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# Sorting a Pandas DataFrame by column

schedule Aug 12, 2023
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To sort a Pandas DataFrame by column, use the DataFrame's `sort_values(~)` method.

# Example

Consider the following DataFrame:

``` df = pd.DataFrame({"A":[5,3,1,3],"B":["c","d","a","a"]})df A B0 5 c1 3 d2 1 a3 3 a ```

## Sorting by a single column

To sort `df` by column `A`:

``` df.sort_values("A") A B2 1 a1 3 d3 3 a0 5 c ```

Here, a new DataFrame is returned the source DataFrame `df` is kept intact.

## Sorting by multiple columns

To sort `df` by both columns `A` and `B`, pass in a list of column labels:

``` df.sort_values(["A","B"]) A B2 1 a3 3 a1 3 d0 5 c ```

Here, the ordering of the column labels matters. In this case, we first sort by column `A`, and then afterwards sort by column `B`.

## Sorting in descending order

By default, values are sorted in ascending order. To sort in descending order instead, set `ascending=False`:

``` df.sort_values("A", ascending=False) A B0 5 c1 3 d3 3 a2 1 a ```
Published by Isshin Inada
Edited by 0 others
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