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Pandas melt()
The Pandas.melt() function is used to unpivot the DataFrame from a wide format to a long format.
Its main task is to massage a DataFrame into a format where some columns are identifier variables and remaining columns are considered as measured variables, are unpivoted to the row axis. It leaves just two non-identifier columns, variable and value.
Syntax
Parameters
- frame: It refers to the DataFrame.
- id_vars[tuple, list, or ndarray, optional]: It refers to the columns to use as identifier variables.
- value_vars[tuple, list, or ndarray, optional]: Refers to columns to unpivot. If it is not specified, use all columns that are not set as id_vars.
- var_name[scalar]: Refers to a name to use for the ‘variable’ column. If it is None, it uses frame.columns.name or ‘variable’.
- value_name[scalar, default ‘value’]: Refers to a name to use for the ‘value’ column.
- col_level[int or string, optional]: It will use this level to melt if the columns are MultiIndex.
Returns
It returns the unpivoted DataFrame as the output.
Example
Output
Name Language Age 0 Parker Python 22 1 Smith Java 30 2 John C++ 26
Example2
Output
A myVarname myValname 0 p C 56 1 q C 62 2 r C 42
Next TopicDataFrame.merge()