7 ms·

Ggplot2 for python

187 points by martingoodson 13y ago

hatmatrix 13y ago
> I've tried other libraries like Bockah and d3py but what I really want is ggplot2. I wonder if that's meant to say, "bokeh"... and I would be interested to know the major differences. This library might be better than bokeh if there's no dependencies on coffeescript and such. But I wonder in what way this is un-pythonic, except perhaps in its imitation of R syntax. But ggplot2 is also not very much like the rest of R either.
- darkarmani 13y ago
  I think you only need coffeescript if you want to develop bokeh not if you want to use it.
- paddy_m 13y ago
  I'm a Bokeh developer. We have plans to make the coffescript situation a lot easier to deal with, this fix should be coming soon.
marrone12 13y ago
I'm really excited for this. I might finally switch to python now!
- dlib 13y ago
  Indeed, there's some incredible work put into the Python data analysis toolkit. Pandas is very impressive. However, no GGplot was holding me back from switching but this and improvements to other graphing libraries really make me want to use Python in my next projects.
  - rprospero 13y ago
    As someone who does all my data analysis in Python, I'm curious what it is about GGplot that it's absence was a deal breaker for you? It's obviously quite powerful, considering all the excitement this port has generated, but I haven't seen anything explain what it provides over other plotting solutions.
    - has2k1 13y ago
      You need understand what ggplot is all about, i.e a structured/formulaic way to think about and build graphs. Explaining it cannot possibly do it justice. You have dive into it, even a little bit and the way you see graphs and plots totally changes, you immediately buy into it and would never wish to go back. I haven't really said anything to give you a sense of comparison. It's kind of like PGs essay (http://www.paulgraham.com/avg.html http://www.paulgraham.com/avg.html) about how the merits of higher level programming (specifically in lisp) can hardly be explained to those who have not been exposed to it.
      - rprospero 13y ago
        The merits of higher level programming are hard to explain to a Blub programmer, but the differences are trivial to explain. I can tell a C programmer that Lisp has automatic memory management, higher order functions, macros, and atoms. She may not know why those matter, but I can tell her they exist. I can tell a Python programmer that Haskell has pure functions, Monads, Arrows, and an advanced type system. He'll think those will make his life harder, but he'll know they're there. What makes GGplot different? I know that I won't understand why this difference matters until I've played with it, but it will at least tell me where to start playing.
        has2k1 13y ago
        I mentioned the difference "a structured/formulaic way to think about and build graphs" This is what plotting using the "grammar" provides. Each plot is a like a sentence, for a sentence can be composed using some of the following - verb, noun, adverb, adjective, interjection, pronoun, proposition, conjunction. Alike, ggplot2 allows you to think of a graph in terms of layers, which layers can have different components that describe the "geometry" or "statistics" of the plot. Plus, there is a lot more. You could probably describe your favourite plotting package as structured and formulaic, but an experience with ggplot2 would convince you otherwise.
        peatmoss 13y ago
        Here's another stab at why ggplot2 is a Good Thing. In the easiest plotting case, there is a function that builds exactly the visualization that you're looking for. This is great as long as you don't need to do anything that deviates from the normal set of barplots, histograms, linegraphs, piecharts (shudder), etc. But let's say you need something a little different. Maybe you want to add additional dimensions to that dot plot. Maybe you want the dots' size or color to be mapped to different aspects of your data. In a world without ggplot2 (or more generally the grammar of graphics), you're pretty much stuck going to a very primitive drawing system in which you're specifying the virtual path of a pen, or working with basic geometric figures. The grammar of graphics and ggplot2 occupy a sweet middle ground between being able to simply pick an off-the-shelf visualization, and needing to draw the whole damn works manually. And because the grammar really is consistent, you can also play with different facets of your data and build completely different charts to see which is better at presenting your thesis. In short, ggplot2 rocks, Hadley/Leland rock, and a port of ggplot2 to Python is nothing but good news for the Python community.
Osmium 13y ago
This is really exciting! I've always liked ggplot2 but sadly struggled with R syntax (the only time I ever used it was for ggplot2, and found it really confusing). For anyone reading this, I don't think this is intended to replace e.g. matplotlib which I suspect is more powerful overall. It's more for creating good looking, publication-quality graphs. A lot of thought has gone into ggplot2's default theme. A lot of influence from Tufte et al. if I remember rightly. Though, sadly, it looks like this port doesn't replicate ggplot2's graphs pixel-for-pixel, which is a shame. Edit: Incidentally if anyone has a recommendation for a good graphing app for OS X, I'd be all ears. I still haven't found a good one. I usually use Plot (http://plot.micw.eu http://plot.micw.eu) which is great (scriptable, produces good looking graphs) but has a bit of a clunky interface. I personally find DataGraph's interface horrendous, even though its graphs are good, and Excel takes forever to make anything remotely decent. matplotlib and its ilk are fine but require custom scripting. I've been using xmgrace recently simply because it launches quickly, but it's (understandably) not retina and not native and just a pain really. What I'd give for a nice graphing app...
- xioxox 13y ago
  You could try my Veusz http://home.gna.org/veusz/ http://home.gna.org/veusz/ package. GUI, scripting and multiplatform. Quite a few satisfied users!
  - Osmium 13y ago
    Thanks for the recommendation :)
  - hatmatrix 13y ago
    Wow, I'm surprised I haven't heard of this. Looks like it could be a good competitor to the Sigmaplot/Origin/Igor pro audience?
    - xioxox 13y ago
      Hopefully it's a good competitor to these (people tell me so), but I hadn't used them before embarking on Veusz! I mainly got annoyed with the state of command-line plotting facilities in astronomy and unix (like IDL, gnuplot, etc). I started with the idea that graphs should be built in an object-oriented fashion out of widgets. The widgets are arranged in a tree, a page holds a graph or a grid of graphs and a graph has axes and plotting widgets, and so on. Each widget has a set of properties and formatting settings which can be changed. It's now gained more data manipulation abilities. Data is stored in named datasets, linked to external files or entered manually, or you can even capture it from sockets or external programs. You can easily write a plugin to load your own file format. There are a set of data manipulation plugins for filtering and so on (again you can write your own). When plotting, you can just enter expressions to investigate your data. Most of Veusz is written in Python with PyQt. There's a bit of C++ code to handle the inner loops, but it's pretty responsive. The next release should support Python 3, too. One nice thing is that the saved files are simply python commands to regenerate the plot, so it's easy for the user to automate making plots. You can also use it as a python module for plotting, using the same command interface as the saved plots use.
marcosscriven 13y ago
This is fantastic - I remember the pain of sorting out R issues for some finance analysts who were wedded to ggplot. So much better to be able to do it in Python.
dkroy 13y ago
Is there a reason that the dependencies are not installed via the pip call for ggplot? I ask this out of ignorance, not trying to be facetious.
- gh02t 13y ago
  At times numpy/scipy/matplotlib have proven pretty troublesome to install with pip. I think they have it working now, but it's still not 100% reliable.
  - jofer 13y ago
    The main problem is that they have system library dependencies that pip doesn't handle.
    - andrewryno 13y ago
      I think all you need is build-essentials and python-dev.
      - spiffworks 13y ago
        Nope, numpy needs libblas and scipy needs libatlas, both of which have to installed from the system package manager. I slap my forehead every time I move to a new system and find that the pip install in the virtualenv failed.
      - jofer 13y ago
        Matplotlib depends on freetype, libpng, and libjpeg as well. Numpy can be built without any external dependencies, but it will be a very slow installation. You're better off with an accelerated BLAS library (e.g. ATLAS/MKL/etc) and some sort of LAPACK library. Some of numpy's functionality also needs a fortran compiler to build. At any rate, there are other system dependencies beyond a basic compiler and the header files for python.
        andrewryno 13y ago
sonabinu 13y ago
Awesome!
Blahah 13y ago
ggplot is a beautiful thing - excellent job porting it to python. I only wish something similar were available for ruby.
rcarmo 13y ago
This is amazing. FYI, this works out of the box with Mac OS X Lion's system Python and the gfortran compiler from homebrew - that's the only thing I need to install separately (Xcode and brew are required to install that, of course, but most people doing any sort of coding seem to have them anyway). Also, a tip for those of you wanting to do the same: I'm running IPython notebook, ggplot and all required packages under my user account without any hassles whatsoever thanks to this: $ cat ~/.pydistutils.cfg [install] install_lib = ~/Library/Python/$py_version_short/site-packages install_scripts = ~/Library/Python/$py_version_short/bin install_data = ~/Library/Python/$py_version_short/share Just set $PATH to include the install_scripts, run pip, and you're all set. Everything just works, without the need to install another Python interpreter or mess about with system components. (edited for formatting)
Fomite 13y ago
Having written all my simulation code in Python, and having done all the visualization for said simulations in R mainly for ggplot2 graphs, this is very exciting.
washedup 13y ago
Great stuff. Thanks a ton!

187 points by martingoodson 13y ago

> I've tried other libraries like Bockah and d3py but what I really want is ggplot2. I wonder if that's meant to say, "bokeh"... and I would be interested to know the major differences. This library might be better than bokeh if there's no dependencies on coffeescript and such. But I wonder in what way this is un-pythonic, except perhaps in its imitation of R syntax. But ggplot2 is also not very much like the rest of R either.

darkarmani 13y ago
I think you only need coffeescript if you want to develop bokeh not if you want to use it.
paddy_m 13y ago
I'm a Bokeh developer. We have plans to make the coffescript situation a lot easier to deal with, this fix should be coming soon.

marrone12 13y ago

I'm really excited for this. I might finally switch to python now!

dlib 13y ago
Indeed, there's some incredible work put into the Python data analysis toolkit. Pandas is very impressive. However, no GGplot was holding me back from switching but this and improvements to other graphing libraries really make me want to use Python in my next projects.
- rprospero 13y ago
  As someone who does all my data analysis in Python, I'm curious what it is about GGplot that it's absence was a deal breaker for you? It's obviously quite powerful, considering all the excitement this port has generated, but I haven't seen anything explain what it provides over other plotting solutions.
  - has2k1 13y ago
    You need understand what ggplot is all about, i.e a structured/formulaic way to think about and build graphs. Explaining it cannot possibly do it justice. You have dive into it, even a little bit and the way you see graphs and plots totally changes, you immediately buy into it and would never wish to go back. I haven't really said anything to give you a sense of comparison. It's kind of like PGs essay (http://www.paulgraham.com/avg.html http://www.paulgraham.com/avg.html) about how the merits of higher level programming (specifically in lisp) can hardly be explained to those who have not been exposed to it.
    - rprospero 13y ago
      The merits of higher level programming are hard to explain to a Blub programmer, but the differences are trivial to explain. I can tell a C programmer that Lisp has automatic memory management, higher order functions, macros, and atoms. She may not know why those matter, but I can tell her they exist. I can tell a Python programmer that Haskell has pure functions, Monads, Arrows, and an advanced type system. He'll think those will make his life harder, but he'll know they're there. What makes GGplot different? I know that I won't understand why this difference matters until I've played with it, but it will at least tell me where to start playing.
      - has2k1 13y ago
        I mentioned the difference "a structured/formulaic way to think about and build graphs" This is what plotting using the "grammar" provides. Each plot is a like a sentence, for a sentence can be composed using some of the following - verb, noun, adverb, adjective, interjection, pronoun, proposition, conjunction. Alike, ggplot2 allows you to think of a graph in terms of layers, which layers can have different components that describe the "geometry" or "statistics" of the plot. Plus, there is a lot more. You could probably describe your favourite plotting package as structured and formulaic, but an experience with ggplot2 would convince you otherwise.
      - peatmoss 13y ago
        Here's another stab at why ggplot2 is a Good Thing. In the easiest plotting case, there is a function that builds exactly the visualization that you're looking for. This is great as long as you don't need to do anything that deviates from the normal set of barplots, histograms, linegraphs, piecharts (shudder), etc. But let's say you need something a little different. Maybe you want to add additional dimensions to that dot plot. Maybe you want the dots' size or color to be mapped to different aspects of your data. In a world without ggplot2 (or more generally the grammar of graphics), you're pretty much stuck going to a very primitive drawing system in which you're specifying the virtual path of a pen, or working with basic geometric figures. The grammar of graphics and ggplot2 occupy a sweet middle ground between being able to simply pick an off-the-shelf visualization, and needing to draw the whole damn works manually. And because the grammar really is consistent, you can also play with different facets of your data and build completely different charts to see which is better at presenting your thesis. In short, ggplot2 rocks, Hadley/Leland rock, and a port of ggplot2 to Python is nothing but good news for the Python community.

Osmium 13y ago

This is really exciting! I've always liked ggplot2 but sadly struggled with R syntax (the only time I ever used it was for ggplot2, and found it really confusing). For anyone reading this, I don't think this is intended to replace e.g. matplotlib which I suspect is more powerful overall. It's more for creating good looking, publication-quality graphs. A lot of thought has gone into ggplot2's default theme. A lot of influence from Tufte et al. if I remember rightly. Though, sadly, it looks like this port doesn't replicate ggplot2's graphs pixel-for-pixel, which is a shame. Edit: Incidentally if anyone has a recommendation for a good graphing app for OS X, I'd be all ears. I still haven't found a good one. I usually use Plot (http://plot.micw.eu http://plot.micw.eu) which is great (scriptable, produces good looking graphs) but has a bit of a clunky interface. I personally find DataGraph's interface horrendous, even though its graphs are good, and Excel takes forever to make anything remotely decent. matplotlib and its ilk are fine but require custom scripting. I've been using xmgrace recently simply because it launches quickly, but it's (understandably) not retina and not native and just a pain really. What I'd give for a nice graphing app...

xioxox 13y ago
You could try my Veusz http://home.gna.org/veusz/ http://home.gna.org/veusz/ package. GUI, scripting and multiplatform. Quite a few satisfied users!
- Osmium 13y ago
  Thanks for the recommendation :)
- hatmatrix 13y ago
  Wow, I'm surprised I haven't heard of this. Looks like it could be a good competitor to the Sigmaplot/Origin/Igor pro audience?
  - xioxox 13y ago
    Hopefully it's a good competitor to these (people tell me so), but I hadn't used them before embarking on Veusz! I mainly got annoyed with the state of command-line plotting facilities in astronomy and unix (like IDL, gnuplot, etc). I started with the idea that graphs should be built in an object-oriented fashion out of widgets. The widgets are arranged in a tree, a page holds a graph or a grid of graphs and a graph has axes and plotting widgets, and so on. Each widget has a set of properties and formatting settings which can be changed. It's now gained more data manipulation abilities. Data is stored in named datasets, linked to external files or entered manually, or you can even capture it from sockets or external programs. You can easily write a plugin to load your own file format. There are a set of data manipulation plugins for filtering and so on (again you can write your own). When plotting, you can just enter expressions to investigate your data. Most of Veusz is written in Python with PyQt. There's a bit of C++ code to handle the inner loops, but it's pretty responsive. The next release should support Python 3, too. One nice thing is that the saved files are simply python commands to regenerate the plot, so it's easy for the user to automate making plots. You can also use it as a python module for plotting, using the same command interface as the saved plots use.

marcosscriven 13y ago

This is fantastic - I remember the pain of sorting out R issues for some finance analysts who were wedded to ggplot. So much better to be able to do it in Python.

dkroy 13y ago

Is there a reason that the dependencies are not installed via the pip call for ggplot? I ask this out of ignorance, not trying to be facetious.

gh02t 13y ago
At times numpy/scipy/matplotlib have proven pretty troublesome to install with pip. I think they have it working now, but it's still not 100% reliable.
- jofer 13y ago
  The main problem is that they have system library dependencies that pip doesn't handle.
  - andrewryno 13y ago
    I think all you need is build-essentials and python-dev.
    - spiffworks 13y ago
      Nope, numpy needs libblas and scipy needs libatlas, both of which have to installed from the system package manager. I slap my forehead every time I move to a new system and find that the pip install in the virtualenv failed.
    - jofer 13y ago
      Matplotlib depends on freetype, libpng, and libjpeg as well. Numpy can be built without any external dependencies, but it will be a very slow installation. You're better off with an accelerated BLAS library (e.g. ATLAS/MKL/etc) and some sort of LAPACK library. Some of numpy's functionality also needs a fortran compiler to build. At any rate, there are other system dependencies beyond a basic compiler and the header files for python.
      - andrewryno 13y ago

sonabinu 13y ago

Awesome!

Blahah 13y ago

ggplot is a beautiful thing - excellent job porting it to python. I only wish something similar were available for ruby.

rcarmo 13y ago

This is amazing. FYI, this works out of the box with Mac OS X Lion's system Python and the gfortran compiler from homebrew - that's the only thing I need to install separately (Xcode and brew are required to install that, of course, but most people doing any sort of coding seem to have them anyway). Also, a tip for those of you wanting to do the same: I'm running IPython notebook, ggplot and all required packages under my user account without any hassles whatsoever thanks to this: $ cat ~/.pydistutils.cfg [install] install_lib = ~/Library/Python/$py_version_short/site-packages install_scripts = ~/Library/Python/$py_version_short/bin install_data = ~/Library/Python/$py_version_short/share Just set $PATH to include the install_scripts, run pip, and you're all set. Everything just works, without the need to install another Python interpreter or mess about with system components. (edited for formatting)

Fomite 13y ago

Having written all my simulation code in Python, and having done all the visualization for said simulations in R mainly for ggplot2 graphs, this is very exciting.

washedup 13y ago

Great stuff. Thanks a ton!