Grouping and filtering with .apply()

By using .apply(), you can write functions that filter rows within groups. The .apply() method will handle the iteration over individual groups and then re-combine them back into a Series or DataFrame.

In this exercise you'll take the Titanic data set and analyze survival rates from the 'C' deck, which contained the most passengers. To do this you'll group the dataset by 'sex' and then use the .apply() method on a provided user defined function which calculates the mean survival rates on the 'C' deck:

def c_deck_survival(gr):

    c_passengers = gr['cabin'].str.startswith('C').fillna(False)

    return gr.loc[c_passengers, 'survived'].mean()

The DataFrame has been pre-loaded as titanic.

Group titanic by 'sex'. Save the result as by_sex.
Apply the provided c_deck_survival function on the by_sex DataFrame. Save the result as c_surv_by_sex.
Print c_surv_by_sex.

Exercise

Grouping and filtering with .apply()

Instructions