nlargest(self, n: 'int', columns: 'IndexLabel', keep: 'str' = 'first') -> 'DataFrame'
Return the first n rows with the largest values in :None:None:`columns`, in descending 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=False).head(n)
, but more performant.
This function cannot be used with all column types. For example, when specifying columns with :None:None:`object` or category
dtypes, TypeError
is raised.
Number of rows to return.
Column label(s) to order by.
Where there are duplicate values:
The first n rows ordered by the given columns in descending order.
Return the first n rows ordered by :None:None:`columns` in descending order.
DataFrame.head
Return the first :None:None:`n` rows without re-ordering.
DataFrame.nsmallest
Return the first :None:None:`n` rows ordered by :None:None:`columns` in ascending order.
DataFrame.sort_values
Sort DataFrame by the values.
>>> 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 nlargest
to select the three rows having the largest values in column "population".
>>> df.nlargest(3, 'population') population GDP alpha-2 France 65000000 2583560 FR Italy 59000000 1937894 IT Malta 434000 12011 MT
When using keep='last'
, ties are resolved in reverse order:
>>> df.nlargest(3, 'population', keep='last') population GDP alpha-2 France 65000000 2583560 FR Italy 59000000 1937894 IT Brunei 434000 12128 BN
When using keep='all'
, all duplicate items are maintained:
>>> df.nlargest(3, 'population', keep='all') population GDP alpha-2 France 65000000 2583560 FR Italy 59000000 1937894 IT Malta 434000 12011 MT Maldives 434000 4520 MV Brunei 434000 12128 BN
To order by the largest values in column "population" and then "GDP", we can specify multiple columns like in the next example.
This example is valid syntax, but we were not able to check execution>>> df.nlargest(3, ['population', 'GDP']) population GDP alpha-2 France 65000000 2583560 FR Italy 59000000 1937894 IT Brunei 434000 12128 BNSee :
The following pages refer to to this document either explicitly or contain code examples using this.
pandas.core.frame.DataFrame.nsmallest
Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.
Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)
SVG is more flexible but power hungry; and does not scale well to 50 + nodes.
All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them