What is the cumsum function in pandas?

The cumsum function in pandas returns a cumulative sum over a dataframe or series axis.

The return series or dataframe is of the same size as the original one, except with the cumulative sum.

The illustration below shows how the cumsum function works in pandas:

How does the cumsum function work in Pandas

Syntax

The syntax of the cumsum function is as follows:

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

Parameters

The table below describes each parameter of the cumsum function:

Parameter Description
axis The axis of the cumulative sum. axis takes a bool value. 0 refers to column-wise sum, whereas 1 refers to row-wise. By default, axis is 0.
skipna Determines if null values need to be excluded or not. By default, skipna is True.
args Additional keywords have no effect but might be accepted for compatibility with NumPy.
**kwargs Any additional arguments.

All parameters are optional.

Return value

The cumsum function returns a series or dataframe with the cumulative sum at each index. The length of the return object is the same as the original series or dataframe.

Example

The code snippet below shows how the cumsum function is used in pandas:

import pandas as pd
import numpy as np
s = pd.Series([2, np.nan, 5, -1, 0])
print("Original Series")
print(s)
print('\n')
print("Cumulative Sum-NA values are ignored by default")
print(s.cumsum())
print('\n')
print("If skip_na is False")
print(s.cumsum(skipna=False))
print('\n')
print("Original Dataframe")
df = pd.DataFrame([[2.0, 1.0], [3.0, np.nan], [1.0, 0.0]], columns=list('AB'))
print(df)
print('\n')
print("By default, cumulative sum")
print(df.cumsum())
print('\n')
print("Sum by Axis = 1 (row-wise)")
print(df.cumsum(axis=1))
print('\n')

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