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Pandas DataFrame cumsum() Method

❮ DataFrame Reference


Example

Multiply the values for each row with the values from the previous row:

import pandas as pd

data = [[10, 18, 11], [13, 15, 8], [9, 20, 3]]

df = pd.DataFrame(data)

print(df.cumsum())
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Definition and Usage

The cumsum() method returns a DataFrame with the cumulative sum for each row.

The cumsum() method goes through the values in the DataFrame, from the top, row by row, adding the values with the value from the previous row, ending up with a DataFrame where the last row contains the sum of all values for each column.

If the axis parameter is set to axes='columns', the method goes through the values, column by column, and ends up with a DataFrame where the last columns contains the sum of all values for each row.


Syntax

dataframe.cumsum(axis, skipna, args, kwargs)

Parameters

The axis and skipna parameters are keyword arguments.

Parameter Value Description
axis 0
1
'index'
'columns'
Optional, default 0, specifies the axis to run the accumulation over.
skip_na True
False
Optional, default True. Set to False if the result should NOT skip NULL values
args   Optional. These arguments has no effect, but could be accepted by a NumPy function
kwargs   Optional, keyword arguments. These arguments has no effect, but could be accepted by a NumPy function

 Return Value

A DataFrame object.

This function does NOT make changes to the original DataFrame object.


❮ DataFrame Reference