saveenr saveenr - 7 months ago 614
Python Question

Converting a Pandas GroupBy object to DataFrame

I'm starting with input data like this

df1 = pandas.DataFrame( {
"Name" : ["Alice", "Bob", "Mallory", "Mallory", "Bob" , "Mallory"] ,
"City" : ["Seattle", "Seattle", "Portland", "Seattle", "Seattle", "Portland"] } )


Which when printed appears as this:

City Name
0 Seattle Alice
1 Seattle Bob
2 Portland Mallory
3 Seattle Mallory
4 Seattle Bob
5 Portland Mallory


Grouping is simple enough:

g1 = df1.groupby( [ "Name", "City"] ).count()


and printing yields a GroupBy object:

City Name
Name City
Alice Seattle 1 1
Bob Seattle 2 2
Mallory Portland 2 2
Seattle 1 1


But what I want eventually is another DataFrame object that contains all the rows in the GroupBy object. In other words I want to get the following result:

City Name
Name City
Alice Seattle 1 1
Bob Seattle 2 2
Mallory Portland 2 2
Mallory Seattle 1 1


I can't quite see how to accomplish this in the pandas documentation. Any hints would be welcome.

Answer

g1 here is a DataFrame. It has a hierarchical index, though:

In [19]: type(g1)
Out[19]: pandas.core.frame.DataFrame

In [20]: g1.index
Out[20]: 
MultiIndex([('Alice', 'Seattle'), ('Bob', 'Seattle'), ('Mallory', 'Portland'),
       ('Mallory', 'Seattle')], dtype=object)

Perhaps you want something like this?

In [21]: g1.add_suffix('_Count').reset_index()
Out[21]: 
      Name      City  City_Count  Name_Count
0    Alice   Seattle           1           1
1      Bob   Seattle           2           2
2  Mallory  Portland           2           2
3  Mallory   Seattle           1           1

Or something like:

In [36]: DataFrame({'count' : df1.groupby( [ "Name", "City"] ).size()}).reset_index()
Out[36]: 
      Name      City  count
0    Alice   Seattle      1
1      Bob   Seattle      2
2  Mallory  Portland      2
3  Mallory   Seattle      1