Python .map Nested Dataframe Dictionary

I have data nested in a dictionary that I would like to recode with another nested dictionary. Diagram here. The files dict is the location of the data I would like to recode based

Solution 1:

Just change the values of the dict df3_01, df3_11 to strings.

In your code:

# df3 are dicts nested within a dictionary (refs)

df3_01 = df3_0.set_index("ID").T.to_dict('list')
for key, value in df3_01.items():
    df3_01[key]=value[0]
df3_11 = df3_1.set_index("ID").T.to_dict('list') # Convert df3 to dictfor key, value in df3_11.items():
    df3_11[key]=value[0]

print(f'df3_01={df3_01}')
print(f'df3_11={df3_11}')


Output:

df3_01={'0': 'Select', '1': 'Male', '2': 'Female'}
df3_11={'0': 'Select',
'1': 'American Indian',
'2': 'Asian',
'3': 'Black or African American',
'4': 'Other'}enter code here

 print('modified df')
 print(df)

 Output:

 modified df
 
    Log Gender  Race    Other
    0   1114    Female  American Indian 1
    1   1115    Female  Asian   4
    2   1116    Female  Black or African American   2
    3   1117    NaN Other   1
    4   1118    Male    NaN 1
    5   1119    Male    Asian   3
    6   120 Female  Black or African American   2enter code here