Map the multiple value dictionary with a dataframe column

I have a dictionary with multiple values for 1 key. Now, I need to map them with the dataframe column. Any idea how can I solve this?

Dictionary

Keys_nd_Values = {'ABCD'   : [223, 343, 432],
                  'ZXS'    : ['S23', 'GT4','98J']}

Data

   A        B      C
12525    1FWE23   223
14654    14654    S23
24798    24798    223
38945    38945    223
46456    46485    GT4
AD545    45346    98J
A5D66    A5D66    432

Expected

   A        B      C
12525    1FWE23   ABCD
14654    14654    ZXS
24798    24798    ABCD
38945    38945    ABCD
46456    46485    ZXS
AD545    45346    ZXS
A5D66    A5D66    ABCD

Answer

First we convert the Keys_nd_Values to a df and convert the rows to columns. The function we wrote later does this: get the value of the column if the row value exists as a column in the df named control.

dfx=pd.DataFrame(Keys_nd_Values)
control = dfx.melt(ignore_index = False).set_index('value').T

             223    343     432     S23     GT4  98J
variable    ABCD    ABCD    ABCD    ZXS     ZXS  ZXS

def check(a):
    if a in control.columns.to_list():
        return control[a][0]
    else:
        return a
        
for i in df1.columns:
    df1[i]=df1[i].apply(check)
        
print(df1)
    A       B       C
0   12525   1FWE23  ABCD
1   14654   14654   ZXS
2   24798   24798   ABCD
3   38945   38945   ABCD
4   46456   46485   ZXS
5   AD545   45346   ZXS
6   A5D66   A5D66   ABCD