polars.LazyFrame.melt

LazyFrame.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,
    *,
    streamable: bool = True,
) → LazyFrame

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”

streamable

Allow this node to run in the streaming engine. If this runs in streaming, the output of the unpivot operation will not have a stable ordering.