Pandas: Reducing multi-index to highest available level

Question

I have the following type of a dataframe, values which are grouped by 3 different categories A,B,C:

import pandas as pd
A = ['A1', 'A2', 'A3', 'A2', 'A1']
B = ['B3', 'B2', 'B2', 'B1', 'B3']
C = ['C2', 'C2', 'C3', 'C1', 'C3']
value = ['6','2','3','3','5']

df = pd.DataFrame({'categA': A,'categB': B, 'categC': C, 'value': value})
df

Which looks like:

  categA categB categC value
0     A1     B3     C2     6
1     A2     B2     C2     2
2     A3     B2     C3     3
3     A2     B1     C1     3
4     A1     B3     C3     5

Now, when I want to unstack this df by the C category, .unstack() returns some multi-indexed dataframe with 'value' at the first level and my categories of interest C1, C2 & C3 at the second level:

df = df.set_index(['categA','categB','categC']).unstack('categC')
df

Output:

              value          
categC           C1   C2   C3
categA categB                
A1     B3       NaN    6    5
A2     B1         3  NaN  NaN
       B2       NaN    2  NaN
A3     B2       NaN  NaN    3

Is there a quick and clean way to get rid of the multi-index by reducing it to the highest available level? This is what I'd like to have as output:

categA categB   C1   C2   C3                
A1     B3       NaN    6    5
A2     B1         3  NaN  NaN
       B2       NaN    2  NaN
A3     B2       NaN  NaN    3

Many thanks in advance!

Edit:

print(df.reset_index())

gives:

           categA categB value          
categC                  C1   C2   C3
0          A1     B3   NaN    6    5
1          A2     B1     3  NaN  NaN
2          A2     B2   NaN    2  NaN
3          A3     B2   NaN  NaN    3

Answer 1

Adding reset_index also , unstack with Series

df.set_index(['categA','categB','categC']).value.unstack('categC').reset_index()
Out[875]: 
categC categA categB    C1    C2    C3
0          A1     B3  None     6     5
1          A2     B1     3  None  None
2          A2     B2  None     2  None
3          A3     B2  None  None     3