ggplot
is a Python implementation of the grammar of graphics. It is
not intended to be a feature-for-feature port of
`ggplot2 for R
<https://github.com/hadley/ggplot2>`__--though there
is much greatness in ggplot2
, the Python world could stand to
benefit from it. So there will be feature overlap, but not
neccessarily mimicry (after all, R is a little weird).
You can do cool things like this:
ggplot(diamonds, aes(x='price', color='clarity')) + \
geom_density() + \
scale_color_brewer(type='div', palette=7) + \
facet_wrap('cut')
$ pip install -U ggplot
# or
$ conda install -c conda-forge ggplot
# or
pip install git+https://github.com/yhat/ggplot.git
Examples are the best way to learn. There is a Jupyter Notebook full of them. There are also notebooks that show how to do particular things with ggplot (i.e. make a scatter plot or make a histogram).
It's gone--the windows, the doors, everything. Just kidding, you can find it here, though I'm not sure why you'd want to look at it. The data grouping and manipulation bits were re-written (so they actually worked) with things like facets in mind.
Thanks to all of the ggplot contributors! See `contributing.md <./contributing.md>`__.