pandas.DataFrame.melt

Unpivot a DataFrame from wide format to long format, optionally leaving identifier variables 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’. .. versionadded:: 0.20.0

param frame

DataFrame

param id_vars

tuple, list, or ndarray, optional

Column(s) to use as identifier variables.

param value_vars

tuple, list, or ndarray, optional

Column(s) to unpivot. If not specified, uses all columns that are not set as id_vars.

param var_name

scalar

Name to use for the ‘variable’ column. If None it uses frame.columns.name or ‘variable’.

param value_name

scalar, default ‘value’

Name to use for the ‘value’ column.

param col_level

int or string, optional

If columns are a MultiIndex then use this level to melt.

return

DataFrame Unpivoted DataFrame.

Warning

This feature is currently unsupported by Intel Scalable Dataframe Compiler