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,
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: Please use
unpivot()
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 inid_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.