summarizing a series.py

fake_data_index = pd.MultiIndex.from_product([
[
    'nate',
    'jess'
], pd.date_range('2019-01-01', '2019-12-31')
], names=('who', 'date'))
fake_df = pd.DataFrame({
    'increasing': np.arange(len(fake_data)),
    'random': np.random.rand(len(fake_data))
}, index=fake_data_index)

(fake_df 
     #Homework Part 2, Step 9
     #https://stackoverflow.com/questions/21646710/pandas-pivot-table-using-index-data-of-dataframe
    .reset_index()
    .pivot(columns='who', index='date', values='random')
     .loc['2019-01-01':'2019-03-31']
    .plot
    .line())

by_who_group = fake_df.groupby(['who'])
mean_by_who_all_cols_df = by_who_group.mean()
pd.DataFrame({
    'mean_of_increase':mean_by_who_all_cols_df['increasing'],
    'sum_of_random': by_who_group.sum()['random'],
    'mean_of_random': mean_by_who_all_cols_df['random']
})

by_who_group = fake_df.groupby(['who'])
agg_by_who_specific_cols = by_who_group.agg({
    'increasing':'mean',
    'random':['mean','sum']
})

#https://stackoverflow.com/a/14508633/1175496
agg_by_who_specific_cols.columns = [''.join(_) for _ in agg_by_who_specific_cols.columns]