Examples
import numpy as np
import pandas as pd
idx = pd.MultiIndex.from_arrays([
['warm', 'warm', 'cold', 'cold'],
['fox', 'cat', 'snake', 'spider']],
names=['blooded', 'animal'])
s = pd.Series([4, 4, 0, 8], name='legs', index=idx)
s
s.sum()
Sum using level names, as well as indices.
s.sum(level='blooded')
By default, the sum of an empty or all-NA Series is 0.
pd.Series([]).sum() # min_count=0 is the default
This can be controlled with the min_count parameter. For example, if you’d like the sum of an empty
series to be NaN, pass min_count=1.
pd.Series([]).sum(min_count=1)
Thanks to the skipna parameter, min_count handles all-NA and empty series identically.
pd.Series([np.nan]).sum()
pd.Series([np.nan]).sum(min_count=1)