replace - python pandas replacing strings in dataframe with numbers

Question

Is there anyway to use the mapping function or something better to replace values in an entire dataframe?

I only know how to perform the mapping on series.

I would like to replace the strings in the 'tesst' and 'set' column with a number for example set = 1, test =2

Here is a example of my dataset: (Original dataset is very large)

ds_r
  respondent  brand engine  country  aware  aware_2  aware_3  age tesst   set
0          a  volvo      p      swe      1        0        1   23   set   set
1          b  volvo   None      swe      0        0        1   45   set   set
2          c    bmw      p       us      0        0        1   56  test  test
3          d    bmw      p       us      0        1        1   43  test  test
4          e    bmw      d  germany      1        0        1   34   set   set
5          f   audi      d  germany      1        0        1   59   set   set
6          g  volvo      d      swe      1        0        0   65  test   set
7          h   audi      d      swe      1        0        0   78  test   set
8          i  volvo      d       us      1        1        1   32   set   set

Final result should be

 ds_r
  respondent  brand engine  country  aware  aware_2  aware_3  age  tesst  set
0          a  volvo      p      swe      1        0        1   23      1    1
1          b  volvo   None      swe      0        0        1   45      1    1
2          c    bmw      p       us      0        0        1   56      2    2
3          d    bmw      p       us      0        1        1   43      2    2
4          e    bmw      d  germany      1        0        1   34      1    1
5          f   audi      d  germany      1        0        1   59      1    1
6          g  volvo      d      swe      1        0        0   65      2    1
7          h   audi      d      swe      1        0        0   78      2    1
8          i  volvo      d       us      1        1        1   32      1    1

grateful for advise,

Answer 1

What about DataFrame.replace?

In [9]: mapping = {'set': 1, 'test': 2}

In [10]: df.replace({'set': mapping, 'tesst': mapping})
Out[10]: 
   Unnamed: 0 respondent  brand engine  country  aware  aware_2  aware_3  age  
0           0          a  volvo      p      swe      1        0        1   23   
1           1          b  volvo   None      swe      0        0        1   45   
2           2          c    bmw      p       us      0        0        1   56   
3           3          d    bmw      p       us      0        1        1   43   
4           4          e    bmw      d  germany      1        0        1   34   
5           5          f   audi      d  germany      1        0        1   59   
6           6          g  volvo      d      swe      1        0        0   65   
7           7          h   audi      d      swe      1        0        0   78   
8           8          i  volvo      d       us      1        1        1   32   

  tesst set  
0     2   1  
1     1   2  
2     2   1  
3     1   2  
4     2   1  
5     1   2  
6     2   1  
7     1   2  
8     2   1  

As @Jeff pointed out in the comments, in pandas versions < 0.11.1, manually tack .convert_objects() onto the end to properly convert tesst and set to int64 columns, in case that matters in subsequent operations.