Python | Pandas Series.argmax ()

Michael Zippo 18.07.2021

Series.argmax() Pandas Series.argmax() returns the string label of the maximum value in the given object series.

Syntax: Series.argmax (axis = 0, skipna = True, * args, ** kwargs)

Parameter:
skipna: Exclude NA / null values. If the entire Series is NA, the result will be NA.
axis: For compatibility with DataFrame.idxmax. Redundant for application on Series.
* args, ** kwargs: Additional keywords have no effect but might be accepted for compatibility with NumPy.

Returns: idxmax: Index of maximum of values.

Example # 1: Use Series.argmax () to return the label maximum value lines in this series object

# import pandas as pd

import pandas as pd

# Create Series

sr = pd .Series ([ 34 , 5 , 13 , 32 , 4 , 15 ])

# Create index

index_ = [ ’Coca Cola’ , ’Sprite’ , ’ Coke’ , ’Fanta’ , ’ Dew’ , ’ThumbsUp’ ]

# set index

sr.index = index_

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# Print series

print (sr)

Output:

 Coca Cola 34 Sprite 5 Coke 13 Fanta 32 Dew 4 ThumbsUp 15 dtype: int64

Now we will use Series.argmax ( ) to return the label of the maximum value row in the given series object.

# return line label for
# maximum value

result = sr.argmax ()

# Print result

print (result)

Output:

 Coca Cola

As we see in the output , Series.argmax () successfully returned the string label of the maximum value in the given series object.

Example # 2: Use Series.argmax ( ) to get the label of the maximum value row in the given series object.

# import pandas as pd

import pandas as pd

# Create series

sr = pd.Series ([ 11 , 21 , 8 , 18 , 65 , 18 , 32 , 10 , 5 , 32 , None ])

# Create index
# apply annual rate

index_ = pd.date_range ( ’2010-10-09 08:45’ , periods = 11 , freq = ’Y’ )

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# set index

sr .index = index_

# Print series

print ( sr)

Output:

 2010-12-31 08:45:00 11.0 2011-12-31 08:45:00 21.0 2012-12-31 08:45:00 8.0 2013-12-31 08:45:00 18.0 2014-12-31 08:45:00 65.0 2015-12-31 08:45:00 18.0 2016-12-31 08:45:00 32.0 2017-12-31 08:45:00 10.0 2018-12-31 08 : 45: 00 5.0 2019-12-31 08:45:00 32.0 2020-12-31 08:45:00 NaN Freq: A-DEC, dtype: float64

Now we will use Series.argmax () to return the string label of the maximum value in the given series object.

# return line label for
# maximum value

result = sr.argmax ()

# Print result

print (result)

Output: