# pyvisacharts
This package wraps [@visa/charts](https://github.com/visa/visa-chart-components/tree/main/packages/charts) web components for use in [Python](https://www.python.org/) and [jupyter notebooks](https://jupyter.org/), leveraging the [widget-cookiecutter](https://github.com/jupyter-widgets/widget-cookiecutter) Python package. You can find pyvisacharts on [pypi](https://pypi.org/project/pyvisacharts/), installation steps provided below.
---
### Installation Steps
- Using `pip`:
```
$ pip install pyvisacharts
```
- or `conda`:
```
$ conda install -c conda-forge pyvisacharts
```
---
#### Components with `Ready` status in this bundle
- [@visa/bar-chart](https://github.com/visa/visa-chart-components/tree/main/packages/bar-chart)
- [@visa/clustered-bar-chart](https://github.com/visa/visa-chart-components/tree/main/packages/clustered-bar-chart)
- [@visa/stacked-bar-chart](https://github.com/visa/visa-chart-components/tree/main/packages/stacked-bar-chart)
- [@visa/line-chart](https://github.com/visa/visa-chart-components/tree/main/packages/line-chart)
- [@visa/pie-chart](https://github.com/visa/visa-chart-components/tree/main/packages/pie-chart)
- [@visa/scatter-plot](https://github.com/visa/visa-chart-components/tree/main/packages/scatter-plot)
- [@visa/heat-map](https://github.com/visa/visa-chart-components/tree/main/packages/heat-map)
- [@visa/circle-packing](https://github.com/visa/visa-chart-components/tree/main/packages/circle-packing)
- [@visa/parallel-plot](https://github.com/visa/visa-chart-components/tree/main/packages/parallel-plot)
- [@visa/dumbbell-plot](https://github.com/visa/visa-chart-components/tree/main/packages/dumbbell-plot)
- [@visa/world-map](https://github.com/visa/visa-chart-components/tree/main/packages/world-map)
- [@visa/alluvial-diagram](https://github.com/visa/visa-chart-components/tree/main/packages/alluvial-diagram)
## <!-- #### Components with `Development` status -->
#### <a name="Python_components" href="#Python_components">#</a> Use VCC as Python functions
<br>
Step 1: Install:
```
$ pip install pyvisacharts
```
Step 2: Use component as any other Python function
```python
import pyvisacharts as vcc
import pandas as pd
bar_chart_data = pd.read_json("https://github.com/visa/visa-chart-components/tree/main/packages/charts-python/docs/demo_data/bar_chart_data.json")
line_chart_data = pd.read_json("https://github.com/visa/visa-chart-components/tree/main/packages/charts-python/docs/demo_data/line_chart_data.json")
vcc.BarChart(
accessibility={
"purpose": "Demonstration of a bar chart built with VCC and minimal properties provided.",
"statisticalNotes": "This chart is using dummy data."
},
data=bar_chart_data,
ordinalAccessor="item",
valueAccessor="value"
)
vcc.LineChart(
accessibility={
"purpose": "Demonstration of a line chart built with VCC and minimal properties provided.",
"statisticalNotes": "This chart is using dummy data."
},
data=line_chart_data, # a pandas data frame
ordinalAccessor="date",
valueAccessor="value",
seriesAccessor="category",
config={
"hoverOpacity": 0.25
}
)
```
See our [VCC Demo Notebook](https://github.com/visa/visa-chart-components/tree/main/packages/charts-python/docs/VCC%20Demo%20Notebook.ipynb) for more examples.
<hr>
### Development Steps
To the python widget locally, you will need to follow the below installation and build steps to symlink the necessary packages across the monorepo.
```
$ yarn
$ yarn dev --i
$ yarn dev --b
$ yarn dev --ipy
$ yarn dev --spy (spins up a local jupyter notebook)
or
$ yarn dev --lpy (spins up a local jupyter lab)
```
After running these commands, the js lib `@visa/charts` will by symlink'd and a jupyter notebook will be spun up locally for development and testing work. If you update the js build and/or python code you will likely need to restart/refresh the juptyer notebook to see development changes reflected.
In addition to the core project team, special thanks to Luis Chaves Rodriguez ([@visa](https://github.com/luis-chaves-visa)) for his assistance in development of `pyvisacharts`.
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