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@@ -1,10 +1,16 @@
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-# @jupyterlab/vega3-extension
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+# vega3-extension
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-A mime-renderer extension for JupyterLab that provides support for rendering Vega and Vega-Lite documents and mimebundles.
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+A JupyterLab extension for rendering Vega and Vega-Lite
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+
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-Example in Python:
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+## Prerequisites
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+* JupyterLab ^0.27.0
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+
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+## Usage
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+
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+To render Vega-Lite output in IPython:
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```python
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from IPython.display import display
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@@ -28,3 +34,74 @@ display({
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}
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}, raw=True)
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```
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+
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+Using the [altair library](https://github.com/altair-viz/altair):
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+
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+```python
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+import altair as alt
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+
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+cars = alt.load_dataset('cars')
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+
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+chart = alt.Chart(cars).mark_point().encode(
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+ x='Horsepower',
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+ y='Miles_per_Gallon',
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+ color='Origin',
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+)
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+
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+chart
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+```
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+
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+Provide vega-embed options via metadata:
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+
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+```python
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+from IPython.display import display
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+
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+display({
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+ "application/vnd.vegalite.v2+json": {
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+ "$schema": "https://vega.github.io/schema/vega-lite/v2.json",
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+ "description": "A simple bar chart with embedded data.",
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+ "data": {
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+ "values": [
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+ {"a": "A", "b": 28}, {"a": "B", "b": 55}, {"a": "C", "b": 43},
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+ {"a": "D", "b": 91}, {"a": "E", "b": 81}, {"a": "F", "b": 53},
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+ {"a": "G", "b": 19}, {"a": "H", "b": 87}, {"a": "I", "b": 52}
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+ ]
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+ },
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+ "mark": "bar",
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+ "encoding": {
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+ "x": {"field": "a", "type": "ordinal"},
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+ "y": {"field": "b", "type": "quantitative"}
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+ }
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+ }
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+}, metadata={
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+ "application/vnd.vegalite.v2+json": {
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+ "embed_options": {
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+ "actions": False
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+ }
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+ }
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+}, raw=True)
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+```
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+
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+Provide vega-embed options via altair:
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+
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+```python
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+import altair as alt
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+
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+alt.renderers.enable('default', embed_options={'actions': False})
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+
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+cars = alt.load_dataset('cars')
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+
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+chart = alt.Chart(cars).mark_point().encode(
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+ x='Horsepower',
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+ y='Miles_per_Gallon',
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+ color='Origin',
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+)
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+
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+chart
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+```
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+
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+To render a `.vl`, `.vg`, `vl.json` or `.vg.json` file, simply open it:
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+
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+## Development
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+
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+See the [JupyterLab Contributor Documentation](https://github.com/jupyterlab/jupyterlab/blob/master/CONTRIBUTING.md).
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