How to create mosaic plot from Pandas dataframe with Statsmodels library?

Using Python 3.4, Pandas 0.15 and Statsmodels 0.6.0, I try to create a mosaic plot from a dataframe as described in the Statsmodels documentation. However, I just don't understand how the input has to be formatted that is provided to the `mosaic()` function. Given a simple dataframe: ``` In: myDataframe = pd.DataFrame({'size' : ['small', 'large', 'large', 'small', 'large', 'small'], 'length' : ['long', 'short', 'short', 'long', 'long', 'short']}) Out: length size 0 long small 1 short large 2 short large 3 long small 4 long large 5 short small ``` When trying to create a mosaic plot of this data: ``` from statsmodels.graphics.mosaicplot import mosaic mosaic(data=myDataframe, title='Mosaic Plot') ``` gives `ValueError: cannot label index with a null key` As mosaic plots are a visualization of contingency tables, I tried to create such first with ``` In: myCrosstable = pd.crosstab(myDataframe['size'], myDataframe['length']) Out: length long short size large 1 2 small 2 1 ``` Still, using `myCrosstable` as data argument gives the same error. How does the dataframe have to be formatted in order to get accepted by the `mosaic()` function? The documentation says as explanation for the data argument: Parameters: data : dict, pandas.Series, np.ndarray, pandas.DataFrame ``` The contingency table that contains the data. Each category should contain a non-negative number with a tuple as index. ``` Isn't that what the `pd.crosstab` function returns? If not, how can I convert the dataframe accordingly?