I want to insert column in cross-tabulation?

Question

I have Pandas cross-tabulation object.

| Age Category | A | B  | C  | D |
|--------------|---|----|----|---|
| 21-26        | 2 | 2  | 4  | 1 |
| 26-31        | 7 | 11 | 12 | 5 |
| 31-36        | 3 | 5  | 5  | 2 |
| 36-41        | 2 | 4  | 1  | 7 |
| 41-46        | 0 | 1  | 3  | 2 |
| 46-51        | 0 | 0  | 2  | 3 |
| Above 51     | 0 | 3  | 0  | 6 |

If I am doing age.dtypes this is giving me output

Age Category
A int64
B int64
C int64
D int64 
dtype: object

But I want Age Category should also be object . If it need to insert one more column for that that would be fine. So that the age.dtypes should show something like this

Age Category
Age Category  object
A             int64
B             int64
C             int64
D             int64 
dtype: object

Thank you for your time and consideration

Answer 1

I think you need DataFrame.reset_index for convert index to column and then if necessary rename_axis :

age = age.reset_index().rename_axis(columns='Age Category')
print (age.dtypes)
Age Category
Age Category    object
A                int64
B                int64
C                int64
D                int64
dtype: object

EDIT:

If columns names are categoricals use CategoricalIndex.add_categories before:

age.columns = age.columns.add_categories(['Age Category'])
age = age.reset_index().rename_axis(columns='Age Category')

print (age.dtypes)
Age Category
Age Category    object
A                int64
B                int64
C                int64
D                int64
dtype: object