n",
+      "Name: MSA, Length: 298, dtype: int64\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "132"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "print(data['MSA'].value_counts())\n",
+    "data['MSA'].isna().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "e683874f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "A    34803\n",
+       "B    28505\n",
+       "D    16580\n",
+       "C    15524\n",
+       "Name: GEOCODE2, dtype: int64"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "categorical['GEOCODE2'] = categorical['GEOCODE2'].fillna(data['GEOCODE2'].mode()[0])\n",
+    "categorical['GEOCODE2'].replace(\" \", categorical['GEOCODE2'].mode()[0], inplace=True)\n",
+    "categorical['GEOCODE2'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "c4d74296",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "numerical['WEALTH1'] = numerical['WEALTH1'].fillna(numerical['WEALTH1'].mode()[0])\n",
+    "numerical['WEALTH1'].isna().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "64e3896c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "numerical['ADI'] = numerical['ADI'].fillna(round(numerical['ADI'].mean()))\n",
+    "numerical['DMA'] = numerical['DMA'].fillna(round(numerical['DMA'].mean()))\n",
+    "numerical['MSA'] = numerical['MSA'].fillna(round(numerical['MSA'].mean()))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "b281a4b3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0\n",
+      "0\n",
+      "0\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(numerical['ADI'].isna().sum())\n",
+    "print(numerical['DMA'].isna().sum())\n",
+    "print(numerical['MSA'].isna().sum())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1c39c9b9",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d2fb7c69",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}