polars.DataFrame.melt

DataFrame.melt(
    id_vars: ColumnNameOrSelector | Sequence[ColumnNameOrSelector] | None = None,
    value_vars: ColumnNameOrSelector | Sequence[ColumnNameOrSelector] | None = None,
    variable_name: str | None = None,
    value_name: str | None = None,
) → DataFrame

Unpivot a DataFrame from wide to long format.

Optionally leaves identifiers set.

This function is useful to massage a DataFrame into a format where one or more columns are identifier variables (id_vars) while all other columns, considered measured variables (value_vars), are “unpivoted” to the row axis leaving just two non-identifier columns, ‘variable’ and ‘value’.

Deprecated since version 1.0.0: Use the unpivot() method instead.

Parameters:

id_vars

Column(s) or selector(s) to use as identifier variables.

value_vars

Column(s) or selector(s) to use as values variables; if value_vars is empty all columns that are not in id_vars will be used.

variable_name

Name to give to the variable column. Defaults to “variable”

value_name

Name to give to the value column. Defaults to “value”