Any linear algebra looks ugly --

   python: X.dot(Y)
   matlab: X*Y
   R: X %*% Y

It makes less difference when it's only 2 matrices, but when it's 3+ it's far more readable.

pandas has a lot of functionality, but the interface is far inferior to R's data frame, where you have

   df[row predicate, column predicate]

particularly the highly useable intermingling of column access by index or name. reshape2 and plyr are, imo, far more elegant and less wordy apis.

The api to sklearn, while definitely more consistent than R's apis, has a lot more programmer nonsense interjected: imports of random packages, the difference between pandas and numpy that still peeks through the second you step outside of statsmodels, etc.

numpy has a serialization format, while pandas uses pickle or hd5. R just uses save/load, and unlike pickle in my experience, it reliably works.

matplotlib is an ugly api, particularly compared to ggplot.