How to get away with a multidimensional index in pandas

Question

In Pandas, what is a good way to select sets of arbitrary rows in a multiindex?

df = pd.DataFrame(columns=[\'A\', \'B\', \'C\'])
df[\'A\'] = [\'a\', \'a\', \         


        

Answer 1

In newer versions of pandas you can simply use .iloc for row indexing.

df = pd.DataFrame(columns=['A', 'B', 'C'])
df['A'] = ['a', 'a', 'b', 'b']
df['B'] = [1,2,3,4]
df['C'] = [1,2,3,4]
df.iloc[[0, 3]][['A', 'B']]

Answer 2

You indeed cannot index with a DataFrame directly, but if you convert it to an Index object, it does the correct thing (a row in the DataFrame will be regarded as one multi-index entry):

In [43]: pd.Index(the_indices_we_want)
Out[43]: Index([(u'a', 1), (u'b', 4)], dtype='object')

In [44]: df.ix[pd.Index(the_indices_we_want)]
Out[44]:
     C
A B
a 1  1
b 4  4

In [45]: df.ix[[tuple(x) for x in the_indices_we_want.values]]
Out[45]:
     C
A B
a 1  1
b 4  4

This is a somewhat cleaner. And with some quick tests it seems to be a bit faster (but not much, only 2 times)