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 :
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