Convert a pandas groupby object to list of dataframes

Question

Say I have the following dataframe, and want to group-by the ys:

I can do this by running

grouped = df.groupby('ys')

I can iterate through this new groupby object fine, but instead I want a list of the dataframes that are accessed by group in the following loop:

for name, group in grouped:
    do_something(group)

Is this possible?

You want a list that is accessed by a group name? That's impossible. You probably want a dict. — juanpa.arrivillaga
– juanpa.arrivillaga, Commented Jan 16, 2017 at 17:26
No, I just want a list of the dataframes and don't care about the names. Just realised my loop was wrong, should be corrected now — David Stansby
– David Stansby, Commented Jan 16, 2017 at 17:28

juanpa.arrivillaga · Accepted Answer · 2017-01-16 17:29:13Z

28

Sure, just iterate over the groups!

>>> import pandas as pd, numpy as np
>>> df = pd.DataFrame(dict(xs=list(range(4)), ys=[0,0,1,1]))
>>> df
   xs  ys
0   0   0
1   1   0
2   2   1
3   3   1
>>> grouped = df.groupby('ys')
>>> dataframes = [group for _, group in grouped]
>>> dataframes
[   xs  ys
0   0   0
1   1   0,    xs  ys
2   2   1
3   3   1]
>>>

answered Jan 16, 2017 at 17:29

juanpa.arrivillaga

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3 Comments

David Stansby Over a year ago

Of course... almost answered myself in the question! Thanks for the answer!

bohontw Over a year ago

can smn explain [group for _, group in grouped] how it works?

Zhenya K. Over a year ago

@bcikili, it is equivalent to [group for name, group in grouped]. The underscore is used to emphasize that we don't care about the name.

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