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) |
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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) |
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Output :
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