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Python | Pandas Series.mode()

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

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Syntax: Series.mode(dropna=True)



Parameter :
dropna : Don’t consider counts of NaN/NaT

Returns : modes : Series

Example #1: Use Series.mode() function to find the mode of the given series object.




# 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)

Output :

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




# return the mode
result = sr.mode()
  
# Print the result
print(result)

Output :

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




# 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)

Output :

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




# return the mode
result = sr.mode()
  
# Print the result
print(result)

Output :

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




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