Pandas DataFrame apply() Method
Example
Return the sum of each row by applying a function:
import pandas as pd
def calc_sum(x):
return x.sum()
data =
{
"x": [50, 40, 30],
"y": [300, 1112, 42]
}
df
= pd.DataFrame(data)
x = df.apply(calc_sum)
print(x)
Try it Yourself »
Definition and Usage
The apply() method allows you to apply a function
along one of the axis of the DataFrame, default 0, which is the index (row)
axis.
Syntax
dataframe.apply(func, axis, raw, result_type, args,
kwds)
Parameters
The axis, raw,
result_type, and args
parameters are
keyword arguments.
| Parameter | Value | Description |
|---|---|---|
| func | Required. A function to apply to the DataFrame. | |
| axis | 0 |
Optional, Which axis to apply the function to. default 0. |
| raw | True |
Optional, default False. Set to true if the row/column should be passed as an ndarray object |
| result_type | 'expand' |
Optional, default None. Specifies how the result will be returned |
| args | a tuple | Optional, arguments to send into the function |
| kwds | keyword arguments | Optional, keyword arguments to send into the function |
Return Value
A DataFrame or a Series object, with the changes.
This function does NOT make changes to the original DataFrame object.
