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Percentile rank of a column in a Pandas DataFrame
  • Last Updated : 17 Aug, 2020

Let us see how to find the percentile rank of a column in a Pandas DataFrame. We will use the rank() function with the argument pct = True to find the percentile rank.

Example 1 :

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# import the module
import pandas as pd 
  
# create a DataFrame 
data = {'Name': ['Mukul', 'Rohan', 'Mayank'
                 'Shubham', 'Aakash'],
        'Location' : ['Saharanpur', 'Meerut', 'Agra'
                      'Saharanpur', 'Meerut'],
        'Pay' : [50000, 70000, 62000, 67000, 56000]} 
df = pd.DataFrame(data)  
  
# create a new column of percentile rank
df['Percentile Rank'] = df.Pay.rank(pct = True)
  
# displaying the percentile rank
display(df) 

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Output :

Example 2 :

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# import the module
import pandas as pd 
  
# create a DataFrame 
ODI_runs = {'name': ['Tendulkar', 'Sangakkara', 'Ponting'
                      'Jayasurya', 'Jayawardene', 'Kohli'
                      'Haq', 'Kallis', 'Ganguly', 'Dravid'], 
            'runs': [18426, 14234, 13704, 13430, 12650
                     11867, 11739, 11579, 11363, 10889]} 
df = pd.DataFrame(ODI_runs)  
  
# create a new column of percentile rank
df['Percentile Rank'] = df.runs.rank(pct = True)
  
# displaying the percentile rank
display(df) 

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Output :

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