Multiple linear Regression(update is yet to come by evening

 import pandas as  pd

import matplotlib.pyplot as plt

import numpy as np

from sklearn.model_selection import train_test_split

from sklearn.linear_model import LinearRegression

data = pd.read_csv("taxi.csv")

#print(df.head())

#[:,0:-1] all rows and all expect last column (independent  variable) also feature column

data_x = data.iloc[:,0:-1].values

#[:,-1]all rows and only last column (dependent variable) also target column

data_y = data.iloc[:,-1].values

x_train,x_test,y_train,y_test = train_test_split(data_x,data_y,test_size=0.3, random_state=0)

reg = LinearRegression()

reg.fit(x_train,y_train)

print("train_score=" ,reg.score(x_train,y_train))

print("train_score=" ,reg.score(x_test,y_test))

print(reg.predict([[80,1770000,6000,85]]))