Pandas DataFrame groupby() Method

Example

Find the average co2 consumption for each car brand:

import pandas as pd

data = {
'co2': [95, 90, 99, 104, 105, 94, 99, 104],
'model': ['Citigo', 'Fabia', 'Fiesta', 'Rapid', 'Focus', 'Mondeo', 'Octavia', 'B-Max'],
'car': ['Skoda', 'Skoda', 'Ford', 'Skoda', 'Ford', 'Ford', 'Skoda', 'Ford']
}

df = pd.DataFrame(data)

print(df.groupby(["car"]).mean())

Try it Yourself »

Definition and Usage

The groupby() method allows you to group your data and execute functions on these groups.

Syntax

dataframe.transform(by, axis, level, as_index, sort, group_keys, observed, dropna)

Parameters

The axis, level, as_index, sort, group_keys, observed, dropna parameters are keyword arguments.

Parameter	Value	Description
by		Required. A label, a list of labels, or a function used to specify how to group the DataFrame.
axis	`0 1 'index' 'columns'`	Optional, Which axis to make the group by, default 0.
level	level `None`	Optional. Specify if grouping should be done by a certain level. Default None
as_index	`True False`	Optional, default True. Set to False if the result should NOT use the group labels as index
sort	`True False`	Optional, default True. Set to False if the result should NOT sort the group keys (for better performance)
group_keys	`True False`	Optional, default True. Set to False if the result should NOT add the group keys to index
dropna	`True False`	Optional, default True. Set to False if the result should include the rows/columns where the group key is a NULL value