Python | Pandas Series.argmax ()



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_

< code class = "undefined spaces">  
# 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:

 2014-12-31 08:45:00 

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