nsmallest(self, n: 'int' = 5, keep: 'str' = 'first')
Faster than .sort_values().head(n)
for small n
relative to the size of the Series
object.
Return this many ascending sorted values.
When there are duplicate values that cannot all fit in a Series of n
elements:
The n
smallest values in the Series, sorted in increasing order.
Return the smallest n
elements.
Series.head
Return the first :None:None:`n`
rows.
Series.nlargest
Get the :None:None:`n`
largest elements.
Series.sort_values
Sort Series by values.
>>> countries_population = {"Italy": 59000000, "France": 65000000,
... "Brunei": 434000, "Malta": 434000,
... "Maldives": 434000, "Iceland": 337000,
... "Nauru": 11300, "Tuvalu": 11300,
... "Anguilla": 11300, "Montserrat": 5200}
... s = pd.Series(countries_population)
... s Italy 59000000 France 65000000 Brunei 434000 Malta 434000 Maldives 434000 Iceland 337000 Nauru 11300 Tuvalu 11300 Anguilla 11300 Montserrat 5200 dtype: int64
The n
smallest elements where n=5
by default.
>>> s.nsmallest() Montserrat 5200 Nauru 11300 Tuvalu 11300 Anguilla 11300 Iceland 337000 dtype: int64
The n
smallest elements where n=3
. Default :None:None:`keep`
value is 'first' so Nauru and Tuvalu will be kept.
>>> s.nsmallest(3) Montserrat 5200 Nauru 11300 Tuvalu 11300 dtype: int64
The n
smallest elements where n=3
and keeping the last duplicates. Anguilla and Tuvalu will be kept since they are the last with value 11300 based on the index order.
>>> s.nsmallest(3, keep='last') Montserrat 5200 Anguilla 11300 Tuvalu 11300 dtype: int64
The n
smallest elements where n=3
with all duplicates kept. Note that the returned Series has four elements due to the three duplicates.
>>> s.nsmallest(3, keep='all') Montserrat 5200 Nauru 11300 Tuvalu 11300 Anguilla 11300 dtype: int64See :
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