pandas, matplotlib, use dataframe index as axis tick labels

I am using matplotlib's imshow() function to show a pandas.DataFrame.

I would like the labels and ticks for both x and y axes to be drawn from the DataFrame.index and DataFrame.columns lists, but I can't figure out how to do it.

Assuming that data is a pandas.DataFrame:

>>> print data
<class 'pandas.core.frame.DataFrame'>
Index: 201 entries,  1901 to  2101
Data columns:
jan    201  non-null values
feb    201  non-null values
mar    201  non-null values
apr    201  non-null values
may    201  non-null values
jun    201  non-null values
jul    201  non-null values
aug    201  non-null values
sep    201  non-null values
oct    201  non-null values
nov    201  non-null values
dec    201  non-null values

When I do this:

ax1 = fig.add_subplot(131, xticklabels=data.columns, yticklabels=data.index)
ax1.set_title("A")
ax1.tick_params(axis='both', direction='out')
im1 = ax1.imshow(data, 
                 interpolation='nearest', 
                 aspect='auto',
                 cmap=cmap )

I end up with nicely spaced tick labels on the y axis of the image, but the labels are 1901-1906 instead of 1901 thru 2101. Likewise, the x axis tick labels are feb-jul instead of jan-dec.

If I use

ax1 = fig.add_subplot(131) # without specifying tick labels

Then I end up with the axis tick labels simply being the underlying ndarray index values (i.e. 0-201 and 0-12). I don't need to modify the spacing or quantity of ticks and labels, I just want the label text to come from the DataFrame index and column lists. Not sure if I am missing something easy or not?

Thanks in advance.