Pandas DataFrame: melt() function
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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