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Pandas DataFrame | reorder_levels method

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Python
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Pandas
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DataFrame
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Sorting and Restructuring DataFrames
schedule Mar 10, 2022
Last updated
local_offer PythonPandas
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Pandas DataFrame.reorder_levels(~) method changes the ordering of levels.

Parameters

1. orderlink | list<int> or list<string>

The new order of the levels. You can refer to the levels either by integer index or by their name.

2. axislink | int or string | optional

Whether to reorder index or column levels:

Axis

Description

Reorder levels of the index.

0 or "index"

Reorder levels of the column.

1 or "columns"

By default, axis=0.

Return Value

A new DataFrame with the levels reordered.

Examples

Reordering levels of multi-index row

Consider the following DataFrame with multi-index rows:

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 ordering of the row levels:

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

Here, the argument [1,0] means the following:

  • 1st level (inner level in this case) becomes the outer level.

  • 0th level (outer level) becomes the inner level.

Reordering levels of multi-index column

Consider the following DataFrame with multi-index columns:

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