Set multi column index in pandas

Question

I make dataframe like this.

df = pd.DataFrame({
    \'class\' : [\'A\', \'A\', \'A\', \'A\', \'A\', \'B\', \'B\', \'B\', \'B\', \'B\'],
    \'number\' : [1,2         


        

Answer 1

I like @jezrael answer a lot, but just for completeness - you can also use pandas.DataFrame.pivot_table instead of set_index + unstack:

>>> df.pivot_table(index='number', columns='class').swaplevel(axis=1).sort_index(1)
class        A            B     
       english math english math
number                          
1           40   90      87   67
2           21   20      89   89
3           68   50      54   79
4           89   30      21   45
5           90   57      23   23

Answer 2

I think you need set_index with unstack for reshaping, then swap levels in MultiIndex in columns by swaplevel and last sort columns by sort_index:

df1 = df.set_index(['number','class']).unstack().swaplevel(0,1,1).sort_index(1)

print (df1)
class        A            B     
       english math english math
number                          
1           40   90      87   67
2           21   20      89   89
3           68   50      54   79
4           89   30      21   45
5           90   57      23   23

Another solution with stack and unstack:

print (df.set_index(['number','class']).stack().unstack([1,2]))
class        A            B     
       english math english math
number                          
1           40   90      87   67
2           21   20      89   89
3           68   50      54   79
4           89   30      21   45
5           90   57      23   23