3 ms·

what hoops are you referring to? My phd work was all matlab, and I vastly prefer python for readability and practicality

• x0x0 12y ago
  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.
  • hogu 12y ago
    few things that do not completely address your points, but may help - python 3 (.5?) is adding the @ operator for matrix multiply. Of course this only helps you if your company uses python3 - There are 2 packages (seaborn, ggplot(clone)) which sit on top of matplotlib and provide a much nicer interface for statistical plots
    • rjurney 12y ago
      Too bad Python 3 equals Perl 6. :(