From beed5a3270c7eb5bd7ead6c914b0c4bd42ee7709 Mon Sep 17 00:00:00 2001 From: dienshyadav3169 Date: Sat, 25 Jul 2020 16:34:12 +0530 Subject: [PATCH] loan class --- .../Loan Prediction/Loan_prediction.ipynb | 973 ++++++++++++++++++ .../Loan Prediction/loan_predict.csv | 615 +++++++++++ 2 files changed, 1588 insertions(+) create mode 100644 Classification/Loan Prediction/Loan_prediction.ipynb create mode 100644 Classification/Loan Prediction/loan_predict.csv diff --git a/Classification/Loan Prediction/Loan_prediction.ipynb b/Classification/Loan Prediction/Loan_prediction.ipynb new file mode 100644 index 0000000..8ef4403 --- /dev/null +++ b/Classification/Loan Prediction/Loan_prediction.ipynb @@ -0,0 +1,973 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 173, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns; sns.set()\n", + "%matplotlib inline\n", + "\n", + "from warnings import simplefilter\n", + "simplefilter(action='ignore')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Importing DataSet" + ] + }, + { + "cell_type": "code", + "execution_count": 104, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.read_csv('loan_predict.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 105, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Loan_IDGenderMarriedDependentsEducationSelf_EmployedApplicantIncomeCoapplicantIncomeLoanAmountLoan_Amount_TermCredit_HistoryProperty_AreaLoan_Status
0LP001002MaleNo0GraduateNo58490.0NaN360.01.0UrbanY
1LP001003MaleYes1GraduateNo45831508.0128.0360.01.0RuralN
2LP001005MaleYes0GraduateYes30000.066.0360.01.0UrbanY
3LP001006MaleYes0Not GraduateNo25832358.0120.0360.01.0UrbanY
4LP001008MaleNo0GraduateNo60000.0141.0360.01.0UrbanY
..........................................
609LP002978FemaleNo0GraduateNo29000.071.0360.01.0RuralY
610LP002979MaleYes3+GraduateNo41060.040.0180.01.0RuralY
611LP002983MaleYes1GraduateNo8072240.0253.0360.01.0UrbanY
612LP002984MaleYes2GraduateNo75830.0187.0360.01.0UrbanY
613LP002990FemaleNo0GraduateYes45830.0133.0360.00.0SemiurbanN
\n", + "

614 rows × 13 columns

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" + ], + "text/plain": [ + " Loan_ID Gender Married Dependents Education Self_Employed \\\n", + "0 LP001002 Male No 0 Graduate No \n", + "1 LP001003 Male Yes 1 Graduate No \n", + "2 LP001005 Male Yes 0 Graduate Yes \n", + "3 LP001006 Male Yes 0 Not Graduate No \n", + "4 LP001008 Male No 0 Graduate No \n", + ".. ... ... ... ... ... ... \n", + "609 LP002978 Female No 0 Graduate No \n", + "610 LP002979 Male Yes 3+ Graduate No \n", + "611 LP002983 Male Yes 1 Graduate No \n", + "612 LP002984 Male Yes 2 Graduate No \n", + "613 LP002990 Female No 0 Graduate Yes \n", + "\n", + " ApplicantIncome CoapplicantIncome LoanAmount Loan_Amount_Term \\\n", + "0 5849 0.0 NaN 360.0 \n", + "1 4583 1508.0 128.0 360.0 \n", + "2 3000 0.0 66.0 360.0 \n", + "3 2583 2358.0 120.0 360.0 \n", + "4 6000 0.0 141.0 360.0 \n", + ".. ... ... ... ... \n", + "609 2900 0.0 71.0 360.0 \n", + "610 4106 0.0 40.0 180.0 \n", + "611 8072 240.0 253.0 360.0 \n", + "612 7583 0.0 187.0 360.0 \n", + "613 4583 0.0 133.0 360.0 \n", + "\n", + " Credit_History Property_Area Loan_Status \n", + "0 1.0 Urban Y \n", + "1 1.0 Rural N \n", + "2 1.0 Urban Y \n", + "3 1.0 Urban Y \n", + "4 1.0 Urban Y \n", + ".. ... ... ... \n", + "609 1.0 Rural Y \n", + "610 1.0 Rural Y \n", + "611 1.0 Urban Y \n", + "612 1.0 Urban Y \n", + "613 0.0 Semiurban N \n", + "\n", + "[614 rows x 13 columns]" + ] + }, + "execution_count": 105, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 106, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Loan_ID object\n", + "Gender object\n", + "Married object\n", + "Dependents object\n", + "Education object\n", + "Self_Employed object\n", + "ApplicantIncome int64\n", + "CoapplicantIncome float64\n", + "LoanAmount float64\n", + "Loan_Amount_Term float64\n", + "Credit_History float64\n", + "Property_Area object\n", + "Loan_Status object\n", + "dtype: object" + ] + }, + "execution_count": 106, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.dtypes" + ] + }, + { + "cell_type": "code", + "execution_count": 107, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Y 422\n", + "N 192\n", + "Name: Loan_Status, dtype: int64" + ] + }, + "execution_count": 107, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['Loan_Status'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 108, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(614, 13)" + ] + }, + "execution_count": 108, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 109, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Loan_ID 0\n", + "Gender 13\n", + "Married 3\n", + "Dependents 15\n", + "Education 0\n", + "Self_Employed 32\n", + "ApplicantIncome 0\n", + "CoapplicantIncome 0\n", + "LoanAmount 22\n", + "Loan_Amount_Term 14\n", + "Credit_History 50\n", + "Property_Area 0\n", + "Loan_Status 0\n", + "dtype: int64" + ] + }, + "execution_count": 109, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.isnull().sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 110, + "metadata": {}, + "outputs": [], + "source": [ + "df.dropna(axis=0, inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 111, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Semiurban 191\n", + "Urban 150\n", + "Rural 139\n", + "Name: Property_Area, dtype: int64" + ] + }, + "execution_count": 111, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['Property_Area'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 112, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\Dinesh\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:1: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame\n", + "\n", + "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " \"\"\"Entry point for launching an IPython kernel.\n" + ] + } + ], + "source": [ + "df['Dependents'][df['Dependents']=='3+']=4" + ] + }, + { + "cell_type": "code", + "execution_count": 128, + "metadata": {}, + "outputs": [], + "source": [ + "df.drop(['Loan_ID'], axis=1, inplace=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Encoding categorical data values (Transforming categorical data/ Strings to integers)" + ] + }, + { + "cell_type": "code", + "execution_count": 113, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.preprocessing import LabelEncoder\n", + "encoder = LabelEncoder()\n", + "encoder_col = ['Gender','Married','Education','Self_Employed','Loan_Status']\n", + "for col in encoder_col:\n", + " df[col] = encoder.fit_transform(df[col])" + ] + }, + { + "cell_type": "code", + "execution_count": 114, + "metadata": {}, + "outputs": [], + "source": [ + "df['Dependents'] = df['Dependents'].astype('int32')" + ] + }, + { + "cell_type": "code", + "execution_count": 124, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.concat([df,pd.get_dummies(df['Property_Area'])], axis=1).drop(['Property_Area'], axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 176, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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GenderMarriedDependentsEducationSelf_EmployedApplicantIncomeCoapplicantIncomeLoanAmountLoan_Amount_TermCredit_HistoryLoan_StatusSemiurbanUrban
11110045831508.0128.0360.01.0000
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" + ], + "text/plain": [ + " Gender Married Dependents Education Self_Employed ApplicantIncome \\\n", + "1 1 1 1 0 0 4583 \n", + "2 1 1 0 0 1 3000 \n", + "3 1 1 0 1 0 2583 \n", + "4 1 0 0 0 0 6000 \n", + "5 1 1 2 0 1 5417 \n", + "\n", + " CoapplicantIncome LoanAmount Loan_Amount_Term Credit_History \\\n", + "1 1508.0 128.0 360.0 1.0 \n", + "2 0.0 66.0 360.0 1.0 \n", + "3 2358.0 120.0 360.0 1.0 \n", + "4 0.0 141.0 360.0 1.0 \n", + "5 4196.0 267.0 360.0 1.0 \n", + "\n", + " Loan_Status Semiurban Urban \n", + "1 0 0 0 \n", + "2 1 0 1 \n", + "3 1 0 1 \n", + "4 1 0 1 \n", + "5 1 0 1 " + ] + }, + "execution_count": 176, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.drop(['Rural'],axis=1,inplace=True)\n", + "df.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Split the data into independent 'X' and dependent 'Y' variables" + ] + }, + { + "cell_type": "code", + "execution_count": 179, + "metadata": {}, + "outputs": [], + "source": [ + "X = df.drop(['Loan_Status'], axis=1).values\n", + "Y = df.iloc[:, 10:11].values" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Split the dataset into 75% Training set and 25% Testing set" + ] + }, + { + "cell_type": "code", + "execution_count": 180, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "\n", + "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, random_state=0, test_size=0.25)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Feature scalling" + ] + }, + { + "cell_type": "code", + "execution_count": 181, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.preprocessing import StandardScaler\n", + "\n", + "scaller = StandardScaler()\n", + "X_train = scaller.fit_transform(X_train)\n", + "X_test = scaller.transform(X_test)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

Classification

" + ] + }, + { + "cell_type": "code", + "execution_count": 182, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.model_selection import GridSearchCV\n", + "from sklearn.metrics import classification_report\n", + "from sklearn.metrics import accuracy_score\n", + "\n", + "def models(X_train,Y_tarin):\n", + " #Using Logistic Regression Algorithm to the Training Set\n", + " from sklearn.linear_model import LogisticRegression\n", + " log = LogisticRegression()\n", + " log.fit(X_train,Y_train)\n", + " parameters = [{'solver':['newton-cg', 'lbfgs', 'liblinear', 'sag', 'saga']}]\n", + " logGS = GridSearchCV(estimator = log, param_grid = parameters, scoring = 'accuracy', n_jobs = -1)\n", + " logGS.fit(X_train, Y_train)\n", + " \n", + " #Using KNeighborsClassifier Method of neighbors class to use Nearest Neighbor algorithm\n", + " from sklearn.neighbors import KNeighborsClassifier\n", + " knn = KNeighborsClassifier()\n", + " knn.fit(X_train, Y_train)\n", + " parameters = [{'n_neighbors':[1,2,3,4,5,6,7,8]}]\n", + " knnGS = GridSearchCV(estimator = knn, param_grid = parameters, scoring = 'accuracy', n_jobs = -1)\n", + " knnGS.fit(X_train, Y_train)\n", + " \n", + " #Using SVC method of svm class to use Support Vector Machine Algorithm\n", + " from sklearn.svm import SVC\n", + " svc = SVC()\n", + " svc.fit(X_train, Y_train)\n", + " parameters = [{'kernel':['linear', 'poly', 'rbf', 'sigmoid']}]\n", + " svcGS = GridSearchCV(estimator = svc, param_grid = parameters, scoring = 'accuracy', n_jobs = -1)\n", + " svcGS.fit(X_train, Y_train)\n", + " \n", + " #Using GaussianNB method of naïve_bayes class to use Naïve Bayes Algorithm\n", + " from sklearn.naive_bayes import GaussianNB\n", + " gauss = GaussianNB()\n", + " gauss.fit(X_train, Y_train)\n", + " \n", + " #Using DecisionTreeClassifier of tree class to use Decision Tree Algorithm\n", + " from sklearn.tree import DecisionTreeClassifier\n", + " tree = DecisionTreeClassifier()\n", + " tree.fit(X_train, Y_train)\n", + " parameters = [{'criterion':['entropy', 'gini']}]\n", + " treeGS = GridSearchCV(estimator = tree, param_grid = parameters, scoring = 'accuracy', n_jobs = -1)\n", + " treeGS.fit(X_train, Y_train)\n", + " \n", + " #Using RandomForestClassifier method of ensemble class to use Random Forest Classification algorithm\n", + " from sklearn.ensemble import RandomForestClassifier\n", + " forest = DecisionTreeClassifier()\n", + " forest.fit(X_train, Y_train)\n", + " parameters = [{'criterion':['entropy', 'gini']}]\n", + " forestGS = GridSearchCV(estimator = forest, param_grid = parameters, scoring = 'accuracy', n_jobs = -1)\n", + " forestGS.fit(X_train, Y_train)\n", + " \n", + " model_name = ['Logistic Regression','KNeighbors','SVM', 'GaussianNB', 'Decision Tree', 'Random Forest']\n", + " \n", + " return logGS, knnGS, svcGS, gauss, treeGS, forestGS, model_name" + ] + }, + { + "cell_type": "code", + "execution_count": 183, + "metadata": {}, + "outputs": [], + "source": [ + "model = models(X_train, Y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 184, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model : Logistic Regression\n", + " precision recall f1-score support\n", + "\n", + " 0 1.00 0.36 0.53 42\n", + " 1 0.74 1.00 0.85 78\n", + "\n", + " accuracy 0.78 120\n", + " macro avg 0.87 0.68 0.69 120\n", + "weighted avg 0.83 0.78 0.74 120\n", + "\n", + "------------------\n", + "0.775\n", + "-----------------------------------------------------\n", + "Model : KNeighbors\n", + " precision recall f1-score support\n", + "\n", + " 0 0.89 0.38 0.53 42\n", + " 1 0.75 0.97 0.84 78\n", + "\n", + " accuracy 0.77 120\n", + " macro avg 0.82 0.68 0.69 120\n", + "weighted avg 0.80 0.77 0.74 120\n", + "\n", + "------------------\n", + "0.7666666666666667\n", + "-----------------------------------------------------\n", + "Model : SVM\n", + " precision recall f1-score support\n", + "\n", + " 0 1.00 0.36 0.53 42\n", + " 1 0.74 1.00 0.85 78\n", + "\n", + " accuracy 0.78 120\n", + " macro avg 0.87 0.68 0.69 120\n", + "weighted avg 0.83 0.78 0.74 120\n", + "\n", + "------------------\n", + "0.775\n", + "-----------------------------------------------------\n", + "Model : GaussianNB\n", + " precision recall f1-score support\n", + "\n", + " 0 0.81 0.40 0.54 42\n", + " 1 0.75 0.95 0.84 78\n", + "\n", + " accuracy 0.76 120\n", + " macro avg 0.78 0.68 0.69 120\n", + "weighted avg 0.77 0.76 0.73 120\n", + "\n", + "------------------\n", + "0.7583333333333333\n", + "-----------------------------------------------------\n", + "Model : Decision Tree\n", + " precision recall f1-score support\n", + "\n", + " 0 0.54 0.48 0.51 42\n", + " 1 0.73 0.78 0.76 78\n", + "\n", + " accuracy 0.68 120\n", + " macro avg 0.64 0.63 0.63 120\n", + "weighted avg 0.67 0.68 0.67 120\n", + "\n", + "------------------\n", + "0.675\n", + "-----------------------------------------------------\n", + "Model : Random Forest\n", + " precision recall f1-score support\n", + "\n", + " 0 0.52 0.52 0.52 42\n", + " 1 0.74 0.74 0.74 78\n", + "\n", + " accuracy 0.67 120\n", + " macro avg 0.63 0.63 0.63 120\n", + "weighted avg 0.67 0.67 0.67 120\n", + "\n", + "------------------\n", + "0.6666666666666666\n", + "-----------------------------------------------------\n" + ] + } + ], + "source": [ + "for i in range(len(model)-1):\n", + " print('Model : ',model[6][i])\n", + " #Check precision, recall, f1-score\n", + " print(classification_report(Y_test, model[i].predict(X_test)))\n", + " print('------------------')\n", + " print( accuracy_score(Y_test, model[i].predict(X_test)))\n", + " print('-----------------------------------------------------')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As the dataset is imbalanced, there are more number loan approval than disapproved loans.
\n", + "i.e Model does not have sufficient data to learn from..\n", + "\n", + "DataFrame in Loan_Status\n", + "
\n", + "count 1 is more (332)
\n", + "count 0 is less (148)" + ] + }, + { + "cell_type": "code", + "execution_count": 185, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1 332\n", + "0 148\n", + "Name: Loan_Status, dtype: int64" + ] + }, + "execution_count": 185, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['Loan_Status'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "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": "3.7.4" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/Classification/Loan Prediction/loan_predict.csv b/Classification/Loan Prediction/loan_predict.csv new file mode 100644 index 0000000..f787350 --- /dev/null +++ b/Classification/Loan Prediction/loan_predict.csv @@ -0,0 +1,615 @@ +Loan_ID,Gender,Married,Dependents,Education,Self_Employed,ApplicantIncome,CoapplicantIncome,LoanAmount,Loan_Amount_Term,Credit_History,Property_Area,Loan_Status +LP001002,Male,No,0,Graduate,No,5849,0,,360,1,Urban,Y +LP001003,Male,Yes,1,Graduate,No,4583,1508,128,360,1,Rural,N +LP001005,Male,Yes,0,Graduate,Yes,3000,0,66,360,1,Urban,Y +LP001006,Male,Yes,0,Not Graduate,No,2583,2358,120,360,1,Urban,Y +LP001008,Male,No,0,Graduate,No,6000,0,141,360,1,Urban,Y +LP001011,Male,Yes,2,Graduate,Yes,5417,4196,267,360,1,Urban,Y +LP001013,Male,Yes,0,Not Graduate,No,2333,1516,95,360,1,Urban,Y +LP001014,Male,Yes,3+,Graduate,No,3036,2504,158,360,0,Semiurban,N +LP001018,Male,Yes,2,Graduate,No,4006,1526,168,360,1,Urban,Y +LP001020,Male,Yes,1,Graduate,No,12841,10968,349,360,1,Semiurban,N +LP001024,Male,Yes,2,Graduate,No,3200,700,70,360,1,Urban,Y +LP001027,Male,Yes,2,Graduate,,2500,1840,109,360,1,Urban,Y +LP001028,Male,Yes,2,Graduate,No,3073,8106,200,360,1,Urban,Y +LP001029,Male,No,0,Graduate,No,1853,2840,114,360,1,Rural,N +LP001030,Male,Yes,2,Graduate,No,1299,1086,17,120,1,Urban,Y +LP001032,Male,No,0,Graduate,No,4950,0,125,360,1,Urban,Y +LP001034,Male,No,1,Not Graduate,No,3596,0,100,240,,Urban,Y +LP001036,Female,No,0,Graduate,No,3510,0,76,360,0,Urban,N +LP001038,Male,Yes,0,Not Graduate,No,4887,0,133,360,1,Rural,N +LP001041,Male,Yes,0,Graduate,,2600,3500,115,,1,Urban,Y +LP001043,Male,Yes,0,Not Graduate,No,7660,0,104,360,0,Urban,N +LP001046,Male,Yes,1,Graduate,No,5955,5625,315,360,1,Urban,Y +LP001047,Male,Yes,0,Not Graduate,No,2600,1911,116,360,0,Semiurban,N +LP001050,,Yes,2,Not Graduate,No,3365,1917,112,360,0,Rural,N +LP001052,Male,Yes,1,Graduate,,3717,2925,151,360,,Semiurban,N +LP001066,Male,Yes,0,Graduate,Yes,9560,0,191,360,1,Semiurban,Y +LP001068,Male,Yes,0,Graduate,No,2799,2253,122,360,1,Semiurban,Y +LP001073,Male,Yes,2,Not Graduate,No,4226,1040,110,360,1,Urban,Y +LP001086,Male,No,0,Not Graduate,No,1442,0,35,360,1,Urban,N +LP001087,Female,No,2,Graduate,,3750,2083,120,360,1,Semiurban,Y +LP001091,Male,Yes,1,Graduate,,4166,3369,201,360,,Urban,N +LP001095,Male,No,0,Graduate,No,3167,0,74,360,1,Urban,N +LP001097,Male,No,1,Graduate,Yes,4692,0,106,360,1,Rural,N +LP001098,Male,Yes,0,Graduate,No,3500,1667,114,360,1,Semiurban,Y +LP001100,Male,No,3+,Graduate,No,12500,3000,320,360,1,Rural,N +LP001106,Male,Yes,0,Graduate,No,2275,2067,,360,1,Urban,Y +LP001109,Male,Yes,0,Graduate,No,1828,1330,100,,0,Urban,N +LP001112,Female,Yes,0,Graduate,No,3667,1459,144,360,1,Semiurban,Y +LP001114,Male,No,0,Graduate,No,4166,7210,184,360,1,Urban,Y +LP001116,Male,No,0,Not Graduate,No,3748,1668,110,360,1,Semiurban,Y +LP001119,Male,No,0,Graduate,No,3600,0,80,360,1,Urban,N +LP001120,Male,No,0,Graduate,No,1800,1213,47,360,1,Urban,Y +LP001123,Male,Yes,0,Graduate,No,2400,0,75,360,,Urban,Y +LP001131,Male,Yes,0,Graduate,No,3941,2336,134,360,1,Semiurban,Y +LP001136,Male,Yes,0,Not Graduate,Yes,4695,0,96,,1,Urban,Y +LP001137,Female,No,0,Graduate,No,3410,0,88,,1,Urban,Y +LP001138,Male,Yes,1,Graduate,No,5649,0,44,360,1,Urban,Y +LP001144,Male,Yes,0,Graduate,No,5821,0,144,360,1,Urban,Y +LP001146,Female,Yes,0,Graduate,No,2645,3440,120,360,0,Urban,N +LP001151,Female,No,0,Graduate,No,4000,2275,144,360,1,Semiurban,Y +LP001155,Female,Yes,0,Not Graduate,No,1928,1644,100,360,1,Semiurban,Y +LP001157,Female,No,0,Graduate,No,3086,0,120,360,1,Semiurban,Y +LP001164,Female,No,0,Graduate,No,4230,0,112,360,1,Semiurban,N +LP001179,Male,Yes,2,Graduate,No,4616,0,134,360,1,Urban,N +LP001186,Female,Yes,1,Graduate,Yes,11500,0,286,360,0,Urban,N +LP001194,Male,Yes,2,Graduate,No,2708,1167,97,360,1,Semiurban,Y +LP001195,Male,Yes,0,Graduate,No,2132,1591,96,360,1,Semiurban,Y +LP001197,Male,Yes,0,Graduate,No,3366,2200,135,360,1,Rural,N +LP001198,Male,Yes,1,Graduate,No,8080,2250,180,360,1,Urban,Y +LP001199,Male,Yes,2,Not Graduate,No,3357,2859,144,360,1,Urban,Y +LP001205,Male,Yes,0,Graduate,No,2500,3796,120,360,1,Urban,Y +LP001206,Male,Yes,3+,Graduate,No,3029,0,99,360,1,Urban,Y +LP001207,Male,Yes,0,Not Graduate,Yes,2609,3449,165,180,0,Rural,N +LP001213,Male,Yes,1,Graduate,No,4945,0,,360,0,Rural,N +LP001222,Female,No,0,Graduate,No,4166,0,116,360,0,Semiurban,N +LP001225,Male,Yes,0,Graduate,No,5726,4595,258,360,1,Semiurban,N +LP001228,Male,No,0,Not Graduate,No,3200,2254,126,180,0,Urban,N +LP001233,Male,Yes,1,Graduate,No,10750,0,312,360,1,Urban,Y +LP001238,Male,Yes,3+,Not Graduate,Yes,7100,0,125,60,1,Urban,Y +LP001241,Female,No,0,Graduate,No,4300,0,136,360,0,Semiurban,N +LP001243,Male,Yes,0,Graduate,No,3208,3066,172,360,1,Urban,Y +LP001245,Male,Yes,2,Not Graduate,Yes,1875,1875,97,360,1,Semiurban,Y +LP001248,Male,No,0,Graduate,No,3500,0,81,300,1,Semiurban,Y +LP001250,Male,Yes,3+,Not Graduate,No,4755,0,95,,0,Semiurban,N +LP001253,Male,Yes,3+,Graduate,Yes,5266,1774,187,360,1,Semiurban,Y +LP001255,Male,No,0,Graduate,No,3750,0,113,480,1,Urban,N +LP001256,Male,No,0,Graduate,No,3750,4750,176,360,1,Urban,N +LP001259,Male,Yes,1,Graduate,Yes,1000,3022,110,360,1,Urban,N +LP001263,Male,Yes,3+,Graduate,No,3167,4000,180,300,0,Semiurban,N +LP001264,Male,Yes,3+,Not Graduate,Yes,3333,2166,130,360,,Semiurban,Y +LP001265,Female,No,0,Graduate,No,3846,0,111,360,1,Semiurban,Y +LP001266,Male,Yes,1,Graduate,Yes,2395,0,,360,1,Semiurban,Y +LP001267,Female,Yes,2,Graduate,No,1378,1881,167,360,1,Urban,N +LP001273,Male,Yes,0,Graduate,No,6000,2250,265,360,,Semiurban,N +LP001275,Male,Yes,1,Graduate,No,3988,0,50,240,1,Urban,Y +LP001279,Male,No,0,Graduate,No,2366,2531,136,360,1,Semiurban,Y +LP001280,Male,Yes,2,Not Graduate,No,3333,2000,99,360,,Semiurban,Y +LP001282,Male,Yes,0,Graduate,No,2500,2118,104,360,1,Semiurban,Y +LP001289,Male,No,0,Graduate,No,8566,0,210,360,1,Urban,Y +LP001310,Male,Yes,0,Graduate,No,5695,4167,175,360,1,Semiurban,Y +LP001316,Male,Yes,0,Graduate,No,2958,2900,131,360,1,Semiurban,Y +LP001318,Male,Yes,2,Graduate,No,6250,5654,188,180,1,Semiurban,Y +LP001319,Male,Yes,2,Not Graduate,No,3273,1820,81,360,1,Urban,Y +LP001322,Male,No,0,Graduate,No,4133,0,122,360,1,Semiurban,Y +LP001325,Male,No,0,Not Graduate,No,3620,0,25,120,1,Semiurban,Y +LP001326,Male,No,0,Graduate,,6782,0,,360,,Urban,N +LP001327,Female,Yes,0,Graduate,No,2484,2302,137,360,1,Semiurban,Y +LP001333,Male,Yes,0,Graduate,No,1977,997,50,360,1,Semiurban,Y +LP001334,Male,Yes,0,Not Graduate,No,4188,0,115,180,1,Semiurban,Y +LP001343,Male,Yes,0,Graduate,No,1759,3541,131,360,1,Semiurban,Y +LP001345,Male,Yes,2,Not Graduate,No,4288,3263,133,180,1,Urban,Y +LP001349,Male,No,0,Graduate,No,4843,3806,151,360,1,Semiurban,Y +LP001350,Male,Yes,,Graduate,No,13650,0,,360,1,Urban,Y +LP001356,Male,Yes,0,Graduate,No,4652,3583,,360,1,Semiurban,Y +LP001357,Male,,,Graduate,No,3816,754,160,360,1,Urban,Y +LP001367,Male,Yes,1,Graduate,No,3052,1030,100,360,1,Urban,Y +LP001369,Male,Yes,2,Graduate,No,11417,1126,225,360,1,Urban,Y +LP001370,Male,No,0,Not Graduate,,7333,0,120,360,1,Rural,N +LP001379,Male,Yes,2,Graduate,No,3800,3600,216,360,0,Urban,N +LP001384,Male,Yes,3+,Not Graduate,No,2071,754,94,480,1,Semiurban,Y +LP001385,Male,No,0,Graduate,No,5316,0,136,360,1,Urban,Y +LP001387,Female,Yes,0,Graduate,,2929,2333,139,360,1,Semiurban,Y +LP001391,Male,Yes,0,Not Graduate,No,3572,4114,152,,0,Rural,N +LP001392,Female,No,1,Graduate,Yes,7451,0,,360,1,Semiurban,Y +LP001398,Male,No,0,Graduate,,5050,0,118,360,1,Semiurban,Y +LP001401,Male,Yes,1,Graduate,No,14583,0,185,180,1,Rural,Y +LP001404,Female,Yes,0,Graduate,No,3167,2283,154,360,1,Semiurban,Y +LP001405,Male,Yes,1,Graduate,No,2214,1398,85,360,,Urban,Y +LP001421,Male,Yes,0,Graduate,No,5568,2142,175,360,1,Rural,N +LP001422,Female,No,0,Graduate,No,10408,0,259,360,1,Urban,Y +LP001426,Male,Yes,,Graduate,No,5667,2667,180,360,1,Rural,Y +LP001430,Female,No,0,Graduate,No,4166,0,44,360,1,Semiurban,Y +LP001431,Female,No,0,Graduate,No,2137,8980,137,360,0,Semiurban,Y +LP001432,Male,Yes,2,Graduate,No,2957,0,81,360,1,Semiurban,Y +LP001439,Male,Yes,0,Not Graduate,No,4300,2014,194,360,1,Rural,Y +LP001443,Female,No,0,Graduate,No,3692,0,93,360,,Rural,Y +LP001448,,Yes,3+,Graduate,No,23803,0,370,360,1,Rural,Y +LP001449,Male,No,0,Graduate,No,3865,1640,,360,1,Rural,Y +LP001451,Male,Yes,1,Graduate,Yes,10513,3850,160,180,0,Urban,N +LP001465,Male,Yes,0,Graduate,No,6080,2569,182,360,,Rural,N +LP001469,Male,No,0,Graduate,Yes,20166,0,650,480,,Urban,Y +LP001473,Male,No,0,Graduate,No,2014,1929,74,360,1,Urban,Y +LP001478,Male,No,0,Graduate,No,2718,0,70,360,1,Semiurban,Y +LP001482,Male,Yes,0,Graduate,Yes,3459,0,25,120,1,Semiurban,Y +LP001487,Male,No,0,Graduate,No,4895,0,102,360,1,Semiurban,Y +LP001488,Male,Yes,3+,Graduate,No,4000,7750,290,360,1,Semiurban,N +LP001489,Female,Yes,0,Graduate,No,4583,0,84,360,1,Rural,N +LP001491,Male,Yes,2,Graduate,Yes,3316,3500,88,360,1,Urban,Y +LP001492,Male,No,0,Graduate,No,14999,0,242,360,0,Semiurban,N +LP001493,Male,Yes,2,Not Graduate,No,4200,1430,129,360,1,Rural,N +LP001497,Male,Yes,2,Graduate,No,5042,2083,185,360,1,Rural,N +LP001498,Male,No,0,Graduate,No,5417,0,168,360,1,Urban,Y +LP001504,Male,No,0,Graduate,Yes,6950,0,175,180,1,Semiurban,Y +LP001507,Male,Yes,0,Graduate,No,2698,2034,122,360,1,Semiurban,Y +LP001508,Male,Yes,2,Graduate,No,11757,0,187,180,1,Urban,Y +LP001514,Female,Yes,0,Graduate,No,2330,4486,100,360,1,Semiurban,Y +LP001516,Female,Yes,2,Graduate,No,14866,0,70,360,1,Urban,Y +LP001518,Male,Yes,1,Graduate,No,1538,1425,30,360,1,Urban,Y +LP001519,Female,No,0,Graduate,No,10000,1666,225,360,1,Rural,N +LP001520,Male,Yes,0,Graduate,No,4860,830,125,360,1,Semiurban,Y +LP001528,Male,No,0,Graduate,No,6277,0,118,360,0,Rural,N +LP001529,Male,Yes,0,Graduate,Yes,2577,3750,152,360,1,Rural,Y +LP001531,Male,No,0,Graduate,No,9166,0,244,360,1,Urban,N +LP001532,Male,Yes,2,Not Graduate,No,2281,0,113,360,1,Rural,N +LP001535,Male,No,0,Graduate,No,3254,0,50,360,1,Urban,Y +LP001536,Male,Yes,3+,Graduate,No,39999,0,600,180,0,Semiurban,Y +LP001541,Male,Yes,1,Graduate,No,6000,0,160,360,,Rural,Y +LP001543,Male,Yes,1,Graduate,No,9538,0,187,360,1,Urban,Y +LP001546,Male,No,0,Graduate,,2980,2083,120,360,1,Rural,Y +LP001552,Male,Yes,0,Graduate,No,4583,5625,255,360,1,Semiurban,Y +LP001560,Male,Yes,0,Not Graduate,No,1863,1041,98,360,1,Semiurban,Y +LP001562,Male,Yes,0,Graduate,No,7933,0,275,360,1,Urban,N +LP001565,Male,Yes,1,Graduate,No,3089,1280,121,360,0,Semiurban,N +LP001570,Male,Yes,2,Graduate,No,4167,1447,158,360,1,Rural,Y +LP001572,Male,Yes,0,Graduate,No,9323,0,75,180,1,Urban,Y +LP001574,Male,Yes,0,Graduate,No,3707,3166,182,,1,Rural,Y +LP001577,Female,Yes,0,Graduate,No,4583,0,112,360,1,Rural,N +LP001578,Male,Yes,0,Graduate,No,2439,3333,129,360,1,Rural,Y +LP001579,Male,No,0,Graduate,No,2237,0,63,480,0,Semiurban,N +LP001580,Male,Yes,2,Graduate,No,8000,0,200,360,1,Semiurban,Y +LP001581,Male,Yes,0,Not Graduate,,1820,1769,95,360,1,Rural,Y +LP001585,,Yes,3+,Graduate,No,51763,0,700,300,1,Urban,Y +LP001586,Male,Yes,3+,Not Graduate,No,3522,0,81,180,1,Rural,N +LP001594,Male,Yes,0,Graduate,No,5708,5625,187,360,1,Semiurban,Y +LP001603,Male,Yes,0,Not Graduate,Yes,4344,736,87,360,1,Semiurban,N +LP001606,Male,Yes,0,Graduate,No,3497,1964,116,360,1,Rural,Y +LP001608,Male,Yes,2,Graduate,No,2045,1619,101,360,1,Rural,Y +LP001610,Male,Yes,3+,Graduate,No,5516,11300,495,360,0,Semiurban,N +LP001616,Male,Yes,1,Graduate,No,3750,0,116,360,1,Semiurban,Y +LP001630,Male,No,0,Not Graduate,No,2333,1451,102,480,0,Urban,N +LP001633,Male,Yes,1,Graduate,No,6400,7250,180,360,0,Urban,N +LP001634,Male,No,0,Graduate,No,1916,5063,67,360,,Rural,N +LP001636,Male,Yes,0,Graduate,No,4600,0,73,180,1,Semiurban,Y +LP001637,Male,Yes,1,Graduate,No,33846,0,260,360,1,Semiurban,N +LP001639,Female,Yes,0,Graduate,No,3625,0,108,360,1,Semiurban,Y +LP001640,Male,Yes,0,Graduate,Yes,39147,4750,120,360,1,Semiurban,Y +LP001641,Male,Yes,1,Graduate,Yes,2178,0,66,300,0,Rural,N +LP001643,Male,Yes,0,Graduate,No,2383,2138,58,360,,Rural,Y +LP001644,,Yes,0,Graduate,Yes,674,5296,168,360,1,Rural,Y +LP001647,Male,Yes,0,Graduate,No,9328,0,188,180,1,Rural,Y +LP001653,Male,No,0,Not Graduate,No,4885,0,48,360,1,Rural,Y +LP001656,Male,No,0,Graduate,No,12000,0,164,360,1,Semiurban,N +LP001657,Male,Yes,0,Not Graduate,No,6033,0,160,360,1,Urban,N +LP001658,Male,No,0,Graduate,No,3858,0,76,360,1,Semiurban,Y +LP001664,Male,No,0,Graduate,No,4191,0,120,360,1,Rural,Y +LP001665,Male,Yes,1,Graduate,No,3125,2583,170,360,1,Semiurban,N +LP001666,Male,No,0,Graduate,No,8333,3750,187,360,1,Rural,Y +LP001669,Female,No,0,Not Graduate,No,1907,2365,120,,1,Urban,Y +LP001671,Female,Yes,0,Graduate,No,3416,2816,113,360,,Semiurban,Y +LP001673,Male,No,0,Graduate,Yes,11000,0,83,360,1,Urban,N +LP001674,Male,Yes,1,Not Graduate,No,2600,2500,90,360,1,Semiurban,Y +LP001677,Male,No,2,Graduate,No,4923,0,166,360,0,Semiurban,Y +LP001682,Male,Yes,3+,Not Graduate,No,3992,0,,180,1,Urban,N +LP001688,Male,Yes,1,Not Graduate,No,3500,1083,135,360,1,Urban,Y +LP001691,Male,Yes,2,Not Graduate,No,3917,0,124,360,1,Semiurban,Y +LP001692,Female,No,0,Not Graduate,No,4408,0,120,360,1,Semiurban,Y +LP001693,Female,No,0,Graduate,No,3244,0,80,360,1,Urban,Y +LP001698,Male,No,0,Not Graduate,No,3975,2531,55,360,1,Rural,Y +LP001699,Male,No,0,Graduate,No,2479,0,59,360,1,Urban,Y +LP001702,Male,No,0,Graduate,No,3418,0,127,360,1,Semiurban,N +LP001708,Female,No,0,Graduate,No,10000,0,214,360,1,Semiurban,N +LP001711,Male,Yes,3+,Graduate,No,3430,1250,128,360,0,Semiurban,N +LP001713,Male,Yes,1,Graduate,Yes,7787,0,240,360,1,Urban,Y +LP001715,Male,Yes,3+,Not Graduate,Yes,5703,0,130,360,1,Rural,Y +LP001716,Male,Yes,0,Graduate,No,3173,3021,137,360,1,Urban,Y +LP001720,Male,Yes,3+,Not Graduate,No,3850,983,100,360,1,Semiurban,Y +LP001722,Male,Yes,0,Graduate,No,150,1800,135,360,1,Rural,N +LP001726,Male,Yes,0,Graduate,No,3727,1775,131,360,1,Semiurban,Y +LP001732,Male,Yes,2,Graduate,,5000,0,72,360,0,Semiurban,N +LP001734,Female,Yes,2,Graduate,No,4283,2383,127,360,,Semiurban,Y +LP001736,Male,Yes,0,Graduate,No,2221,0,60,360,0,Urban,N +LP001743,Male,Yes,2,Graduate,No,4009,1717,116,360,1,Semiurban,Y +LP001744,Male,No,0,Graduate,No,2971,2791,144,360,1,Semiurban,Y +LP001749,Male,Yes,0,Graduate,No,7578,1010,175,,1,Semiurban,Y +LP001750,Male,Yes,0,Graduate,No,6250,0,128,360,1,Semiurban,Y +LP001751,Male,Yes,0,Graduate,No,3250,0,170,360,1,Rural,N +LP001754,Male,Yes,,Not Graduate,Yes,4735,0,138,360,1,Urban,N +LP001758,Male,Yes,2,Graduate,No,6250,1695,210,360,1,Semiurban,Y +LP001760,Male,,,Graduate,No,4758,0,158,480,1,Semiurban,Y +LP001761,Male,No,0,Graduate,Yes,6400,0,200,360,1,Rural,Y +LP001765,Male,Yes,1,Graduate,No,2491,2054,104,360,1,Semiurban,Y +LP001768,Male,Yes,0,Graduate,,3716,0,42,180,1,Rural,Y +LP001770,Male,No,0,Not Graduate,No,3189,2598,120,,1,Rural,Y +LP001776,Female,No,0,Graduate,No,8333,0,280,360,1,Semiurban,Y +LP001778,Male,Yes,1,Graduate,No,3155,1779,140,360,1,Semiurban,Y +LP001784,Male,Yes,1,Graduate,No,5500,1260,170,360,1,Rural,Y +LP001786,Male,Yes,0,Graduate,,5746,0,255,360,,Urban,N +LP001788,Female,No,0,Graduate,Yes,3463,0,122,360,,Urban,Y +LP001790,Female,No,1,Graduate,No,3812,0,112,360,1,Rural,Y +LP001792,Male,Yes,1,Graduate,No,3315,0,96,360,1,Semiurban,Y +LP001798,Male,Yes,2,Graduate,No,5819,5000,120,360,1,Rural,Y +LP001800,Male,Yes,1,Not Graduate,No,2510,1983,140,180,1,Urban,N +LP001806,Male,No,0,Graduate,No,2965,5701,155,60,1,Urban,Y +LP001807,Male,Yes,2,Graduate,Yes,6250,1300,108,360,1,Rural,Y +LP001811,Male,Yes,0,Not Graduate,No,3406,4417,123,360,1,Semiurban,Y +LP001813,Male,No,0,Graduate,Yes,6050,4333,120,180,1,Urban,N +LP001814,Male,Yes,2,Graduate,No,9703,0,112,360,1,Urban,Y +LP001819,Male,Yes,1,Not Graduate,No,6608,0,137,180,1,Urban,Y +LP001824,Male,Yes,1,Graduate,No,2882,1843,123,480,1,Semiurban,Y +LP001825,Male,Yes,0,Graduate,No,1809,1868,90,360,1,Urban,Y +LP001835,Male,Yes,0,Not Graduate,No,1668,3890,201,360,0,Semiurban,N +LP001836,Female,No,2,Graduate,No,3427,0,138,360,1,Urban,N +LP001841,Male,No,0,Not Graduate,Yes,2583,2167,104,360,1,Rural,Y +LP001843,Male,Yes,1,Not Graduate,No,2661,7101,279,180,1,Semiurban,Y +LP001844,Male,No,0,Graduate,Yes,16250,0,192,360,0,Urban,N +LP001846,Female,No,3+,Graduate,No,3083,0,255,360,1,Rural,Y +LP001849,Male,No,0,Not Graduate,No,6045,0,115,360,0,Rural,N +LP001854,Male,Yes,3+,Graduate,No,5250,0,94,360,1,Urban,N +LP001859,Male,Yes,0,Graduate,No,14683,2100,304,360,1,Rural,N +LP001864,Male,Yes,3+,Not Graduate,No,4931,0,128,360,,Semiurban,N +LP001865,Male,Yes,1,Graduate,No,6083,4250,330,360,,Urban,Y +LP001868,Male,No,0,Graduate,No,2060,2209,134,360,1,Semiurban,Y +LP001870,Female,No,1,Graduate,No,3481,0,155,36,1,Semiurban,N +LP001871,Female,No,0,Graduate,No,7200,0,120,360,1,Rural,Y +LP001872,Male,No,0,Graduate,Yes,5166,0,128,360,1,Semiurban,Y +LP001875,Male,No,0,Graduate,No,4095,3447,151,360,1,Rural,Y +LP001877,Male,Yes,2,Graduate,No,4708,1387,150,360,1,Semiurban,Y +LP001882,Male,Yes,3+,Graduate,No,4333,1811,160,360,0,Urban,Y +LP001883,Female,No,0,Graduate,,3418,0,135,360,1,Rural,N +LP001884,Female,No,1,Graduate,No,2876,1560,90,360,1,Urban,Y +LP001888,Female,No,0,Graduate,No,3237,0,30,360,1,Urban,Y +LP001891,Male,Yes,0,Graduate,No,11146,0,136,360,1,Urban,Y +LP001892,Male,No,0,Graduate,No,2833,1857,126,360,1,Rural,Y +LP001894,Male,Yes,0,Graduate,No,2620,2223,150,360,1,Semiurban,Y +LP001896,Male,Yes,2,Graduate,No,3900,0,90,360,1,Semiurban,Y +LP001900,Male,Yes,1,Graduate,No,2750,1842,115,360,1,Semiurban,Y +LP001903,Male,Yes,0,Graduate,No,3993,3274,207,360,1,Semiurban,Y +LP001904,Male,Yes,0,Graduate,No,3103,1300,80,360,1,Urban,Y +LP001907,Male,Yes,0,Graduate,No,14583,0,436,360,1,Semiurban,Y +LP001908,Female,Yes,0,Not Graduate,No,4100,0,124,360,,Rural,Y +LP001910,Male,No,1,Not Graduate,Yes,4053,2426,158,360,0,Urban,N +LP001914,Male,Yes,0,Graduate,No,3927,800,112,360,1,Semiurban,Y +LP001915,Male,Yes,2,Graduate,No,2301,985.7999878,78,180,1,Urban,Y +LP001917,Female,No,0,Graduate,No,1811,1666,54,360,1,Urban,Y +LP001922,Male,Yes,0,Graduate,No,20667,0,,360,1,Rural,N +LP001924,Male,No,0,Graduate,No,3158,3053,89,360,1,Rural,Y +LP001925,Female,No,0,Graduate,Yes,2600,1717,99,300,1,Semiurban,N +LP001926,Male,Yes,0,Graduate,No,3704,2000,120,360,1,Rural,Y +LP001931,Female,No,0,Graduate,No,4124,0,115,360,1,Semiurban,Y +LP001935,Male,No,0,Graduate,No,9508,0,187,360,1,Rural,Y +LP001936,Male,Yes,0,Graduate,No,3075,2416,139,360,1,Rural,Y +LP001938,Male,Yes,2,Graduate,No,4400,0,127,360,0,Semiurban,N +LP001940,Male,Yes,2,Graduate,No,3153,1560,134,360,1,Urban,Y +LP001945,Female,No,,Graduate,No,5417,0,143,480,0,Urban,N +LP001947,Male,Yes,0,Graduate,No,2383,3334,172,360,1,Semiurban,Y +LP001949,Male,Yes,3+,Graduate,,4416,1250,110,360,1,Urban,Y +LP001953,Male,Yes,1,Graduate,No,6875,0,200,360,1,Semiurban,Y +LP001954,Female,Yes,1,Graduate,No,4666,0,135,360,1,Urban,Y +LP001955,Female,No,0,Graduate,No,5000,2541,151,480,1,Rural,N +LP001963,Male,Yes,1,Graduate,No,2014,2925,113,360,1,Urban,N +LP001964,Male,Yes,0,Not Graduate,No,1800,2934,93,360,0,Urban,N +LP001972,Male,Yes,,Not Graduate,No,2875,1750,105,360,1,Semiurban,Y +LP001974,Female,No,0,Graduate,No,5000,0,132,360,1,Rural,Y +LP001977,Male,Yes,1,Graduate,No,1625,1803,96,360,1,Urban,Y +LP001978,Male,No,0,Graduate,No,4000,2500,140,360,1,Rural,Y +LP001990,Male,No,0,Not Graduate,No,2000,0,,360,1,Urban,N +LP001993,Female,No,0,Graduate,No,3762,1666,135,360,1,Rural,Y +LP001994,Female,No,0,Graduate,No,2400,1863,104,360,0,Urban,N +LP001996,Male,No,0,Graduate,No,20233,0,480,360,1,Rural,N +LP001998,Male,Yes,2,Not Graduate,No,7667,0,185,360,,Rural,Y +LP002002,Female,No,0,Graduate,No,2917,0,84,360,1,Semiurban,Y +LP002004,Male,No,0,Not Graduate,No,2927,2405,111,360,1,Semiurban,Y +LP002006,Female,No,0,Graduate,No,2507,0,56,360,1,Rural,Y +LP002008,Male,Yes,2,Graduate,Yes,5746,0,144,84,,Rural,Y +LP002024,,Yes,0,Graduate,No,2473,1843,159,360,1,Rural,N +LP002031,Male,Yes,1,Not Graduate,No,3399,1640,111,180,1,Urban,Y +LP002035,Male,Yes,2,Graduate,No,3717,0,120,360,1,Semiurban,Y +LP002036,Male,Yes,0,Graduate,No,2058,2134,88,360,,Urban,Y +LP002043,Female,No,1,Graduate,No,3541,0,112,360,,Semiurban,Y +LP002050,Male,Yes,1,Graduate,Yes,10000,0,155,360,1,Rural,N +LP002051,Male,Yes,0,Graduate,No,2400,2167,115,360,1,Semiurban,Y +LP002053,Male,Yes,3+,Graduate,No,4342,189,124,360,1,Semiurban,Y +LP002054,Male,Yes,2,Not Graduate,No,3601,1590,,360,1,Rural,Y +LP002055,Female,No,0,Graduate,No,3166,2985,132,360,,Rural,Y +LP002065,Male,Yes,3+,Graduate,No,15000,0,300,360,1,Rural,Y +LP002067,Male,Yes,1,Graduate,Yes,8666,4983,376,360,0,Rural,N +LP002068,Male,No,0,Graduate,No,4917,0,130,360,0,Rural,Y +LP002082,Male,Yes,0,Graduate,Yes,5818,2160,184,360,1,Semiurban,Y +LP002086,Female,Yes,0,Graduate,No,4333,2451,110,360,1,Urban,N +LP002087,Female,No,0,Graduate,No,2500,0,67,360,1,Urban,Y +LP002097,Male,No,1,Graduate,No,4384,1793,117,360,1,Urban,Y +LP002098,Male,No,0,Graduate,No,2935,0,98,360,1,Semiurban,Y +LP002100,Male,No,,Graduate,No,2833,0,71,360,1,Urban,Y +LP002101,Male,Yes,0,Graduate,,63337,0,490,180,1,Urban,Y +LP002103,,Yes,1,Graduate,Yes,9833,1833,182,180,1,Urban,Y +LP002106,Male,Yes,,Graduate,Yes,5503,4490,70,,1,Semiurban,Y +LP002110,Male,Yes,1,Graduate,,5250,688,160,360,1,Rural,Y +LP002112,Male,Yes,2,Graduate,Yes,2500,4600,176,360,1,Rural,Y +LP002113,Female,No,3+,Not Graduate,No,1830,0,,360,0,Urban,N +LP002114,Female,No,0,Graduate,No,4160,0,71,360,1,Semiurban,Y +LP002115,Male,Yes,3+,Not Graduate,No,2647,1587,173,360,1,Rural,N +LP002116,Female,No,0,Graduate,No,2378,0,46,360,1,Rural,N +LP002119,Male,Yes,1,Not Graduate,No,4554,1229,158,360,1,Urban,Y +LP002126,Male,Yes,3+,Not Graduate,No,3173,0,74,360,1,Semiurban,Y +LP002128,Male,Yes,2,Graduate,,2583,2330,125,360,1,Rural,Y +LP002129,Male,Yes,0,Graduate,No,2499,2458,160,360,1,Semiurban,Y +LP002130,Male,Yes,,Not Graduate,No,3523,3230,152,360,0,Rural,N +LP002131,Male,Yes,2,Not Graduate,No,3083,2168,126,360,1,Urban,Y +LP002137,Male,Yes,0,Graduate,No,6333,4583,259,360,,Semiurban,Y +LP002138,Male,Yes,0,Graduate,No,2625,6250,187,360,1,Rural,Y +LP002139,Male,Yes,0,Graduate,No,9083,0,228,360,1,Semiurban,Y +LP002140,Male,No,0,Graduate,No,8750,4167,308,360,1,Rural,N +LP002141,Male,Yes,3+,Graduate,No,2666,2083,95,360,1,Rural,Y +LP002142,Female,Yes,0,Graduate,Yes,5500,0,105,360,0,Rural,N +LP002143,Female,Yes,0,Graduate,No,2423,505,130,360,1,Semiurban,Y +LP002144,Female,No,,Graduate,No,3813,0,116,180,1,Urban,Y +LP002149,Male,Yes,2,Graduate,No,8333,3167,165,360,1,Rural,Y +LP002151,Male,Yes,1,Graduate,No,3875,0,67,360,1,Urban,N +LP002158,Male,Yes,0,Not Graduate,No,3000,1666,100,480,0,Urban,N +LP002160,Male,Yes,3+,Graduate,No,5167,3167,200,360,1,Semiurban,Y +LP002161,Female,No,1,Graduate,No,4723,0,81,360,1,Semiurban,N +LP002170,Male,Yes,2,Graduate,No,5000,3667,236,360,1,Semiurban,Y +LP002175,Male,Yes,0,Graduate,No,4750,2333,130,360,1,Urban,Y +LP002178,Male,Yes,0,Graduate,No,3013,3033,95,300,,Urban,Y +LP002180,Male,No,0,Graduate,Yes,6822,0,141,360,1,Rural,Y +LP002181,Male,No,0,Not Graduate,No,6216,0,133,360,1,Rural,N +LP002187,Male,No,0,Graduate,No,2500,0,96,480,1,Semiurban,N +LP002188,Male,No,0,Graduate,No,5124,0,124,,0,Rural,N +LP002190,Male,Yes,1,Graduate,No,6325,0,175,360,1,Semiurban,Y +LP002191,Male,Yes,0,Graduate,No,19730,5266,570,360,1,Rural,N +LP002194,Female,No,0,Graduate,Yes,15759,0,55,360,1,Semiurban,Y +LP002197,Male,Yes,2,Graduate,No,5185,0,155,360,1,Semiurban,Y +LP002201,Male,Yes,2,Graduate,Yes,9323,7873,380,300,1,Rural,Y +LP002205,Male,No,1,Graduate,No,3062,1987,111,180,0,Urban,N +LP002209,Female,No,0,Graduate,,2764,1459,110,360,1,Urban,Y +LP002211,Male,Yes,0,Graduate,No,4817,923,120,180,1,Urban,Y +LP002219,Male,Yes,3+,Graduate,No,8750,4996,130,360,1,Rural,Y +LP002223,Male,Yes,0,Graduate,No,4310,0,130,360,,Semiurban,Y +LP002224,Male,No,0,Graduate,No,3069,0,71,480,1,Urban,N +LP002225,Male,Yes,2,Graduate,No,5391,0,130,360,1,Urban,Y +LP002226,Male,Yes,0,Graduate,,3333,2500,128,360,1,Semiurban,Y +LP002229,Male,No,0,Graduate,No,5941,4232,296,360,1,Semiurban,Y +LP002231,Female,No,0,Graduate,No,6000,0,156,360,1,Urban,Y +LP002234,Male,No,0,Graduate,Yes,7167,0,128,360,1,Urban,Y +LP002236,Male,Yes,2,Graduate,No,4566,0,100,360,1,Urban,N +LP002237,Male,No,1,Graduate,,3667,0,113,180,1,Urban,Y +LP002239,Male,No,0,Not Graduate,No,2346,1600,132,360,1,Semiurban,Y +LP002243,Male,Yes,0,Not Graduate,No,3010,3136,,360,0,Urban,N +LP002244,Male,Yes,0,Graduate,No,2333,2417,136,360,1,Urban,Y +LP002250,Male,Yes,0,Graduate,No,5488,0,125,360,1,Rural,Y +LP002255,Male,No,3+,Graduate,No,9167,0,185,360,1,Rural,Y +LP002262,Male,Yes,3+,Graduate,No,9504,0,275,360,1,Rural,Y +LP002263,Male,Yes,0,Graduate,No,2583,2115,120,360,,Urban,Y +LP002265,Male,Yes,2,Not Graduate,No,1993,1625,113,180,1,Semiurban,Y +LP002266,Male,Yes,2,Graduate,No,3100,1400,113,360,1,Urban,Y +LP002272,Male,Yes,2,Graduate,No,3276,484,135,360,,Semiurban,Y +LP002277,Female,No,0,Graduate,No,3180,0,71,360,0,Urban,N +LP002281,Male,Yes,0,Graduate,No,3033,1459,95,360,1,Urban,Y +LP002284,Male,No,0,Not Graduate,No,3902,1666,109,360,1,Rural,Y +LP002287,Female,No,0,Graduate,No,1500,1800,103,360,0,Semiurban,N +LP002288,Male,Yes,2,Not Graduate,No,2889,0,45,180,0,Urban,N +LP002296,Male,No,0,Not Graduate,No,2755,0,65,300,1,Rural,N +LP002297,Male,No,0,Graduate,No,2500,20000,103,360,1,Semiurban,Y +LP002300,Female,No,0,Not Graduate,No,1963,0,53,360,1,Semiurban,Y +LP002301,Female,No,0,Graduate,Yes,7441,0,194,360,1,Rural,N +LP002305,Female,No,0,Graduate,No,4547,0,115,360,1,Semiurban,Y +LP002308,Male,Yes,0,Not Graduate,No,2167,2400,115,360,1,Urban,Y +LP002314,Female,No,0,Not Graduate,No,2213,0,66,360,1,Rural,Y +LP002315,Male,Yes,1,Graduate,No,8300,0,152,300,0,Semiurban,N +LP002317,Male,Yes,3+,Graduate,No,81000,0,360,360,0,Rural,N +LP002318,Female,No,1,Not Graduate,Yes,3867,0,62,360,1,Semiurban,N +LP002319,Male,Yes,0,Graduate,,6256,0,160,360,,Urban,Y +LP002328,Male,Yes,0,Not Graduate,No,6096,0,218,360,0,Rural,N +LP002332,Male,Yes,0,Not Graduate,No,2253,2033,110,360,1,Rural,Y +LP002335,Female,Yes,0,Not Graduate,No,2149,3237,178,360,0,Semiurban,N +LP002337,Female,No,0,Graduate,No,2995,0,60,360,1,Urban,Y +LP002341,Female,No,1,Graduate,No,2600,0,160,360,1,Urban,N +LP002342,Male,Yes,2,Graduate,Yes,1600,20000,239,360,1,Urban,N +LP002345,Male,Yes,0,Graduate,No,1025,2773,112,360,1,Rural,Y +LP002347,Male,Yes,0,Graduate,No,3246,1417,138,360,1,Semiurban,Y +LP002348,Male,Yes,0,Graduate,No,5829,0,138,360,1,Rural,Y +LP002357,Female,No,0,Not Graduate,No,2720,0,80,,0,Urban,N +LP002361,Male,Yes,0,Graduate,No,1820,1719,100,360,1,Urban,Y +LP002362,Male,Yes,1,Graduate,No,7250,1667,110,,0,Urban,N +LP002364,Male,Yes,0,Graduate,No,14880,0,96,360,1,Semiurban,Y +LP002366,Male,Yes,0,Graduate,No,2666,4300,121,360,1,Rural,Y +LP002367,Female,No,1,Not Graduate,No,4606,0,81,360,1,Rural,N +LP002368,Male,Yes,2,Graduate,No,5935,0,133,360,1,Semiurban,Y +LP002369,Male,Yes,0,Graduate,No,2920,16.12000084,87,360,1,Rural,Y +LP002370,Male,No,0,Not Graduate,No,2717,0,60,180,1,Urban,Y +LP002377,Female,No,1,Graduate,Yes,8624,0,150,360,1,Semiurban,Y +LP002379,Male,No,0,Graduate,No,6500,0,105,360,0,Rural,N +LP002386,Male,No,0,Graduate,,12876,0,405,360,1,Semiurban,Y +LP002387,Male,Yes,0,Graduate,No,2425,2340,143,360,1,Semiurban,Y +LP002390,Male,No,0,Graduate,No,3750,0,100,360,1,Urban,Y +LP002393,Female,,,Graduate,No,10047,0,,240,1,Semiurban,Y +LP002398,Male,No,0,Graduate,No,1926,1851,50,360,1,Semiurban,Y +LP002401,Male,Yes,0,Graduate,No,2213,1125,,360,1,Urban,Y +LP002403,Male,No,0,Graduate,Yes,10416,0,187,360,0,Urban,N +LP002407,Female,Yes,0,Not Graduate,Yes,7142,0,138,360,1,Rural,Y +LP002408,Male,No,0,Graduate,No,3660,5064,187,360,1,Semiurban,Y +LP002409,Male,Yes,0,Graduate,No,7901,1833,180,360,1,Rural,Y +LP002418,Male,No,3+,Not Graduate,No,4707,1993,148,360,1,Semiurban,Y +LP002422,Male,No,1,Graduate,No,37719,0,152,360,1,Semiurban,Y +LP002424,Male,Yes,0,Graduate,No,7333,8333,175,300,,Rural,Y +LP002429,Male,Yes,1,Graduate,Yes,3466,1210,130,360,1,Rural,Y +LP002434,Male,Yes,2,Not Graduate,No,4652,0,110,360,1,Rural,Y +LP002435,Male,Yes,0,Graduate,,3539,1376,55,360,1,Rural,N +LP002443,Male,Yes,2,Graduate,No,3340,1710,150,360,0,Rural,N +LP002444,Male,No,1,Not Graduate,Yes,2769,1542,190,360,,Semiurban,N +LP002446,Male,Yes,2,Not Graduate,No,2309,1255,125,360,0,Rural,N +LP002447,Male,Yes,2,Not Graduate,No,1958,1456,60,300,,Urban,Y +LP002448,Male,Yes,0,Graduate,No,3948,1733,149,360,0,Rural,N +LP002449,Male,Yes,0,Graduate,No,2483,2466,90,180,0,Rural,Y +LP002453,Male,No,0,Graduate,Yes,7085,0,84,360,1,Semiurban,Y +LP002455,Male,Yes,2,Graduate,No,3859,0,96,360,1,Semiurban,Y +LP002459,Male,Yes,0,Graduate,No,4301,0,118,360,1,Urban,Y +LP002467,Male,Yes,0,Graduate,No,3708,2569,173,360,1,Urban,N +LP002472,Male,No,2,Graduate,No,4354,0,136,360,1,Rural,Y +LP002473,Male,Yes,0,Graduate,No,8334,0,160,360,1,Semiurban,N +LP002478,,Yes,0,Graduate,Yes,2083,4083,160,360,,Semiurban,Y +LP002484,Male,Yes,3+,Graduate,No,7740,0,128,180,1,Urban,Y +LP002487,Male,Yes,0,Graduate,No,3015,2188,153,360,1,Rural,Y +LP002489,Female,No,1,Not Graduate,,5191,0,132,360,1,Semiurban,Y +LP002493,Male,No,0,Graduate,No,4166,0,98,360,0,Semiurban,N +LP002494,Male,No,0,Graduate,No,6000,0,140,360,1,Rural,Y +LP002500,Male,Yes,3+,Not Graduate,No,2947,1664,70,180,0,Urban,N +LP002501,,Yes,0,Graduate,No,16692,0,110,360,1,Semiurban,Y +LP002502,Female,Yes,2,Not Graduate,,210,2917,98,360,1,Semiurban,Y +LP002505,Male,Yes,0,Graduate,No,4333,2451,110,360,1,Urban,N +LP002515,Male,Yes,1,Graduate,Yes,3450,2079,162,360,1,Semiurban,Y +LP002517,Male,Yes,1,Not Graduate,No,2653,1500,113,180,0,Rural,N +LP002519,Male,Yes,3+,Graduate,No,4691,0,100,360,1,Semiurban,Y +LP002522,Female,No,0,Graduate,Yes,2500,0,93,360,,Urban,Y +LP002524,Male,No,2,Graduate,No,5532,4648,162,360,1,Rural,Y +LP002527,Male,Yes,2,Graduate,Yes,16525,1014,150,360,1,Rural,Y +LP002529,Male,Yes,2,Graduate,No,6700,1750,230,300,1,Semiurban,Y +LP002530,,Yes,2,Graduate,No,2873,1872,132,360,0,Semiurban,N +LP002531,Male,Yes,1,Graduate,Yes,16667,2250,86,360,1,Semiurban,Y +LP002533,Male,Yes,2,Graduate,No,2947,1603,,360,1,Urban,N +LP002534,Female,No,0,Not Graduate,No,4350,0,154,360,1,Rural,Y +LP002536,Male,Yes,3+,Not Graduate,No,3095,0,113,360,1,Rural,Y +LP002537,Male,Yes,0,Graduate,No,2083,3150,128,360,1,Semiurban,Y +LP002541,Male,Yes,0,Graduate,No,10833,0,234,360,1,Semiurban,Y +LP002543,Male,Yes,2,Graduate,No,8333,0,246,360,1,Semiurban,Y +LP002544,Male,Yes,1,Not Graduate,No,1958,2436,131,360,1,Rural,Y +LP002545,Male,No,2,Graduate,No,3547,0,80,360,0,Rural,N +LP002547,Male,Yes,1,Graduate,No,18333,0,500,360,1,Urban,N +LP002555,Male,Yes,2,Graduate,Yes,4583,2083,160,360,1,Semiurban,Y +LP002556,Male,No,0,Graduate,No,2435,0,75,360,1,Urban,N +LP002560,Male,No,0,Not Graduate,No,2699,2785,96,360,,Semiurban,Y +LP002562,Male,Yes,1,Not Graduate,No,5333,1131,186,360,,Urban,Y +LP002571,Male,No,0,Not Graduate,No,3691,0,110,360,1,Rural,Y +LP002582,Female,No,0,Not Graduate,Yes,17263,0,225,360,1,Semiurban,Y +LP002585,Male,Yes,0,Graduate,No,3597,2157,119,360,0,Rural,N +LP002586,Female,Yes,1,Graduate,No,3326,913,105,84,1,Semiurban,Y +LP002587,Male,Yes,0,Not Graduate,No,2600,1700,107,360,1,Rural,Y +LP002588,Male,Yes,0,Graduate,No,4625,2857,111,12,,Urban,Y +LP002600,Male,Yes,1,Graduate,Yes,2895,0,95,360,1,Semiurban,Y +LP002602,Male,No,0,Graduate,No,6283,4416,209,360,0,Rural,N +LP002603,Female,No,0,Graduate,No,645,3683,113,480,1,Rural,Y +LP002606,Female,No,0,Graduate,No,3159,0,100,360,1,Semiurban,Y +LP002615,Male,Yes,2,Graduate,No,4865,5624,208,360,1,Semiurban,Y +LP002618,Male,Yes,1,Not Graduate,No,4050,5302,138,360,,Rural,N +LP002619,Male,Yes,0,Not Graduate,No,3814,1483,124,300,1,Semiurban,Y +LP002622,Male,Yes,2,Graduate,No,3510,4416,243,360,1,Rural,Y +LP002624,Male,Yes,0,Graduate,No,20833,6667,480,360,,Urban,Y +LP002625,,No,0,Graduate,No,3583,0,96,360,1,Urban,N +LP002626,Male,Yes,0,Graduate,Yes,2479,3013,188,360,1,Urban,Y +LP002634,Female,No,1,Graduate,No,13262,0,40,360,1,Urban,Y +LP002637,Male,No,0,Not Graduate,No,3598,1287,100,360,1,Rural,N +LP002640,Male,Yes,1,Graduate,No,6065,2004,250,360,1,Semiurban,Y +LP002643,Male,Yes,2,Graduate,No,3283,2035,148,360,1,Urban,Y +LP002648,Male,Yes,0,Graduate,No,2130,6666,70,180,1,Semiurban,N +LP002652,Male,No,0,Graduate,No,5815,3666,311,360,1,Rural,N +LP002659,Male,Yes,3+,Graduate,No,3466,3428,150,360,1,Rural,Y +LP002670,Female,Yes,2,Graduate,No,2031,1632,113,480,1,Semiurban,Y +LP002682,Male,Yes,,Not Graduate,No,3074,1800,123,360,0,Semiurban,N +LP002683,Male,No,0,Graduate,No,4683,1915,185,360,1,Semiurban,N +LP002684,Female,No,0,Not Graduate,No,3400,0,95,360,1,Rural,N +LP002689,Male,Yes,2,Not Graduate,No,2192,1742,45,360,1,Semiurban,Y +LP002690,Male,No,0,Graduate,No,2500,0,55,360,1,Semiurban,Y +LP002692,Male,Yes,3+,Graduate,Yes,5677,1424,100,360,1,Rural,Y +LP002693,Male,Yes,2,Graduate,Yes,7948,7166,480,360,1,Rural,Y +LP002697,Male,No,0,Graduate,No,4680,2087,,360,1,Semiurban,N +LP002699,Male,Yes,2,Graduate,Yes,17500,0,400,360,1,Rural,Y +LP002705,Male,Yes,0,Graduate,No,3775,0,110,360,1,Semiurban,Y +LP002706,Male,Yes,1,Not Graduate,No,5285,1430,161,360,0,Semiurban,Y +LP002714,Male,No,1,Not Graduate,No,2679,1302,94,360,1,Semiurban,Y +LP002716,Male,No,0,Not Graduate,No,6783,0,130,360,1,Semiurban,Y +LP002717,Male,Yes,0,Graduate,No,1025,5500,216,360,,Rural,Y +LP002720,Male,Yes,3+,Graduate,No,4281,0,100,360,1,Urban,Y +LP002723,Male,No,2,Graduate,No,3588,0,110,360,0,Rural,N +LP002729,Male,No,1,Graduate,No,11250,0,196,360,,Semiurban,N +LP002731,Female,No,0,Not Graduate,Yes,18165,0,125,360,1,Urban,Y +LP002732,Male,No,0,Not Graduate,,2550,2042,126,360,1,Rural,Y +LP002734,Male,Yes,0,Graduate,No,6133,3906,324,360,1,Urban,Y +LP002738,Male,No,2,Graduate,No,3617,0,107,360,1,Semiurban,Y +LP002739,Male,Yes,0,Not Graduate,No,2917,536,66,360,1,Rural,N +LP002740,Male,Yes,3+,Graduate,No,6417,0,157,180,1,Rural,Y +LP002741,Female,Yes,1,Graduate,No,4608,2845,140,180,1,Semiurban,Y +LP002743,Female,No,0,Graduate,No,2138,0,99,360,0,Semiurban,N +LP002753,Female,No,1,Graduate,,3652,0,95,360,1,Semiurban,Y +LP002755,Male,Yes,1,Not Graduate,No,2239,2524,128,360,1,Urban,Y +LP002757,Female,Yes,0,Not Graduate,No,3017,663,102,360,,Semiurban,Y +LP002767,Male,Yes,0,Graduate,No,2768,1950,155,360,1,Rural,Y +LP002768,Male,No,0,Not Graduate,No,3358,0,80,36,1,Semiurban,N +LP002772,Male,No,0,Graduate,No,2526,1783,145,360,1,Rural,Y +LP002776,Female,No,0,Graduate,No,5000,0,103,360,0,Semiurban,N +LP002777,Male,Yes,0,Graduate,No,2785,2016,110,360,1,Rural,Y +LP002778,Male,Yes,2,Graduate,Yes,6633,0,,360,0,Rural,N +LP002784,Male,Yes,1,Not Graduate,No,2492,2375,,360,1,Rural,Y +LP002785,Male,Yes,1,Graduate,No,3333,3250,158,360,1,Urban,Y +LP002788,Male,Yes,0,Not Graduate,No,2454,2333,181,360,0,Urban,N +LP002789,Male,Yes,0,Graduate,No,3593,4266,132,180,0,Rural,N +LP002792,Male,Yes,1,Graduate,No,5468,1032,26,360,1,Semiurban,Y +LP002794,Female,No,0,Graduate,No,2667,1625,84,360,,Urban,Y +LP002795,Male,Yes,3+,Graduate,Yes,10139,0,260,360,1,Semiurban,Y +LP002798,Male,Yes,0,Graduate,No,3887,2669,162,360,1,Semiurban,Y +LP002804,Female,Yes,0,Graduate,No,4180,2306,182,360,1,Semiurban,Y +LP002807,Male,Yes,2,Not Graduate,No,3675,242,108,360,1,Semiurban,Y +LP002813,Female,Yes,1,Graduate,Yes,19484,0,600,360,1,Semiurban,Y +LP002820,Male,Yes,0,Graduate,No,5923,2054,211,360,1,Rural,Y +LP002821,Male,No,0,Not Graduate,Yes,5800,0,132,360,1,Semiurban,Y +LP002832,Male,Yes,2,Graduate,No,8799,0,258,360,0,Urban,N +LP002833,Male,Yes,0,Not Graduate,No,4467,0,120,360,,Rural,Y +LP002836,Male,No,0,Graduate,No,3333,0,70,360,1,Urban,Y +LP002837,Male,Yes,3+,Graduate,No,3400,2500,123,360,0,Rural,N +LP002840,Female,No,0,Graduate,No,2378,0,9,360,1,Urban,N +LP002841,Male,Yes,0,Graduate,No,3166,2064,104,360,0,Urban,N +LP002842,Male,Yes,1,Graduate,No,3417,1750,186,360,1,Urban,Y +LP002847,Male,Yes,,Graduate,No,5116,1451,165,360,0,Urban,N +LP002855,Male,Yes,2,Graduate,No,16666,0,275,360,1,Urban,Y +LP002862,Male,Yes,2,Not Graduate,No,6125,1625,187,480,1,Semiurban,N +LP002863,Male,Yes,3+,Graduate,No,6406,0,150,360,1,Semiurban,N +LP002868,Male,Yes,2,Graduate,No,3159,461,108,84,1,Urban,Y +LP002872,,Yes,0,Graduate,No,3087,2210,136,360,0,Semiurban,N +LP002874,Male,No,0,Graduate,No,3229,2739,110,360,1,Urban,Y +LP002877,Male,Yes,1,Graduate,No,1782,2232,107,360,1,Rural,Y +LP002888,Male,No,0,Graduate,,3182,2917,161,360,1,Urban,Y +LP002892,Male,Yes,2,Graduate,No,6540,0,205,360,1,Semiurban,Y +LP002893,Male,No,0,Graduate,No,1836,33837,90,360,1,Urban,N +LP002894,Female,Yes,0,Graduate,No,3166,0,36,360,1,Semiurban,Y +LP002898,Male,Yes,1,Graduate,No,1880,0,61,360,,Rural,N +LP002911,Male,Yes,1,Graduate,No,2787,1917,146,360,0,Rural,N +LP002912,Male,Yes,1,Graduate,No,4283,3000,172,84,1,Rural,N +LP002916,Male,Yes,0,Graduate,No,2297,1522,104,360,1,Urban,Y +LP002917,Female,No,0,Not Graduate,No,2165,0,70,360,1,Semiurban,Y +LP002925,,No,0,Graduate,No,4750,0,94,360,1,Semiurban,Y +LP002926,Male,Yes,2,Graduate,Yes,2726,0,106,360,0,Semiurban,N +LP002928,Male,Yes,0,Graduate,No,3000,3416,56,180,1,Semiurban,Y +LP002931,Male,Yes,2,Graduate,Yes,6000,0,205,240,1,Semiurban,N +LP002933,,No,3+,Graduate,Yes,9357,0,292,360,1,Semiurban,Y +LP002936,Male,Yes,0,Graduate,No,3859,3300,142,180,1,Rural,Y +LP002938,Male,Yes,0,Graduate,Yes,16120,0,260,360,1,Urban,Y +LP002940,Male,No,0,Not Graduate,No,3833,0,110,360,1,Rural,Y +LP002941,Male,Yes,2,Not Graduate,Yes,6383,1000,187,360,1,Rural,N +LP002943,Male,No,,Graduate,No,2987,0,88,360,0,Semiurban,N +LP002945,Male,Yes,0,Graduate,Yes,9963,0,180,360,1,Rural,Y +LP002948,Male,Yes,2,Graduate,No,5780,0,192,360,1,Urban,Y +LP002949,Female,No,3+,Graduate,,416,41667,350,180,,Urban,N +LP002950,Male,Yes,0,Not Graduate,,2894,2792,155,360,1,Rural,Y +LP002953,Male,Yes,3+,Graduate,No,5703,0,128,360,1,Urban,Y +LP002958,Male,No,0,Graduate,No,3676,4301,172,360,1,Rural,Y +LP002959,Female,Yes,1,Graduate,No,12000,0,496,360,1,Semiurban,Y +LP002960,Male,Yes,0,Not Graduate,No,2400,3800,,180,1,Urban,N +LP002961,Male,Yes,1,Graduate,No,3400,2500,173,360,1,Semiurban,Y +LP002964,Male,Yes,2,Not Graduate,No,3987,1411,157,360,1,Rural,Y +LP002974,Male,Yes,0,Graduate,No,3232,1950,108,360,1,Rural,Y +LP002978,Female,No,0,Graduate,No,2900,0,71,360,1,Rural,Y +LP002979,Male,Yes,3+,Graduate,No,4106,0,40,180,1,Rural,Y +LP002983,Male,Yes,1,Graduate,No,8072,240,253,360,1,Urban,Y +LP002984,Male,Yes,2,Graduate,No,7583,0,187,360,1,Urban,Y +LP002990,Female,No,0,Graduate,Yes,4583,0,133,360,0,Semiurban,N \ No newline at end of file