nested dictionary --> dataframe with multi - columns

kdict = {'A': {'a': 1, 'b': 2}, 'B': {'a': 3, 'b': 4}, 'C': {'a': 5, 'b': 6}}

df5 = pd.DataFrame.from_dict(kdict, orient='index').stack()
df5.columns = ['a', 'b', 'a', 'b', 'a', 'b']
print(df5)

but i want to get the result, as below --

how can i get this form, as above ?

You can use pivot_table after resetting your index:

import pandas as pd

kdict = {'A': {'a': 1, 'b': 2}, 'B': {'a': 3, 'b': 4}, 'C': {'a': 5, 'b': 6}}

df5 = pd.DataFrame.from_dict(kdict, orient='index').stack()
print(df5.reset_index().pivot_table(columns=['level_0', 'level_1']))

Output:

level_0  A     B     C   
level_1  a  b  a  b  a  b
0        1  2  3  4  5  6

You can try to convert the Series to DataFrame and transpose:

print(df5.to_frame().T)

Prints:

   A     B     C   
   a  b  a  b  a  b
0  1  2  3  4  5  6