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.
Syntax:
Series.sum(self, axis=None, skipna=None, level=None, numeric_only=None, min_count=0, **kwargs)
Parameters:
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 |
Required |
level | If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a scalar. | int or level name Default Value: None |
Required |
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 |
Required |
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. |
int Default Value: 0 |
Required |
**kwargs | Additional keyword arguments to be passed to the function. | Required |
Returns: scalar or Series (if level specified)
Example:
Download the Pandas Series Notebooks from here.
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Next: Unique values of Series object in Pandas
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