使用整数列表/元组替换Pandas DataFrame列中的值

Question

I want to replace 3 columns of a pandas dataframe df containing chess square coordinates as strings, using a dictionary chess_dict to map them to Cartesian coordinates in the form of 2x1 integer lists.

I've tried using the replace method, but for some reason it replaces with the first integer of the list only, instead of both

eg. ('a1','h6') -> ([0,0],[7,5])

>>>chess_dict
 {'a1': [0, 0],
 'a2': [0, 1],
 ...
 'h5': [7, 4],
 'h6': [7, 5],
 'h7': [7, 6],
 'h8': [7, 7]}

>>>df
      WK  WR  BK plays outcome
0     h4  e6  a4     b       w
1     a6  h4  g8     w       w
2     f5  a3  d1     w       w
3     c2  h3  f5     w       w
...
>>>df.ix[:,0].replace(chess_dict, inplace=True)
>>>df.ix[:,1].replace(chess_dict, inplace=True)
>>>df.ix[:,2].replace(chess_dict, inplace=True)
>>>df
      WK  WR  BK plays outcome
0      7   4   0     b       w
1      5   3   7     w       w
2      5   0   3     w       w
3      1   2   4     w       w
...

• I have tried replacing with the Cartesian coords as strings, and afterwards converting the string to integer lists and it worked, but since I'm new to python and pandas I'm guessing there is a simpler way using replace but there is something basic I'm missing which I just can't seem to figure out.

• I've also tried this syntax with the same results:

   df.ix[:,0].replace(to_replace = chess_dict.keys(), value = chess_dict.values(), inplace=True) 

• I've also tried using integer tuples for the Cartesian coords (0,0), (0,1), etc., but now only the last instead of first value is inserted in the DataFrame column

   WK WR BK plays outcome 0 3 g7 b4 bw 1 3 h7 d1 bw 2 3 h6 f5 ww 3 6 d5 b1 bw 

Answer 1

option 1

chess_dict = {
    r + c: [i, j]
        for i, r in enumerate(list('abcdefgh'))
        for j, c in enumerate(list('12345678'))
}

df.iloc[:, :3].stack().map(chess_dict).unstack().join(df.iloc[:, 3:])

       WK      WR      BK plays outcome
0  [7, 3]  [4, 5]  [0, 3]     b       w
1  [0, 5]  [7, 3]  [6, 7]     w       w
2  [5, 4]  [0, 2]  [3, 0]     w       w
3  [2, 1]  [7, 2]  [5, 4]     w       w

option 2

df.applymap(lambda x: chess_dict.get(x, x))

       WK      WR      BK plays outcome
0  [7, 3]  [4, 5]  [0, 3]     b       w
1  [0, 5]  [7, 3]  [6, 7]     w       w
2  [5, 4]  [0, 2]  [3, 0]     w       w
3  [2, 1]  [7, 2]  [5, 4]     w       w