Pandas Series: sum() function

Sum of the values for the requested axis in Pandas

The sum() function is used to getg the sum of the values for the requested axis.

This is equivalent to the method numpy.sum.


Series.sum(self, axis=None, skipna=None, level=None, numeric_only=None, min_count=0, **kwargs)
Pandas Series sum image


Name Description Type/Default Value Required / Optional
axis Axis for the function to be applied on. {index (0)} Required
skipna Exclude NA/null values when computing the result. bool
Default Value: True
level If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a scalar. int or level name
Default Value: None
numeric_only Include only float, int, boolean columns. If None, will attempt to use everything, then use only numeric data. Not implemented for Series. bool
Default Value: None
min_count 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.
Default Value: 0
**kwargs Additional keyword arguments to be passed to the function. Required

Returns: scalar or Series (if level specified)


Download the above Notebook from here.

Previous: Compute numerical data ranks along axis
Next: Unique values of Series object in Pandas