I have a pandas dataframe as follows:
a b c
0 1.0 NaN NaN
1 NaN 7.0 5.0
2 3.0 8.0 3.0
3 4.0 9.0 2.0
4 5.0 0.0 NaN
Is there a simple way to split the dataframe into multiple dataframes based on non-null values?
a
0 1.0
b c
1 7.0 5.0
a b c
2 3.0 8.0 3.0
3 4.0 9.0 2.0
a b
4 5.0 0.0
Using groupby with dropna
for _, x in df.groupby(df.isnull().dot(df.columns)):
print(x.dropna(1))
a b c
2 3.0 8.0 3.0
3 4.0 9.0 2.0
b c
1 7.0 5.0
a
0 1.0
a b
4 5.0 0.0
We can save them in dict
d = {y : x.dropna(1) for y, x in df.groupby(df.isnull().dot(df.columns))}
More Info using the dot to get the null column , if they are same we should combine them together
df.isnull().dot(df.columns)
Out[1250]:
0 bc
1 a
2
3
4 c
dtype: object
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