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Pandas DataFrame rpow() Method

❮ DataFrame Reference


Example

Find the exponential power of 5 for each value in the DataFrame:

import pandas as pd

data = {
  "points": [4, 5, 6],
  "total": [10, 12, 15]
}

df = pd.DataFrame(data)

print(df.rpow(5))
Try it Yourself »

Definition and Usage

The rpow() method raises a specified number with each value in the DataFrame.

This method is called reverse pow, and is similar to the pow() method, but instead of calculating 45 it calculates 54.

The specified number must be an object that can be used to raise the values in the DataFrame. It can be a constant number like the one in the example, or it can be a list-like object like a list [5, 10] or a tuple {"points": 5, "total": 10}, or a  Pandas Series or another DataFrame, that fits with the original DataFrame.


Syntax

dataframe.pow(other, axis, level, fill_value)

Parameters

Parameter Description
other Required. A number, list of numbers, or another object with a data structure that fits with the original DataFrame.
axis Optional, A definition that decides whether to compare by index or columns.
0 or 'index' means compare by index.
1 or 'columns' means compare by columns
level Optional. A number or label that indicates where to compare.
fill_value Optional. A number, or None. Specifies what to do with NaN values before doing the calculation.

Return Value

A DataFrame with the results.


❮ DataFrame Reference