modin.pandas.DataFrame.nsmallest¶
- DataFrame.nsmallest(n, columns, keep='first') DataFrame [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)
- 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 thann
items.
- Return type:
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 beyondn
. 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 keepn
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