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https://github.com/yhat/ggpy
ggplot port for python
https://github.com/yhat/ggpy
Last synced: 25 days ago
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ggplot port for python
- Host: GitHub
- URL: https://github.com/yhat/ggpy
- Owner: yhat
- License: bsd-2-clause
- Created: 2013-10-07T13:30:53.000Z (about 11 years ago)
- Default Branch: master
- Last Pushed: 2023-01-21T20:19:13.000Z (almost 2 years ago)
- Last Synced: 2024-04-13T22:22:43.660Z (7 months ago)
- Language: Python
- Homepage: http://yhat.github.io/ggpy/
- Size: 177 MB
- Stars: 3,684
- Watchers: 126
- Forks: 571
- Open Issues: 180
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGES.txt
- Contributing: contributing.md
- License: LICENSE
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README
# ggplot
### What is it?
`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:
```python
ggplot(diamonds, aes(x='price', color='clarity')) + \
geom_density() + \
scale_color_brewer(type='div', palette=7) + \
facet_wrap('cut')
```
### Installation
```bash
$ pip install -U ggplot
# or
$ conda install -c conda-forge ggplot
# or
pip install git+https://github.com/yhat/ggplot.git
```
### Examples
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](./docs/how-to/Making%20a%20Scatter%20Plot.ipynb) or [make a histogram](./docs/how-to/Making%20a%20Scatter%20Plot.ipynb)).
- [docs](./docs)
- [gallery](./docs/Gallery.ipynb)
- [various examples](./examples.md)
### What happened to the old version that didn't work?
It's gone--the windows, the doors, [everything](https://www.youtube.com/watch?v=YuxCKv_0GZc).
Just kidding, [you can find it here](https://github.com/yhat/ggplot/tree/v0.6.6), 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.
### Contributing
Thanks to all of the ggplot [contributors](./contributors.md#contributors)!
See *[contributing.md](./contributing.md)*.