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TWEET # Untitled a guest Jun 26th, 2019 54 Never
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1. import numpy as np
2. import pandas as pd
3. result = data.groupby(groupbyvars).agg({'amount': [ pd.Series.sum, pd.Series.mean]}).reset_index()
4.
5. data.groupby(groupbyvars).agg({'amount': [ pd.Series.sum(skipna=True), pd.Series.mean(skipna=True)]}).reset_index()
6.
7. s_na_mean = partial(pd.Series.mean, skipna = True)
8. data.groupby(groupbyvars).agg({'amount': [ np.nansum, s_na_mean ]}).reset_index()
9.
10. error: 'functools.partial' object has no attribute '__name__'
11.
12. from numpy import nansum
13. from numpy import nanmean
14. data.groupby(groupbyvars).agg({'amount': [ nansum, nanmean]}).reset_index()
15.
16. from functools import partial
17. s_na_mean = partial(pd.Series.mean, skipna = True)
18.
19. import numpy as np
20. import pandas as pd
21.
22. def nan_agg(x):
23.     res = {}
24.
25.     res['nansum'] = x.loc[ not x['amount'].isnull(), :]['amount'].sum()
26.     res['nanmean'] = x.loc[ not x['amount'].isnull(), :]['amount'].mean()
27.
28.     return pd.Series(res, index=['nansum', 'nanmean'])
29.
30. result = data.groupby(groupbyvars).apply(nan_agg).reset_index()
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