making multiple pandas data frames using a loop or list comprehension

Question

I have a Python data frame that I want to subdivide by row BUT in 32 different slices (think of a large data set chopped by row into 32 smaller data sets). I can manually divide the data frames in this way:

df_a = df[df['Type']=='BROKEN PELVIS']

df_b = df[df['Type']=='ABDOMINAL STRAIN']

I'm assuming there is a much more Pythonic expression someone might like to share. I'm looking for something along the lines of:

for i in new1:
    df_%s= df[df['#RIC']=='%s'] , %i

Hope that makes sense.

Andy Hayden · Accepted Answer · 2014-02-22 06:42:59Z

5

In these kind of situations I think it's more pythonic to store the DataFrames in a python dictionary:

injuries = {injury: df[df['Type'] == injury] for injury in df['Type'].unique()}

injuries['BROKEN PELVIS']  # is the same as df_a above

Most of the time you don't need to create a new DataFrame but can use a groupby (it depends what you're doing next), see http://pandas.pydata.org/pandas-docs/stable/groupby.html:

g = df.groupby('Type')

Update: in fact there is a method get_group to access these:

In [21]: df = pd.DataFrame([['A', 2], ['A', 4], ['B', 6]])

In [22]: g = df.groupby(0)

In [23]: g.get_group('A')
Out[23]:
   0  1
0  A  2
1  A  4

Note: most of the time you don't need to do this, apply, aggregate and transform are your friends!

edited Feb 22, 2014 at 6:42

answered Feb 22, 2014 at 4:09

Andy Hayden

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1 Comment

Chase CB Over a year ago

thanks for the input really appreciate it. i want to write something funny to let you know that i'm extremely grateful but, alas, my sense of humor is a little dark and i don't want to offend the people of stack overflow.

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