In [1]:

    

from sklearn.linear_model import LinearRegression


    

In [2]:

    

import pandas as pd

# Assign the dataframe to this variable.
# TODO: Load the data
bmi_life_data = pd.read_csv("bmi_and_life_expectancy.csv")


    

In [3]:

    

# Make and fit the linear regression model
#TODO: Fit the model and Assign it to bmi_life_model
bmi_life_model = LinearRegression()
bmi_life_model.fit(bmi_life_data[['BMI']], bmi_life_data[['Life expectancy']])


    

    
Out[3]:





LinearRegression(copy_X=True, fit_intercept=True, n_jobs=1, normalize=False)

In [4]:

    

# Mak a prediction using the model
# TODO: Predict life expectancy for a BMI value of 21.07931
laos_life_exp = bmi_life_model.predict(21.07931)


    

In [7]:

    

laos_life_exp[0][0]


    

    
Out[7]:





60.315647163993056