Percentile rank of a column in a Pandas DataFrame

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 :

# 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)

Output :

Example 2 :

# 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)

Output :