Pandas DataFrame rpow() Method
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.