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Pandas DataFrame | swaplevel method

schedule Aug 12, 2023
Last updated
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PythonPandas
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Pandas DataFrame.swaplevel(~) method swaps two levels of a multi-index DataFrame.

Parameters

1. ilink | int or string

The level to swap. You can refer to the levels either by integer index or by their name.

2. jlink | int or string

The other level to swap with.

3. axislink | int or string | optional

Whether to swap levels of index or columns:

Axis

Description

0 or "index"

Swap levels of the index.

1 or "columns"

Swap levels of the column.

By default, axis=0.

Return Value

A new DataFrame with a pair of levels swapped.

Examples

Swapping a pair of index levels

Consider the following multi-index DataFrame:

index = [("A", "alice"), ("A", "bob"),("A", "cathy"), ("B", "david"),("B", "eric")]
multi_index = pd.MultiIndex.from_tuples(index)
df = pd.DataFrame({"a":[2,3,4,5,6]}, index=multi_index)
df
a
A alice 2
bob 3
cathy 4
B david 5
eric 6

To swap the two levels:

df.swaplevel(0,1)
a
alice A 2
bob A 3
cathy A 4
david B 5
eric B 6

Here, we are swapping the inner-most level (1) with the outer-most level (0).

Swapping a pair of column levels

Consider the following multi-level column DataFrame:

index = [("A", "alice"), ("A", "bob"),("A", "cathy"), ("B", "david"),("B", "eric")]
multi_index = pd.MultiIndex.from_tuples(index)
df = pd.DataFrame([[2,3,4,5,6]], columns=multi_index)
df
A B
alice bob cathy david eric
0 2 3 4 5 6

To swap the ordering of the column levels, set axis=1 like so:

df.swaplevel(1, 0, axis=1)
alice bob cathy david eric
A A A B B
0 2 3 4 5 6
robocat
Published by Isshin Inada
Edited by 0 others
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