Python | Pandas Series.mode()
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.
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.
import pandas as pd
sr = pd.Series([ 10 , 25 , 3 , 25 , 24 , 6 ])
index_ = [ 'Coca Cola' , 'Sprite' , 'Coke' , 'Fanta' , 'Dew' , 'ThumbsUp' ]
sr.index = index_
print (sr)
|
Output :
Now we will use Series.mode()
function to find the mode of the given series object.
result = sr.mode()
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.
import pandas as pd
sr = pd.Series([ 19.5 , 16.8 , None , 22.78 , 16.8 , 20.124 , None , 18.1002 , 19.5 ])
print (sr)
|
Output :
Now we will use Series.mode()
function to find the mode of the given series object.
result = sr.mode()
print (result)
|
Output :
As we can see in the output, the Series.mode()
function has successfully returned the mode of the given series object.
Last Updated :
11 Feb, 2019
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