Looping over groups in a grouped dataframe

问题

Consider this small example:

data={"X":[1, 2, 3, 4, 5], "Y":[6, 7, 8, 9, 10], "Z": [11, 12, 13, 14, 15])
frame=pd.DataFrame(data,columns=["X","Y","Z"],index=["A","A","A","B","B"])

I want to group frame with

grouped=frame.groupby(frame.index)

Then I want to loop over the groups by:

for group in grouped:

But I'm stuck on the next step: How can I extract the group in each loop as a pandas DataFrame so I can further process it?

回答1:

df.groupby returns a list of 2-tuples: the index, and the group. You can iterate over each group like this:

for _, g in frame.groupby(frame.index):
    .... # do something with `g`

However, if you want to perform some operation on the groups, there are probably better ways than iteration.

回答2:

Here is an example:

groups = frame.groupby(level=0)

for n,g in groups:
    print('This is group '+ str(n)+'.')
    print(g)
    print('\n')

Output:

This is group A.
   X  Y   Z
A  1  6  11
A  2  7  12
A  3  8  13


This is group B.
   X   Y   Z
B  4   9  14
B  5  10  15

来源：https://stackoverflow.com/questions/45797633/looping-over-groups-in-a-grouped-dataframe