Pandas shuffle rows at a certain level

pandas, python

Solution

The `reindex` method can accomplish this when passed a reordered array of tuples matching the desired order. At which point, reordering can be done as best fits your problem. For example:

In [38]: df
Out[38]: 
            A         B         C
0 0 -1.725337  0.111493  0.178294
  1 -1.809003 -0.614219 -0.931909
  2  0.621427 -0.186233  0.254727
1 0 -1.322863  1.242415  1.375579
  1  0.249738 -1.280204  0.356491
  2 -0.743671  0.325841 -0.167772
2 0 -0.070937  0.401172 -1.790801
  1  1.433794  2.257198  1.848435
  2 -1.021557 -1.054363 -1.485536

In [39]: neworder = [1, 0, 2]

In [41]: newindex = sorted(df.index, key=lambda x: neworder.index(x[0]))

In [42]: newindex
Out[42]: 
[(1L, 0L),
 (1L, 1L),
 (1L, 2L),
 (0L, 0L),
 (0L, 1L),
 (0L, 2L),
 (2L, 0L),
 (2L, 1L),
 (2L, 2L)]

In [43]: df.reindex(newindex)
Out[43]: 
            A         B         C
1 0 -1.322863  1.242415  1.375579
  1  0.249738 -1.280204  0.356491
  2 -0.743671  0.325841 -0.167772
0 0 -1.725337  0.111493  0.178294
  1 -1.809003 -0.614219 -0.931909
  2  0.621427 -0.186233  0.254727
2 0 -0.070937  0.401172 -1.790801
  1  1.433794  2.257198  1.848435
  2 -1.021557 -1.054363 -1.485536

Problem

I have a Pandas `DataFrame` using a `MultiIndex` on the rows: ``` index = pandas.MultiIndex.from_tuples(list(itertools.product(range(3), range(3)))) df = pandas.DataFrame(numpy.random.randn(9,3), index=index, columns=['A', 'B', 'C']) A B C 0 0 2.400417 0.698638 1.231540 1 -0.023154 -2.110450 0.774964 2 -1.282392 -0.062794 1.471655 1 0 -1.081853 0.261876 -1.771075 1 -2.013747 -0.377957 -0.393802 2 1.711172 -0.552468 1.018727 2 0 0.155821 -0.222691 0.496586 1 0.563638 -0.756709 1.050212 2 -1.446159 -0.891549 0.256695 ``` I would like to shuffle this DataFrame on the first level of the index, so a possible result would be: ``` A B C 1 0 -1.081853 0.261876 -1.771075 1 -2.013747 -0.377957 -0.393802 2 1.711172 -0.552468 1.018727 0 0 2.400417 0.698638 1.231540 1 -0.023154 -2.110450 0.774964 2 -1.282392 -0.062794 1.471655 2 0 0.155821 -0.222691 0.496586 1 0.563638 -0.756709 1.050212 2 -1.446159 -0.891549 0.256695 ```

Original source