Pandas DataFrame aggregate() Method
Example
Return the sum of each row:
import pandas as pd
data = {
"x": [50, 40, 30],
"y": [300, 1112, 42]
}
df = pd.DataFrame(data)
x = df.aggregate(["sum"])
print(x)
Try it Yourself »
data = {
"x": [50, 40, 30],
"y": [300, 1112, 42]
}
df = pd.DataFrame(data)
x = df.aggregate(["sum"])
print(x)
Definition and Usage
The aggregate() method allows you to apply a function
or a list of function names to be executed
along one of the axis of the DataFrame, default 0, which is the index (row)
axis.
Note: the agg() method is an alias of the
aggregate() method.
Syntax
dataframe.aggregate(func, axis, args, kwargs)
Parameters
The axis
parameter is a
keyword argument.
| Parameter | Value | Description |
|---|---|---|
| func | Required. A function, function name, or a list of function names to apply to the DataFrame. | |
| axis | 0 |
Optional, Which axis to apply the function to. default 0. |
| args | Optional, arguments to send into the function | |
| kwargs | 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.