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pandas.DataFrame.nsmallest

DataFrame.nsmallest(n, columns, keep='first')[source]

Return the first n rows ordered by columns in ascending order.

Return the first n rows with the smallest values in columns, in ascending order. The columns that are not specified are returned as well, but not used for ordering.

This method is equivalent to df.sort_values(columns, ascending=True).head(n), but more performant.

Parameters:

n : int

Number of items to retrieve.

columns : list or str

Column name or names to order by.

keep : {‘first’, ‘last’, ‘all’}, default ‘first’

Where there are duplicate values:

  • first : take the first occurrence.
  • last : take the last occurrence.
  • all : do not drop any duplicates, even it means selecting more than n items.

New in version 0.24.0.

Returns:
DataFrame

See also

DataFrame.nlargest
Return the first n rows ordered by columns in descending order.
DataFrame.sort_values
Sort DataFrame by the values.
DataFrame.head
Return the first n rows without re-ordering.

Examples

>>> df = pd.DataFrame({'population': [59000000, 65000000, 434000,
...                                   434000, 434000, 337000, 11300,
...                                   11300, 11300],
...                    'GDP': [1937894, 2583560 , 12011, 4520, 12128,
...                            17036, 182, 38, 311],
...                    'alpha-2': ["IT", "FR", "MT", "MV", "BN",
...                                "IS", "NR", "TV", "AI"]},
...                   index=["Italy", "France", "Malta",
...                          "Maldives", "Brunei", "Iceland",
...                          "Nauru", "Tuvalu", "Anguilla"])
>>> df
          population      GDP alpha-2
Italy       59000000  1937894      IT
France      65000000  2583560      FR
Malta         434000    12011      MT
Maldives      434000     4520      MV
Brunei        434000    12128      BN
Iceland       337000    17036      IS
Nauru          11300      182      NR
Tuvalu         11300       38      TV
Anguilla       11300      311      AI

In the following example, we will use nsmallest to select the three rows having the smallest values in column “a”.

>>> df.nsmallest(3, 'population')
          population  GDP alpha-2
Nauru          11300  182      NR
Tuvalu         11300   38      TV
Anguilla       11300  311      AI

When using keep='last', ties are resolved in reverse order:

>>> df.nsmallest(3, 'population', keep='last')
          population  GDP alpha-2
Anguilla       11300  311      AI
Tuvalu         11300   38      TV
Nauru          11300  182      NR

When using keep='all', all duplicate items are maintained:

>>> df.nsmallest(3, 'population', keep='all')
          population  GDP alpha-2
Nauru          11300  182      NR
Tuvalu         11300   38      TV
Anguilla       11300  311      AI

To order by the largest values in column “a” and then “c”, we can specify multiple columns like in the next example.

>>> df.nsmallest(3, ['population', 'GDP'])
          population  GDP alpha-2
Tuvalu         11300   38      TV
Nauru          11300  182      NR
Anguilla       11300  311      AI
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