Related Articles

Related Articles

Python | Pandas Series.max()
  • Last Updated : 11 Feb, 2019

Pandas series is a One-dimensional ndarray with axis labels. The labels need not be unique but must be a hashable type. The object supports both integer- and label-based indexing and provides a host of methods for performing operations involving the index.

Pandas Series.max() function return the maximum of the underlying data in the given Series object. This function always returns Series even if only one value is returned.

Syntax: Series.max(axis=None, skipna=None, level=None, numeric_only=None, **kwargs)

Parameter :
axis : Axis for the function to be applied on.
skipna : Exclude NA/null values when computing the result.
level : If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a scalar.
numeric_only : Include only float, int, boolean columns.
**kwargs : Additional keyword arguments to be passed to the function.

Returns : max : scalar or Series (if level specified)



Example #1: Use Series.max() function to find the maximum value among the underlying data in the given series object.

filter_none

edit
close

play_arrow

link
brightness_4
code

# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series([10, 25, 3, 25, 24, 6])
  
# Create the Index
index_ = ['Coca Cola', 'Sprite', 'Coke', 'Fanta', 'Dew', 'ThumbsUp']
  
# set the index
sr.index = index_
  
# Print the series
print(sr)

chevron_right


Output :

Now we will use Series.max() function to find the maximum value of the given series object.

filter_none

edit
close

play_arrow

link
brightness_4
code

# return the maximum value in the 
# series object
result = sr.max()
  
# Print the result
print(result)

chevron_right


Output :

As we can see in the output, the Series.max() function has successfully returned the maximum value of the given series object.
 
Example #2: Use Series.max() function to find the maximum value among the underlying data in the given series object. The given series object also contains some missing values.

filter_none

edit
close

play_arrow

link
brightness_4
code

# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series([19.5, 16.8, None, 22.78, 16.8, 20.124, None, 18.1002, 19.5])
  
# Print the series
print(sr)

chevron_right


Output :

Now we will use Series.max() function to find the maximum value of the given series object. we are going to skip the missing value while finding the maximum value.

filter_none

edit
close

play_arrow

link
brightness_4
code

# return the maximum value in the series object
# skip the missing values
result = sr.max(skipna = True)
  
# Print the result
print(result)

chevron_right


Output :

As we can see in the output, the Series.max() function has successfully returned the maximum value of the given series object.

Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.




My Personal Notes arrow_drop_up
Recommended Articles
Page :