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> And it's really hard to beat ggplot.

To be honest, matplotlib seems a good contender to me (http://matplotlib.org/).

Also, what's wrong with comparing R to Pandas/Numpy ? They can only be used from within Python, right?

Edit: just realised from another comment that Pandas/Numpy can be accessed from R, too.




> > And it's really hard to beat ggplot.

> To be honest, matplotlib seems a good contender to me (http://matplotlib.org/).

They're quite different, though, and I can see why many prefer ggplot. It's a declarative, domain-specific language that implements a Tufte-inspired "grammar of graphics" (hence the gg- in the name; see section 1.3 of [1], and [2,3]) for very fast and convenient interactive plotting, whereas matplotlib is just a clone of MATLIB's procedural plotting API.

[1] http://www.amazon.com/ggplot2-Elegant-Graphics-Data-Analysis...

[2] http://www.amazon.com/The-Grammar-Graphics-Statistics-Comput...

[3] http://vita.had.co.nz/papers/layered-grammar.html


"matplotlib seems a good contender to me'

I've waxed lyrical about Python all over this thread, but here you have to give the medal to R. Matplotlib is one of my least favourite libraries to use, been doing it for almost 2 years, and I still spend half my time buried in the documentation trying to figure out how I'm supposed to move the legend slightly to the right or whatever.

ggplot probably has slightly less flexibility overall (mpl is monolithic), but for just doing easy things that you need 99% of the time, ggplot is king.


There is a gpplot clone in python. Also bokeh is starting to develop a grammar of graphics interface. Then there is seaborn and mbplot. Lots of stuff besides mplotlib


I must give you that after few years of using it, I still have to look for documentation for elementary things.

I am not familiar with ggplot, so I wasn't comparing them on the ground of the easiness of use, but by looking at some ggplot examples, they looked like something you can do with matplotlib, too, so I pointed that option out, too.


i couldnt agree more - the API seems very confusing and the examples provided are shitty in my opinion


> what's wrong with comparing R to Pandas/Numpy

Absolutely nothing.

I was referring to the article title that is was an R vs. Python comparison. Python is so much more in terms of a general purpose language than R is. Similarly, R is much more in terms of stats (built-in) than Python. I just thought that it would be more accurate to call the article an R vs. Pandas/NumPy comparison.

Even though both of them need an extra plotting library to make publication quality plots. Matplotlib isn't bad by any means - and it's gotten better over the years. But R/ggplot2 produces nicer plots (IMO). I'm not sure that I'd export data from Python into R just for ggplot, but I might.


Thanks for the clarification. I am sorry I had got your comment in the wrong way.

I am not that familiar with ggplot myself, but I'll give it a go as soon as I'll have the chance.


matplotlib seems a good contender to me

On paper perhaps, less so in application. Sure you can probably make matplotlib do everything ggplot does with enough work, but working with ggplot is just so much quicker easier and more fun.

And I say that as someone who does all his data analysis in Python.


I have rewritten the python ggplot to put it on per with ggplot2.

You can try out my dev version [1] (rewrite branch). It will be nearly API compatible.

[1] https://github.com/has2k1/ggplot


Please write a blog post when you are done?! This will be huge :)


Even regular R plotting is still far easier and more intuitive than matplotlib, not just ggplot.


I completely agree. ggplot is the only reason why I sometimes use R.


I don't have a lot of experience with either, but I was close to really digging in and learning R just for the ease of use of ggplot.

I tried the ggplot for python (ggplot.yhathq.com/) but eventually settled for seaborn (http://stanford.edu/~mwaskom/software/seaborn/). It is really quite easy to get most of the common plots that I wanted and hasn't let me down yet. The standard plots look SO much better than the standard plots of MPL without a lot of customization.


Ggplot for python is almost done. there is an active dev branch


matplot allows you to create almost any chart you want. However, it is very low level.

On the other hand, with ggplot, you can create a good enough chart in couple of lines of code almost for any data.

BTW, there's a ggplot port for a Python: http://ggplot.yhathq.com/


Matplotlib can produce high quality plots. But it requires lots of code, and hours of digging around the API docs and tweaking subclasses.




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