Convert DataFrameGroupBy object to DataFrame pandas
df_g.apply(lambda x: x)
will return the original dataframe.
The result of kl.aggregate(np.sum)
is a normal DataFrame, you just have to assign it to a variable to further use it. With some random data:
>>> df = DataFrame({'A' : ['foo', 'bar', 'foo', 'bar',
>>> 'foo', 'bar', 'foo', 'foo'],
... 'B' : ['one', 'one', 'two', 'three',
... 'two', 'two', 'one', 'three'],
... 'C' : randn(8), 'D' : randn(8)})
>>> grouped = df.groupby('A')
>>> grouped
<pandas.core.groupby.DataFrameGroupBy object at 0x04E2F630>
>>> test = grouped.aggregate(np.sum)
>>> test
C D
A
bar -1.852376 2.204224
foo -3.398196 -0.045082
Using pd.concat
, just like this:
pd.concat(map(lambda x: x[1], groups))
Or also keep index
aligned:
pd.concat(map(lambda x: x[1], groups)).sort_index()