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Pandas Series: cumprod() function

Cumulative product of a Pandas series

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

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

Syntax:

Series.cumprod(self, axis=None, skipna=True, *args, **kwargs)
Pandas Series cumprod image

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([2, np.nan, 4, -3, 0])
s

Output:

0    2.0
1    NaN
2    4.0
3   -3.0
4    0.0
dtype: float64
Pandas Series cumprod image

Example - By default, NA values are ignored:

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series([2, np.nan, 4, -3, 0])
s.cumprod()

Output:

0     2.0
1     NaN
2     8.0
3   -24.0
4    -0.0
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([2, np.nan, 4, -3, 0])
s.cumprod(skipna=False)

Output:

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

By default, iterates over rows and finds the product in each column. This is equivalent to axis=None or axis='index'.

Previous: Cumulative minimum over a Pandas DataFrame or Series axis
Next: Cumulative sum over a Pandas DataFrame or Series axis



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