XII-IP : Pipe in Pandas

Pipe() in pandas

pipe() method is used to chain a number of operations on a dataframe in a single compound statement. Its an effective way of reducing codelines and achieve a single long term objective from a data frame. (We may run pipes of series items too) In the given example we a doing the followiing things to achive the goal of getting the mean of the Points column in an extracted group from a dataframe.

• Creating the group based on year - df.groupby('Year')
• Filtering in a single group from the set of groups(get_group(2014))
• Getting the mean of column Points - x['Points'].agg('mean') 

 coding:

import pandas as pd

ipl_data = {'Team': ['Riders', 'Riders', 'Devils', 'Devils', 'Kings',

   'kings', 'Kings', 'Kings', 'Riders', 'Royals', 'Royals', 'Riders'],

   'Rank': [1, 2, 2, 3, 3,4 ,1 ,1,2 , 4,1,2],

   'Year': [2014,2015,2014,2015,2014,2015,2016,2017,2016,2014,2015,2017],

   'Points':[876,789,863,673,741,812,756,788,694,701,804,690]}

df = pd.DataFrame(ipl_data)

x = df.pipe(lambda x: df.groupby('Year')

           .pipe(lambda x: x.get_group(2014))

           .pipe(lambda x: x['Points'].agg('mean')))

x

output:

795.25

Another example of pipe

x = df.pipe(lambda x: df.groupby('Team')

           .pipe(lambda x: x.get_group('kings'))

           .pipe(lambda x: x['Points'].agg('sum')))

x

output:

812