MATLAB, Python and R are commonly used in bioacoustics. Whilst all three languages are excellent choices, it is difficult to ask entrants into bioacoustics to learn all three. I have tried to put together a table with a summary of what each language is good/bad at - any thoughts on the scores/ additional rows to add?  

|    | MATLAB         |Python   | R      |
| -------- | -------------- |---------|-------|
|**How easy/intuitive is it to get started**| Excellent (totally integrated code and IDE)| Good (Spyder IDE is great) | Good (R Studio)
| **Open source**   | No            | Yes | Yes
| **Price**    | *Very expensive* (but often paid for in academia)| Free | Free
| **Documentation**   | Excellent (consistently comprehensive help files) | Good (help depends on package) | Good (help depends on package)
| **Speed**   | Slow| Slow | Slow |
| **Audio functions e.g. opening files etc.** | Excellent (includes X3 libraries) | Excellent | Excellent |
| **Signal processing functions** | Excellent (includes GUI toolbox) | Excellent (scipy.signal)| Good |
| **Deep learning tools** | Good | Excellent (the default language for Deep Learning) | Medium? | 
| **Statistics** | Medium (patchy at best) | Medium? | Excellent (designed for stats) |
| **Package Management** | Less choice but easy and integrated | Lots of packages - can be confusing | Easy in R studio but lots of competing packages |
| **Building UIs (graphical programs)** | Easy and integrated | More complex (and perhaps powerful) with lots of different packages e.g.  Tkinter, wxPython, and PyQt.  | Easy with R shiny |
| **Use with PAMGuard** | Well developed library to read PAMGuard output | Library planned for 2023 | Well developed library to read PAMGuard output |