pandas: selecting array of index labels with .loc

Question

Consider this dataFrame:

df = pd.DataFrame({u'A': {2.0: 2.2,
  7.0: 1.4,
  8.0: 1.4,
  9.0: 2.2},  u'B': {2.0: 7.2,
  7.0: 6.3,
  8.0: 4.4,
  9.0: 5.0}})

Which looks like this:

      A       B
2    2.2     7.2
7    1.4     6.3
8    1.4     4.4
9    2.2     5.0

I'd like to get indices with label 2and 7 (numbers, not strings)

df.loc[[2, 7]]

gives an error!

IndexError: indices are out-of-bounds

However, df.loc[7] and df.loc[2] work fine and as expected. Also, if I define the dataframe index with strings instead of numbers:

df2 = pd.DataFrame({u'A': {'2': 2.2,
  '7': 1.4,
  '8': 1.4,
  '9': 2.2},
 u'B': {'2': 7.2,
  '7': 6.3,
  '8': 4.4,
  '9': 5.0}})

df2.loc[['2', '8']]

it works fine.

This is not the behavior I expected from df.loc (is it a bug or just a gotcha?) Can I pass an array of numbers as label indices and not just positions?

I can convert all indices to strings and then operate with .loc but it would be very inconvenient for the rest of my code.

Thanks for your time!

Answer 1

This is a bug in 0.12. Version 0.13 fixes this (IOW, label selection, whether number or string should work when you pass a list).

You could do this (uses an internal method though):

In [10]: df.iloc[df.index.get_indexer([2,7])]
Out[10]: 
     A    B
2  2.2  7.2
7  1.4  6.3