Linear Regression in python.py

#!/usr/bin/env python
# coding: utf-8

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import pandas as pd

import os


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iris=pd.read_csv("C:/Users/mymai/Downloads/CAR.csv")


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iris.head()


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iris['selling_price']<300000


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iris[iris['selling_price']<300000]


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y=[['selling_price']]


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x=[['km_driven']]


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from sklearn.model_selection import train_test_split


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x_train,x_test,y_train,y_test=train_test_split(x,y,test_size=0.3)


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from sklearn.preprocessing import LabelEncoder


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le= LabelEncoder()


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iris.fuel=le.fit_transform(iris.fuel)


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iris.transmission=le.fit_transform(iris.transmission)


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iris.seller_type=le.fit_transform(iris.seller_type)


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iris.owner=le.fit_transform(iris.owner)


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iris.name=le.fit_transform(iris.name)


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iris.head()


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iris.fuel=iris.fuel.astype('category')


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iris.seller_type=iris.seller_type.astype('category')


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iris.transmission=iris.transmission.astype('category')


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iris.owner=iris.owner.astype('category')


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iris.name=iris.name.astype('category')


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x_train,x_test,y_train,y_test=train_test_split(x,y,test_size=0.3)


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y=[['selling_price']]


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x=[['km_driven']]


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from sklearn.model_selection import train_test_split


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x_train,x_test,y_train,y_test=train_test_split(x,y,test_size=0.3)


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iris.describe()


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iris.describe('all')


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iris.describe(include='all')


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x_train.head()


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y=iris[['selling_price']]


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x=iris[['name','year','km_driven','fuel','seller_type','transmission','owner']]


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from sklearn.model_selection import train_test_split


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x_train,x_test,y_train,y_test=train_test_split(x,y,test_size=0.3)


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from sklearn.linear_model import LinearRegression


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lr2=LinearRegression()


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lr2.fit(x_train,y_train)


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y_pred=lr2.predict(x_test)


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y_pred[0:5]


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from sklearn.metrics import mean_squared_error


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mean_squared_error(y_test,y_pred)


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