You can create dictionary
of DataFrames
by dict comprehension
:
dfs = {k:v for k, v in df.groupby('A')}
print (dfs)
{0: A B C
0 0 a h
1 0 b i
2 0 c j, 1: A B C
3 1 d k
4 1 e l, 2: A B C
5 2 f m
6 2 g n}
print (dfs[0])
A B C
0 0 a h
1 0 b i
2 0 c j
print (dfs[1])
A B C
3 1 d k
4 1 e l
If necessary you can reset index:
dfs = {k:v.reset_index(drop=True) for k, v in df.groupby('A')}
print (dfs)
{0: A B C
0 0 a h
1 0 b i
2 0 c j, 1: A B C
0 1 d k
1 1 e l, 2: A B C
0 2 f m
1 2 g n}
print (dfs[1])
A B C
0 1 d k
1 1 e l
print (dfs[2])
A B C
0 2 f m
1 2 g n
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