In [1]:

    

import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
import statsmodels.formula.api as smf


    

In [3]:

    

pwd


    

    
Out[3]:





'C:\\Users\\Harsha Devulapalli\\Desktop\\algorithms\\class5\\homework'

In [4]:

    

cd C:\Users\Harsha Devulapalli\Desktop\algorithms


    

    




C:\Users\Harsha Devulapalli\Desktop\algorithms

In [5]:

    

cd ..


    

    




C:\Users\Harsha Devulapalli\Desktop

In [6]:

    

df=pd.read_csv("Fox1.csv")


    

In [7]:

    

df.plot(kind='scatter',x='Approve_of_Obama',y='Favour_Iran_Deal')
lm = smf.ols(formula="Favour_Iran_Deal~Approve_of_Obama",data=df).fit()
lm.params


    

    
Out[7]:





Intercept           30.528042
Approve_of_Obama     0.355619
dtype: float64






    

In [8]:

    

intercept, slope = lm.params


    

In [9]:

    

df.plot(kind="scatter",x="Approve_of_Obama",y="Favour_Iran_Deal")
plt.plot(df["Approve_of_Obama"],slope*df["Approve_of_Obama"]+intercept,"-",color="red")


    

    
Out[9]:





[<matplotlib.lines.Line2D at 0x1c72f7cbf98>]






    

In [10]:

    

df.plot(kind='scatter',x='Approve_of_Obama',y='Confident')
lm = smf.ols(formula="Confident~Approve_of_Obama",data=df).fit()
lm.params


    

    
Out[10]:





Intercept          -0.315065
Approve_of_Obama    0.389589
dtype: float64






    

In [11]:

    

intercept, slope = lm.params


    

In [12]:

    

df.plot(kind="scatter",x="Approve_of_Obama",y="Confident")
plt.plot(df["Approve_of_Obama"],slope*df["Approve_of_Obama"]+intercept,"-",color="red")


    

    
Out[12]:





[<matplotlib.lines.Line2D at 0x1c72fd18c18>]






    

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