https://github.com/hustcc/pyg2plot

🎨 Python3 binding for `@AntV/G2Plot` Plotting Library .
https://github.com/hustcc/pyg2plot

antv g2plot visualization

Last synced: 6 days ago
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🎨 Python3 binding for `@AntV/G2Plot` Plotting Library .

• Host: GitHub
• URL: https://github.com/hustcc/pyg2plot
• Owner: hustcc
• License: mit
• Created: 2021-01-13T01:30:34.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2022-11-29T10:16:32.000Z (about 2 years ago)
• Last Synced: 2025-01-26T04:03:28.160Z (6 days ago)
• Topics: antv, g2plot, visualization
• Language: Python
• Homepage:
• Size: 50.8 KB
• Stars: 1,074
• Watchers: 12
• Forks: 116
• Open Issues: 9
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# PyG2Plot

> 🎨 Python3 binding for [`@AntV/G2Plot`](https://github.com/antvis/G2Plot) which an interactive and responsive charting library. Based on the grammar of graphics, you can easily make superior statistical charts through a few lines of code. `PyG2Plot` is inspired by pyecharts.

[![Latest Stable Version](https://img.shields.io/pypi/v/pyg2plot.svg)](https://pypi.python.org/pypi/pyg2plot)

[![build Status](https://github.com/hustcc/pyg2plot/workflows/build/badge.svg?branch=main)](https://github.com/hustcc/pyg2plot/actions?query=workflow%3Abuild)

[![Pypi Download](https://img.shields.io/pypi/dm/pyg2plot)](https://pypi.python.org/pypi/pyg2plot)



  



**Document**： [中文说明文档](./README_ZH.md)  ·  [Drawing statistical plots](./docs/plot.md)  ·  [In Jupyter Notebook](./docs/jupyter.md)  ·  [Principles](./docs/how.md)

## Installation

```bash

$ pip install pyg2plot

```

## Usage

#### **render HTML**

```py

from pyg2plot import Plot

line = Plot("Line")

line.set_options({

  "data": [

    { "year": "1991", "value": 3 },

    { "year": "1992", "value": 4 },

    { "year": "1993", "value": 3.5 },

    { "year": "1994", "value": 5 },

    { "year": "1995", "value": 4.9 },

    { "year": "1996", "value": 6 },

    { "year": "1997", "value": 7 },

    { "year": "1998", "value": 9 },

    { "year": "1999", "value": 13 },

  ],

  "xField": "year",

  "yField": "value",

})

# 1. render html file

line.render("plot.html")

# 2. render html string

line.render_html()

```

![image](https://user-images.githubusercontent.com/7856674/104466432-31be5000-55f0-11eb-8333-68279d50861e.png)

#### **render Jupyter**

```py

from pyg2plot import Plot

line = Plot("Line")

line.set_options({

  "height": 400, # set a default height in jupyter preview

  "data": [

    { "year": "1991", "value": 3 },

    { "year": "1992", "value": 4 },

    { "year": "1993", "value": 3.5 },

    { "year": "1994", "value": 5 },

    { "year": "1995", "value": 4.9 },

    { "year": "1996", "value": 6 },

    { "year": "1997", "value": 7 },

    { "year": "1998", "value": 9 },

    { "year": "1999", "value": 13 },

  ],

  "xField": "year",

  "yField": "value",

})

# 1. render in notebook

line.render_notebook()

# 2. render in jupyter lab

line.render_jupyter_lab()

```

#### **use JavaScript callback**

```py

from pyg2plot import Plot, JS

line = Plot("Line")

line.set_options({

  "height": 400, # set a default height in jupyter preview

  "data": [

    { "year": "1991", "value": 3 },

    { "year": "1992", "value": 4 },

    { "year": "1993", "value": 3.5 },

    { "year": "1994", "value": 5 },

    { "year": "1995", "value": 4.9 },

    { "year": "1996", "value": 6 },

    { "year": "1997", "value": 7 },

    { "year": "1998", "value": 9 },

    { "year": "1999", "value": 13 },

  ],

  "xField": "year",

  "yField": "value",

  "lineStye": JS('''function() {

    return { stroke: 'red' }; 

  }''')

})

```

Use `JS` API, you can use JavaScript syntax for callback.

## API

Now, only has one API of `pyg2plot`.

 - **Plot**

1. *Plot(plot_type: str)*: get an instance of `Plot` class.

2. *plot.set_options(options: object)*: set the options of [G2Plot](https://g2plot.antv.vision/) into instance.

3. *plot.render(path, env, **kwargs)*: render out html file by setting the path, jinja2 env and kwargs.

4. *plot.render_notebook(env, **kwargs)*: render plot on jupyter preview.

5. *plot.render_jupyter_lab(env, **kwargs)*: render plot on jupyter lab preview.

6. *plot.render_html(env, **kwargs)*: render out html string by setting jinja2 env and kwargs.

7. *plot.dump_js_options(env, **kwargs)*: dump js options by setting jinja2 env and kwargs, use it for HTTP request.

> More apis is on the way.

## License

MIT@[hustcc](https://github.com/hustcc).