Pandas
keyboard_arrow_down 655 guides
chevron_leftSeries
check_circle
Mark as learned thumb_up
0
thumb_down
0
chat_bubble_outline
0
Comment auto_stories Bi-column layout
settings
Pandas Series | argmax method
schedule Aug 11, 2023
Last updated local_offer
Tags Python●Pandas
tocTable of Contents
expand_more Master the mathematics behind data science with 100+ top-tier guides
Start your free 7-days trial now!
Start your free 7-days trial now!
Pandas Series.argmax(~) returns the integer index of the maximum value in the Series. If there are multiple maximums, then the integer index of the first occurrence will be returned.
Parameters
1. skipna | boolean | optional
Whether or not to ignore missing value. If False and Series contains a missing value, then the method returns a -1. By default, skipna=True.
Return Value
An int.
Examples
Basic usage
To get the integer index of the maximum value in a Series:
s = pd.Series([3,5,4,5], index=["A","B","C","D"])s.argmax()
1
Notice how the integer index of the first maximum is returned.
Specifying skipna
By default, skipna=True, which means that missing values are ignored:
s = pd.Series([3,pd.np.nan,4], index=["A","B","C"])s.argmax() # skipna=True
2
If skipna=False and a missing value exists in the Series, then -1 is returned:
s = pd.Series([3,pd.np.nan,4], index=["A","B","C"])s.argmax(skipna=False)
-1
Published by Isshin Inada
Edited by 0 others
Did you find this page useful?
thumb_up
thumb_down
Comment
Citation
Ask a question or leave a feedback...
Official Pandas Documentation
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.argmax.html
thumb_up
0
thumb_down
0
chat_bubble_outline
0
settings
Enjoy our search
Hit / to insta-search docs and recipes!
