please advise how optimal solve the following task:

I have pandas dataframe:

df.shape is (100,3). 1st column values from 0 to 5, 2nd: 0-8, 3rd: 0-10

and 3 dicts with different key:values.

dict1 = {0: 'a',
 1: 'b', ..., 5: 'xx'}

dict2 = {0: 'aa',
 1: 'bb', ..., 8: 'yy'}

dict2 = {0: 'aaa',
 1: 'bbb', ..., 10: 'zzz'}

the question is how to replace values in dataframe by keys from dicts?

something like that but for all columns:

df['1st'].map({v: k for v, k in enumerate(dict1)}).to_frame()

CodePudding user response：

Use zip with Series.map for columns in list:

dict1 = {0: 'a', 1: 'b', 3:'r',2:'y', 5: 'xx'}
dict2 = {0: 'aa',6:'ww', 1: 'bb',  8: 'yy'}
dict3 = {0: 'aaa', 3:'ree',5:'eey', 1: 'bbb', 10: 'zzz'}

for c, d in zip(['1st', '2nd', '3rd'], [dict1, dict2, dict3]):
    df[c] = df[c].map(d)
print (df)
  1st 2nd  3rd
0   b  bb  zzz
1   b  ww  ree
2   r  yy  eey
3  xx  bb  eey
4   y  bb  zzz
5  xx  bb  bbb