ggplot for python
Project description
|image|
{ggplot} from `Yhat <http://yhathq.com>`__
==========================================
read more on our
`blog <http://blog.yhathq.com/posts/ggplot-for-python.html>`__
::
from ggplot import *
ggplot(aes(x='date', y='beef'), data=meat) + \
geom_point(color='lightblue') + \
stat_smooth(span=.15, color='black', se=True) + \
ggtitle("Beef: It's What's for Dinner") + \
xlab("Date") + \
ylab("Head of Cattle Slaughtered")
.. figure:: https://raw.github.com/yhat/ggplot/master/ggplot/tests/baseline_images/test_readme_examples/ggplot_demo_beef.png
:alt: image
image
What is it?
-----------
Yes, it's another port of
`ggplot2 <https://github.com/hadley/ggplot2>`__. One of the biggest
reasons why I continue to reach for ``R`` instead of ``Python`` for data
analysis is the lack of an easy to use, high level plotting package like
``ggplot2``. I've tried other libraries like
`bokeh <https://github.com/continuumio/bokeh>`__ and
`d3py <https://github.com/mikedewar/d3py>`__ but what I really want is
``ggplot2``.
``ggplot`` is just that. It's an extremely un-pythonic package for doing
exactly what ``ggplot2`` does. The goal of the package is to mimic the
``ggplot2`` API. This makes it super easy for people coming over from
``R`` to use, and prevents you from having to re-learn how to plot
stuff.
Goals
-----
- same API as ``ggplot2`` for ``R``
- ability to use both American and British English spellings of
aesthetics
- tight integration with `pandas <https://github.com/pydata/pandas>`__
- pip installable
Getting Started
---------------
Dependencies
~~~~~~~~~~~~
This package depends on the following packages, although they should be
automatically installed if you use ``pip``:
- ``matplotlib``
- ``pandas``
- ``numpy``
- ``scipy``
- ``statsmodels``
- ``patsy``
Installation
~~~~~~~~~~~~
Installing ``ggplot`` is really easy. Just use ``pip``!
::
$ pip install ggplot
Loading ``ggplot``
~~~~~~~~~~~~~~~~~~
::
# run an IPython shell (or don't)
$ ipython
In [1]: from ggplot import *
That's it! You're ready to go!
Examples
--------
::
meat_lng = pd.melt(meat[['date', 'beef', 'pork', 'broilers']], id_vars='date')
ggplot(aes(x='date', y='value', colour='variable'), data=meat_lng) + \
geom_point() + \
stat_smooth(color='red')
.. figure:: https://raw.github.com/yhat/ggplot/master/ggplot/tests/baseline_images/test_readme_examples/ggplot_meat.png
:alt: image
image
``geom_point``
~~~~~~~~~~~~~~
::
from ggplot import *
ggplot(diamonds, aes('carat', 'price')) + \
geom_point(alpha=1/20.) + \
ylim(0, 20000)
.. figure:: https://raw.github.com/yhat/ggplot/master/ggplot/tests/baseline_images/test_readme_examples/diamonds_geom_point_alpha.png
:alt: image
image
``geom_histogram``
~~~~~~~~~~~~~~~~~~
::
p = ggplot(aes(x='carat'), data=diamonds)
p + geom_histogram() + ggtitle("Histogram of Diamond Carats") + labs("Carats", "Freq")
.. figure:: https://raw.github.com/yhat/ggplot/master/ggplot/tests/baseline_images/test_readme_examples/diamonds_carat_hist.png
:alt: image
image
``geom_density``
~~~~~~~~~~~~~~~~
::
ggplot(diamonds, aes(x='price', color='cut')) + \
geom_density()
.. figure:: https://raw.github.com/yhat/ggplot/master/ggplot/tests/baseline_images/test_readme_examples/geom_density_example.png
:alt: image
image
::
meat_lng = pd.melt(meat[['date', 'beef', 'broilers', 'pork']], id_vars=['date'])
p = ggplot(aes(x='value', colour='variable', fill=True, alpha=0.3), data=meat_lng)
p + geom_density()
.. figure:: https://raw.github.com/yhat/ggplot/master/ggplot/tests/baseline_images/test_readme_examples/density_with_fill.png
:alt: image
image
``geom_bar``
~~~~~~~~~~~~
::
p = ggplot(mtcars, aes('factor(cyl)'))
p + geom_bar()
.. figure:: https://raw.github.com/yhat/ggplot/master/ggplot/tests/baseline_images/test_readme_examples/mtcars_geom_bar_cyl.png
:alt: image
image
TODO
----
`The list is long, but
distinguished. <https://github.com/yhat/ggplot/blob/master/TODO.md>`__
We're looking for contributors! Email greg at yhathq.com for more info.
For getting started with contributing, check out `these
docs <https://github.com/yhat/ggplot/blob/master/docs/contributing.rst>`__
|image|
.. |image| image:: https://secure.travis-ci.org/yhat/ggplot.png?branch=master
:target: http://travis-ci.org/yhat/ggplot
.. |image| image:: https://ga-beacon.appspot.com/UA-46996803-1/ggplot/README.md
:target: https://github.com/yhat/ggplot
{ggplot} from `Yhat <http://yhathq.com>`__
==========================================
read more on our
`blog <http://blog.yhathq.com/posts/ggplot-for-python.html>`__
::
from ggplot import *
ggplot(aes(x='date', y='beef'), data=meat) + \
geom_point(color='lightblue') + \
stat_smooth(span=.15, color='black', se=True) + \
ggtitle("Beef: It's What's for Dinner") + \
xlab("Date") + \
ylab("Head of Cattle Slaughtered")
.. figure:: https://raw.github.com/yhat/ggplot/master/ggplot/tests/baseline_images/test_readme_examples/ggplot_demo_beef.png
:alt: image
image
What is it?
-----------
Yes, it's another port of
`ggplot2 <https://github.com/hadley/ggplot2>`__. One of the biggest
reasons why I continue to reach for ``R`` instead of ``Python`` for data
analysis is the lack of an easy to use, high level plotting package like
``ggplot2``. I've tried other libraries like
`bokeh <https://github.com/continuumio/bokeh>`__ and
`d3py <https://github.com/mikedewar/d3py>`__ but what I really want is
``ggplot2``.
``ggplot`` is just that. It's an extremely un-pythonic package for doing
exactly what ``ggplot2`` does. The goal of the package is to mimic the
``ggplot2`` API. This makes it super easy for people coming over from
``R`` to use, and prevents you from having to re-learn how to plot
stuff.
Goals
-----
- same API as ``ggplot2`` for ``R``
- ability to use both American and British English spellings of
aesthetics
- tight integration with `pandas <https://github.com/pydata/pandas>`__
- pip installable
Getting Started
---------------
Dependencies
~~~~~~~~~~~~
This package depends on the following packages, although they should be
automatically installed if you use ``pip``:
- ``matplotlib``
- ``pandas``
- ``numpy``
- ``scipy``
- ``statsmodels``
- ``patsy``
Installation
~~~~~~~~~~~~
Installing ``ggplot`` is really easy. Just use ``pip``!
::
$ pip install ggplot
Loading ``ggplot``
~~~~~~~~~~~~~~~~~~
::
# run an IPython shell (or don't)
$ ipython
In [1]: from ggplot import *
That's it! You're ready to go!
Examples
--------
::
meat_lng = pd.melt(meat[['date', 'beef', 'pork', 'broilers']], id_vars='date')
ggplot(aes(x='date', y='value', colour='variable'), data=meat_lng) + \
geom_point() + \
stat_smooth(color='red')
.. figure:: https://raw.github.com/yhat/ggplot/master/ggplot/tests/baseline_images/test_readme_examples/ggplot_meat.png
:alt: image
image
``geom_point``
~~~~~~~~~~~~~~
::
from ggplot import *
ggplot(diamonds, aes('carat', 'price')) + \
geom_point(alpha=1/20.) + \
ylim(0, 20000)
.. figure:: https://raw.github.com/yhat/ggplot/master/ggplot/tests/baseline_images/test_readme_examples/diamonds_geom_point_alpha.png
:alt: image
image
``geom_histogram``
~~~~~~~~~~~~~~~~~~
::
p = ggplot(aes(x='carat'), data=diamonds)
p + geom_histogram() + ggtitle("Histogram of Diamond Carats") + labs("Carats", "Freq")
.. figure:: https://raw.github.com/yhat/ggplot/master/ggplot/tests/baseline_images/test_readme_examples/diamonds_carat_hist.png
:alt: image
image
``geom_density``
~~~~~~~~~~~~~~~~
::
ggplot(diamonds, aes(x='price', color='cut')) + \
geom_density()
.. figure:: https://raw.github.com/yhat/ggplot/master/ggplot/tests/baseline_images/test_readme_examples/geom_density_example.png
:alt: image
image
::
meat_lng = pd.melt(meat[['date', 'beef', 'broilers', 'pork']], id_vars=['date'])
p = ggplot(aes(x='value', colour='variable', fill=True, alpha=0.3), data=meat_lng)
p + geom_density()
.. figure:: https://raw.github.com/yhat/ggplot/master/ggplot/tests/baseline_images/test_readme_examples/density_with_fill.png
:alt: image
image
``geom_bar``
~~~~~~~~~~~~
::
p = ggplot(mtcars, aes('factor(cyl)'))
p + geom_bar()
.. figure:: https://raw.github.com/yhat/ggplot/master/ggplot/tests/baseline_images/test_readme_examples/mtcars_geom_bar_cyl.png
:alt: image
image
TODO
----
`The list is long, but
distinguished. <https://github.com/yhat/ggplot/blob/master/TODO.md>`__
We're looking for contributors! Email greg at yhathq.com for more info.
For getting started with contributing, check out `these
docs <https://github.com/yhat/ggplot/blob/master/docs/contributing.rst>`__
|image|
.. |image| image:: https://secure.travis-ci.org/yhat/ggplot.png?branch=master
:target: http://travis-ci.org/yhat/ggplot
.. |image| image:: https://ga-beacon.appspot.com/UA-46996803-1/ggplot/README.md
:target: https://github.com/yhat/ggplot
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