Pandas DataFrame: melt() function

Last update on August 19 2022 21:50:52 (UTC/GMT +8 hours)

DataFrame - melt() function

The melt() function is used to unpivot a given DataFrame from wide format to long format, optionally leaving identifier variables set.

Syntax:

DataFrame.melt(self, id_vars=None, value_vars=None, var_name=None, value_name='value', col_level=None)

Parameters:

Name	Description	Type/Default Value	Required / Optional
frame		DataFrame	Required
id_vars	Column(s) to use as identifier variables.	tuple, list, or ndarray	Optional
value_vars	Column(s) to unpivot. If not specified, uses all columns that are not set as id_vars.	tuple, list, or ndarray	Optional
var_name	Name to use for the ‘variable’ column. If None it uses frame.columns.name or ‘variable’.	scalar	Required
value_name	Name to use for the ‘value’ column.	scalar Default Value: ‘value’	Required
col_level	If columns are a MultiIndex then use this level to melt.	int or string	Optional

Returns: DataFrame
Unpivoted DataFrame.

Example:

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