Split pandas dataframe based on groupby

Store them in a dict, which allows you access to the group DataFrames based on the group keys.

d = dict(tuple(df.groupby('ZZ')))
d[6]

#    N0_YLDF  ZZ        MAT
#1  6.317000   6  11.669069
#2  6.324889   6  11.516454
#5  6.359000   6  11.516454
#6  6.359000   6  11.516454
#9  6.361111   6  11.516454

If you need only a subset of the DataFrame, in this case just the 'NO_YLDF' Series, you can modify the dict comprehension.

d = dict((idx, gp['N0_YLDF']) for idx, gp in df.groupby('ZZ'))
d[6]
#1    6.317000
#2    6.324889
#5    6.359000
#6    6.359000
#9    6.361111
#Name: N0_YLDF, dtype: float64

In R there is a dataframe method called split. This is for all the R users out there:

def split(df, group):
     gb = df.groupby(group)
     return [gb.get_group(x) for x in gb.groups]

There is another alternative as the groupby returns a generator we can simply use a list-comprehension to retrieve the 2nd value (the frame).

dfs = [x for _, x in df.groupby('ZZ')]

gb = df.groupby('ZZ')    
[gb.get_group(x) for x in gb.groups]