Regressions

**Cleaning data for regression**

#################### Removing 'M' from the durations and changing Show/Movie to 2/1 ########################

ReplaceThis = ['m']

df.Duration = df.Duration.str.replace('|'.join(ReplaceThis), '').str.strip()

ReplaceThisM = ['M']

df.ShowOrMovie = df.ShowOrMovie.str.replace('|'.join(ReplaceThisM), '1').str.strip()

ReplaceThisS = ['S']

df.ShowOrMovie = df.ShowOrMovie.str.replace('|'.join(ReplaceThisS), '2').str.strip()

##########################################################################################

################################# Making cols numeric #######################################

df['Duration'] = df['Duration'].astype(float)

df['ShowOrMovie'] = df['ShowOrMovie'].astype(int)

df['IMDB_Rating'] = df['IMDB_Rating'].astype(int)

print df.dtypes

print df.describe()

##########################################################################################

Linear Regression

import statsmodels.api as sm

import statsmodels.formula.api as smf

LinearRegression = smf.ols(formula='Likability ~ IMDB_Rating + ShowOrMovie + Duration + Year ', data=df).fit()

print(LinearRegression.summary())