pandas.Series.sum¶
-
Series.
sum
(axis=None, skipna=None, level=None, numeric_only=None, min_count=0, **kwargs)[source]¶ Return the sum of the values for the requested axis
Parameters: - axis : {index (0)}
skipna : boolean, default True
Exclude NA/null values when computing the result.
level : int or level name, default None
If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a scalar
numeric_only : boolean, default None
Include only float, int, boolean columns. If None, will attempt to use everything, then use only numeric data. Not implemented for Series.
min_count : int, default 0
The required number of valid values to perform the operation. If fewer than
min_count
non-NA values are present the result will be NA.New in version 0.22.0: Added with the default being 0. This means the sum of an all-NA or empty Series is 0, and the product of an all-NA or empty Series is 1.
Returns: - sum : scalar or Series (if level specified)
Examples
By default, the sum of an empty or all-NA Series is
0
.>>> pd.Series([]).sum() # min_count=0 is the default 0.0
This can be controlled with the
min_count
parameter. For example, if you’d like the sum of an empty series to be NaN, passmin_count=1
.>>> pd.Series([]).sum(min_count=1) nan
Thanks to the
skipna
parameter,min_count
handles all-NA and empty series identically.>>> pd.Series([np.nan]).sum() 0.0
>>> pd.Series([np.nan]).sum(min_count=1) nan