Understanding MultiIndex

Question

So, I have a sample data like this in csv: -

name team date score John A 3/9/12 100 John B 3/9/12 99 Jane B 4/9/12 102 Peter A 9/9/12 103 Josie C 11/9/12 111 Rachel A 30/10/12 98 Kate B 31/10/12 103 David C 1/11/12 104 

Doing the following: -

 from pandas.io.parsers import read_csv df = read_csv("data/Workbook1.csv", index_col=["team", "name"]) df date score team name A John 3/9/12 100 B John 3/9/12 99 Jane 4/9/12 102 A Peter 9/9/12 103 C Josie 11/9/12 111 A Rachel 30/10/12 98 B Kate 31/10/12 103 C David 1/11/12 104 

How to compress the first index ("command") further so that I do not have duplicate values? Become: -

  date score team name A John 3/9/12 100 Peter 9/9/12 103 Rachel 30/10/12 98 B John 3/9/12 99 Jane 4/9/12 102 Kate 31/10/12 103 C Josie 11/9/12 111 David 1/11/12 104 

Answer 1

I thought for myself.

 df = read_csv("data/Workbook1.csv") df name team date score 0 John A 3/9/12 100 1 John B 3/9/12 99 2 Jane B 4/9/12 102 3 Peter A 9/9/12 103 4 Josie C 11/9/12 111 5 Rachel A 30/10/12 98 6 Kate B 31/10/12 103 7 David C 1/11/12 104 df2 = df.pivot('team', 'name').stack() df2 date score team name A John 3/9/12 100 Peter 9/9/12 103 Rachel 30/10/12 98 B Jane 4/9/12 102 John 3/9/12 99 Kate 31/10/12 103 C David 1/11/12 104 Josie 11/9/12 111 

Answer 2

as an alternative solution, if for some reason you want to keep multi-indexing in the read_csv statement.

The same dataset.

 df = pd.read_csv("Workbook1.csv", index_col=["team", "name"]) df.stack().unstack() date score team name A John 3/9/2012 100 Peter 9/9/2012 103 Rachel 30/10/12 98 B Jane 4/9/2012 102 John 3/9/2012 99 Kate 31/10/12 103 C David 1/11/2012 104 Josie 11/9/2012 111