Pandas DataFrame: stack() function

Last update on August 19 2022 21:50:51 (UTC/GMT +8 hours)

DataFrame - stack() function

The stack() function is used to stack the prescribed level(s) from columns to index.

Return a reshaped DataFrame or Series having a multi-level index with one or more new inner-most levels compared to the current DataFrame. The new inner-most levels are created by pivoting the columns of the current dataframe:

if the columns have a single level, the output is a Series;
if the columns have multiple levels, the new index level(s) is (are) taken from the prescribed level(s) and the output is a DataFrame.

The new index levels are sorted.

Syntax:

DataFrame.stack(self, level=-1, dropna=True)

Parameters:

Name	Description	Type/Default Value	Required / Optional
level	Level(s) to stack from the column axis onto the index axis, defined as one index or label, or a list of indices or labels.	int, str, list Default Value: 1	Required
dropna	Whether to drop rows in the resulting Frame/Series with missing values. Stacking a column level onto the index axis can create combinations of index and column values that are missing from the original dataframe.	bool Default Value: True	Required

Returns: DataFrame or Series
Stacked dataframe or series.

Example:

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