Python | Pandas Series.quantile()

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.quantile() function return value at the given quantile for the underlying data in the given Series object.

Syntax: Series.quantile(q=0.5, interpolation=’linear’) 

Parameter : 
q : float or array-like, default 0.5 (50% quantile) 
interpolation : {‘linear’, ‘lower’, ‘higher’, ‘midpoint’, ‘nearest’} 

Returns : quantile : float or Series

Example #1: Use Series.quantile() function to return the desired quantile of the underlying data in the given Series object. 

Python3

# importing pandas as pd
import pandas as pd

# Creating the Series
sr = pd.Series([10, 25, 3, 11, 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.quantile() function to find the 40% quantile of the underlying data in the given series object. 

Python3

# return the value of 40 % quantile
result = sr.quantile(q = 0.4)

# Print the result
print(result)

Output : As we can see in the output, the Series.quantile() function has successfully returned the desired quantile value of the underlying data of the given Series object. Example #2: Use Series.quantile() function to return the desired quantile of the underlying data in the given Series object. 

Python3

# importing pandas as pd
import pandas as pd

# Creating the Series
sr = pd.Series([11, 21, 8, 18, 65, 84, 32, 10, 5, 24, 32])

# Print the series
print(sr)

Output : Now we will use Series.quantile() function to find the 90% quantile of the underlying data in the given series object. 

Python3

# return the value of 90 % quantile
result = sr.quantile(q = 0.9)

# Print the result
print(result)

Output : As we can see in the output, the Series.quantile() function has successfully returned the desired quantile value of the underlying data of the given Series object.