Pandas Series: cumsum() function

Last update on September 15 2022 12:54:09 (UTC/GMT +8 hours)

Cumulative sum over a Pandas DataFrame or Series axis

The cumsum() function is used to get cumulative sum over a DataFrame or Series axis.

Returns a DataFrame or Series of the same size containing the cumulative sum.

Syntax:

Series.cumsum(self, axis=None, skipna=True, *args, **kwargs)

Parameters:

Name	Description	Type/Default Value	Required / Optional
axis	The index or the name of the axis. 0 is equivalent to None or ‘index’.	{0 or ‘index’, 1 or ‘columns’} Default Value: 0	Required
skipna	Exclude NA/null values. If an entire row/column is NA, the result will be NA.	boolean Default Value: True	Required
args, *kwargs	Additional keywords have no effect but might be accepted for compatibility with NumPy.		Required

Returns: scalar or Series

Example - Series:

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series([3, np.nan, 4, -5, 0])
s

Output:

0    3.0
1    NaN
2    4.0
3   -5.0
4    0.0
dtype: float64

Example - By default, NA values are ignored:

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series([3, np.nan, 4, -5, 0])
s.cumsum()

Output:

0    3.0
1    NaN
2    7.0
3    2.0
4    2.0
dtype: float64

Example - To include NA values in the operation, use skipna=False:

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series([3, np.nan, 4, -5, 0])
s.cumsum(skipna=False)

Output:

0    3.0
1    NaN
2    NaN
3    NaN
4    NaN
dtype: float64

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