Pandas Dataframe split columns list simultaneously

I have a dataframe like this:

data = {'period':[
                  [{'periods': [{'From': '19', 'To': '21'}]}, {'periods': [{'From': '13', 'To': '30'}]}, {'periods': [{'From': '02', 'To': '26'}]}],  
                  [{'periods': [{'From': '21', 'To': '26'}]}, {'periods': [{'From': '22', 'To': '27'}]}, {'periods': [{'From': '05', 'To': '07'}]}]
                 ], 
        'Age':[
                  ['9820', '5480', '8535'], 
                  ['1524', '6555', '4555']
              ], 
        'Address':[
                    '2', 
                    '3'
                   ]
        }

df = pd.DataFrame(data) 

I would like to transform my dataset in this way:

data = {'Name':[
{'periods': [{'From': '19', 'To': '21'}]}, 
{'periods': [{'From': '13', 'To': '30'}]}, 
{'periods': [{'From': '02', 'To': '26'}]}
,  
{'periods': [{'From': '21', 'To': '26'}]}, 
{'periods': [{'From': '22', 'To': '27'}]}, 
{'periods': [{'From': '05', 'To': '07'}]}
], 
        'Age':['9820', '5480', '8535','1524', '6555', '4555'], 
        'Address':['2', '2', '2', '3', '3', '3']}

df = pd.DataFrame(data) 

I am struggling to find a way to do explode() on two columns simultaneously so that the first element of the list in the column period belongs to the same row of the first element of the list in the column Age.

period list and age list are always of equal size.

I tried doing this:

df = df.reset_index()
uid = df.set_index('index')['period'].explode().reset_index()
df = uid.join(df['Age'].explode())

but it does not show the Address column anymore

I would appreciate any help. Thank you

df.apply(pd.Series.explode).reset_index(drop=True)

                                      period   Age Address
0  {'periods': [{'From': '19', 'To': '21'}]}  9820       2
1  {'periods': [{'From': '13', 'To': '30'}]}  5480       2
2  {'periods': [{'From': '02', 'To': '26'}]}  8535       2
3  {'periods': [{'From': '21', 'To': '26'}]}  1524       3
4  {'periods': [{'From': '22', 'To': '27'}]}  6555       3
5  {'periods': [{'From': '05', 'To': '07'}]}  4555       3

names = df.period.explode()
ages = df.Age.explode()

pd.DataFrame({'Name':names, 'Age':ages, 'Address':df.Address.reindex(ages.index)})

                                        Name   Age Address
0  {'periods': [{'From': '19', 'To': '21'}]}  9820       2
0  {'periods': [{'From': '13', 'To': '30'}]}  5480       2
0  {'periods': [{'From': '02', 'To': '26'}]}  8535       2
1  {'periods': [{'From': '21', 'To': '26'}]}  1524       3
1  {'periods': [{'From': '22', 'To': '27'}]}  6555       3
1  {'periods': [{'From': '05', 'To': '07'}]}  4555       3