Distribution of each feature at each level of the target variable, with ttest and P-value with continuous variable

PHOTO EMBED

Tue Mar 15 2022 10:43:24 GMT+0000 (UTC)

Saved by @abhin__dev

def describe_cont_feature(feature):
    print('\n*** Results for {} ***'.format(feature))
    print(titanic.groupby('Survived')[feature].describe())
    print(ttest(feature))
    
def ttest(feature):
    survived = titanic[titanic['Survived']==1][feature]
    not_survived = titanic[titanic['Survived']==0][feature]
    tstat, pval = stats.ttest_ind(survived, not_survived, equal_var=False)
    print('t-statistic: {:.1f}, p-value: {:.3}'.format(tstat, pval))
    
# Look at the distribution of each feature at each level of the target variable
for feature in ['Pclass', 'Age', 'SibSp', 'Parch', 'Fare']:
    describe_cont_feature(feature)
content_copyCOPY

http://localhost:8888/notebooks/Desktop/Python/Ex_Files_Applied_ML/Ex_Files_Applied_ML/Exercise Files/03_Explore_Data/03_02/Begin/03_02.ipynb