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Pandas DataFrame groupby() Method

❮ DataFrame Reference


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

Return Value

A DataFrameGroupBy object where the rows/columns are grouped.


❮ DataFrame Reference

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