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Classe « DataFrame »

Méthode pandas.DataFrame.nsmallest

Signature de la méthode nsmallest

def nsmallest(self, n: 'int', columns: 'IndexLabel', keep: 'NsmallestNlargestKeep' = 'first') -> 'DataFrame' 

Description

help(DataFrame.nsmallest)

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`` : keep all the ties of the largest item even if it means
      selecting more than ``n`` items.

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, 337000,
...                                   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         337000      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 "population".

>>> df.nsmallest(3, 'population')
          population    GDP alpha-2
Tuvalu         11300     38      TV
Anguilla       11300    311      AI
Iceland       337000  17036      IS

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         337000  182      NR

When using ``keep='all'``, the number of element kept can go beyond ``n``
if there are duplicate values for the largest element, all the
ties are kept.

>>> df.nsmallest(3, 'population', keep='all')
          population    GDP alpha-2
Tuvalu         11300     38      TV
Anguilla       11300    311      AI
Iceland       337000  17036      IS
Nauru         337000    182      NR

However, ``nsmallest`` does not keep ``n`` distinct
smallest elements:

>>> df.nsmallest(4, 'population', keep='all')
          population    GDP alpha-2
Tuvalu         11300     38      TV
Anguilla       11300    311      AI
Iceland       337000  17036      IS
Nauru         337000    182      NR

To order by the smallest values in column "population" and then "GDP", we can
specify multiple columns like in the next example.

>>> df.nsmallest(3, ['population', 'GDP'])
          population  GDP alpha-2
Tuvalu         11300   38      TV
Anguilla       11300  311      AI
Nauru         337000  182      NR

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