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Pandas DataFrame melt() Method

❮ DataFrame Reference


Example

Stack the DataFrame from a table where each index had 4 columns, into a table with one row for each column:

In this example we use a .csv file called data.csv

import pandas as pd

df = pd.read_csv('data.csv')

newdf = df.melt()
Try it Yourself »

Definition and Usage

The melt() method reshapes the DataFrame into a long table with one row for each each column.


Syntax

dataframe.melt(id_vars, value_vars, var_name, value_name, col_level, ignore_index)

Parameters

The id_vars, value_vars, var_name, value_namecol_level, ignore_index parameters are keyword arguments.

Parameter Value Description
id_vars Tuple
List
Array
Optional, specifies the column, or columns, to use as identifiers
value_vars Tuple
List
Array
Optional, specifies columns to unpivot.
var_name String Optional, specifies the label of the 'variable' column, default 'variable'
col_level Number
String
Optional, for MultiIndex DataFrames, specifies the level to melt
ignore_index True
False
Optional, default True. Specifies whether to ignore the original index or not

Return Value

A reshaped DataFrame object.

This method does not change the original DataFrame.


❮ DataFrame Reference

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