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Pandas DataFrame | nsmallest method

Programming
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Python
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Pandas
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Documentation
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DataFrame
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Sorting and Restructuring DataFrames
schedule Jul 1, 2022
Last updated
local_offer PythonPandas
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Pandas DataFrame.nsmallest(~) method returns n rows with the smallest value for the specified columns. The returned rows are sorted in ascending order.

Parameters

1. nlink | int

The number of rows you want returned.

2. columnslink | string or list of strings

The label(s) of the columns you want to order by.

3. keeplink | string | optional

How to handle duplicate values in the edge cases. Edge cases arise, for instance, if you select n=2, and the values are [5,4,4,4].

Value

How to deal with duplicate values at edge cases

"first"

Keep the first occurrence(s).

"last"

Keep the last occurrence(s).

"all"

Keep all the occurrences.

For "all", the number of returned rows may exceed n. By default, keep="first".

Return Value

A DataFrame with n rows that have the smallest value in the specified columns, in ascending order.

Examples

Basic usage

Consider the following DataFrame:

df = pd.DataFrame({"A":[4,6,1], "B":[3,3,8]})
df
A B
0 4 3
1 6 3
2 1 8

To get the 2 rows with the smallest value for column A:

df.nsmallest(2, "A")
A B
2 1 8
0 4 3

Notice how the returned rows are sorted in ascending order of the values in A.

Dealing with duplicate values

Consider the same df we had above:

df
A B
0 4 3
1 6 3
2 1 8

Keeping only the first

To get the first occurrence of the row with the smallest value for column B:

df.nsmallest(1, "B") # By default, keep="first"
A B
0 4 3

Notice how row 0 was returned, as opposed to row 1, despite the fact that they both had the same value (3) for column B.

Keeping only the last

To get the last occurrence instead, set keep="last":

df.nsmallest(1, "B", keep="last")
A B
1 6 3

Keeping all occurrences

To keep both the occurrences, set keep="all":

df.nsmallest(1, "B", keep="all")
A B
0 4 3
1 6 3

Notice how despite the fact that we set n=1, we end up with 2 rows.

robocat
Published by Isshin Inada
Edited by 0 others
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