# ggplot

**Repository Path**: enemy_705/ggplot

## Basic Information

- **Project Name**: ggplot
- **Description**: ggplot for python
- **Primary Language**: Python
- **License**: BSD-2-Clause
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2016-09-09
- **Last Updated**: 2020-12-18

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# ggplot

<img src="./examples/example-34d773b9-ec68-40b1-999b-7bb07c208be9.png" width="400px" />
<img src="./examples/example-8f4fbffe-2999-42b0-9c34-de6f0b205733.png" width="400px" />

### 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')
```
![](./docs/example.png)

### 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)*.