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 |
Optional, Which axis to make the group by, default 0. |
| level | levelNone |
Optional. Specify if grouping should be done by a certain level. Default None |
| as_index | True |
Optional, default True. Set to False if the result should NOT use the group labels as index |
| sort | True |
Optional, default True. Set to False if the result should NOT sort the group keys (for better performance) |
| group_keys | True |
Optional, default True. Set to False if the result should NOT add the group keys to index |
| dropna | True |
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.
