Pandas Reindex And Fill Missing Values: "index Must Be Monotonic"

In answering this stackoverflow question, I found some interesting behavior when using a fill method while reindexing a dataframe. This old bug report in pandas says that df.reinde

Solution 1:

Some element of reindex requires the incoming index to be sorted. I'm deducing that when method is passed, it fails to presort the incoming index and subsequently fails. I'm drawing this conclusion based on the fact that this works:

print df.sort_index().reindex(newIndex.sort_values(), method='ffill')

Solution 2:

It seems that this needs to be done on the columns as well.

In[76]: frame = DataFrame(np.arange(9).reshape((3, 3)), index=['a', 'c', 'd'],columns=['Ohio', 'Texas', 'California'])

In[77]: frame.reindex(index=['a','b','c','d'],method='ffill',columns=states)
---> ValueError: index must be monotonic increasing or decreasing

In[78]: frame.reindex(index=['a','b','c','d'],method='ffill',columns=states.sort())

Out[78]:
  Ohio  Texas  California
a     012
b     012
c     345
d     678