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doc: update Colab notebooks
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‎examples/interactivity.ipynb‎

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{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# pyobsplot - jupyter interactivity\n",
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"\n",
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"**Note :** this notebook is designed to be used on [Google Colab](https://colab.research.google.com/github/juba/pyobsplot/blob/main/examples/introduction.ipynb).\n",
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"\n",
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"[pyobsplot](https://github.com/juba/pyobsplot) is a Python package which allows to use Observable Plot in Jupyter notebooks with a syntax as close as possible to the JavaScript one. For more information, see the [documentation website](https://juba.github.io/pyobsplot).\n",
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"\n",
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"When using the `widget` renderer, the fact that plots are generated as Jupyter widgets allow for basic interactivity. More specifically, you can set the spec attribute of an existing `pyobsplot` plot to another plot specification and it will update it.\n",
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"\n",
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"First we install the `pyobsplot` package in the Colab environment:\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Only needed in Colab, cleanup environment\n",
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"! pip uninstall -y pandas-gbq\n",
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"# Install pyobsplot\n",
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"! pip install pyobsplot"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Then we load the needed modules and data:\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import polars as pl\n",
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"from IPython.display import display\n",
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"from ipywidgets import IntSlider\n",
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"\n",
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"from pyobsplot import Plot\n",
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"\n",
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"penguins = pl.read_csv(\n",
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" \"https://github.com/juba/pyobsplot/raw/main/doc/data/penguins.csv\"\n",
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")"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"The next step is to create a `generate_plot` function which takes an opacity value as input and returns a plot specification. We create our starting plot with an opacity value of 1.\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"def generate_plot_spec(opacity):\n",
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" return {\n",
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" \"grid\": True,\n",
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" \"marks\": [\n",
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" Plot.rectY(\n",
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" penguins,\n",
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" Plot.binX(\n",
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" {\"y\": \"count\"},\n",
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" {\"x\": \"body_mass_g\", \"fill\": \"steelblue\", \"fillOpacity\": opacity},\n",
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" ),\n",
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" ),\n",
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" Plot.ruleY([0]),\n",
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" ],\n",
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" }\n",
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"\n",
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"\n",
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"plot = Plot.plot(generate_plot_spec(1))"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Now we create an `IntSlider` input widget and observe its value with a new `update_plot` function which generates a new specification with the updated opacity value, and stores it as the `spec` plot attribute.\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"def update_plot(change):\n",
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" new = change[\"new\"]\n",
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" plot.spec = generate_plot_spec(new / 100) # type: ignore\n",
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"\n",
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"\n",
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"w = IntSlider(value=100, min=0, max=100)\n",
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"w.observe(update_plot, names=\"value\")"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Finally we can display both our input widget and our plot.\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"display(w)\n",
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"display(plot)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.9"
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},
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"orig_nbformat": 4
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},
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"nbformat": 4,
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"nbformat_minor": 2
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# pyobsplot - jupyter interactivity\n",
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"\n",
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"**Note :** this notebook is designed to be used on [Google Colab](https://colab.research.google.com/github/juba/pyobsplot/blob/main/examples/introduction.ipynb).\n",
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"\n",
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"[pyobsplot](https://github.com/juba/pyobsplot) is a Python package which allows to use Observable Plot in Jupyter notebooks with a syntax as close as possible to the JavaScript one. For more information, see the [documentation website](https://juba.github.io/pyobsplot).\n",
13+
"\n",
14+
"When using the `widget` renderer, the fact that plots are generated as Jupyter widgets allow for basic interactivity. More specifically, you can set the spec attribute of an existing `pyobsplot` plot to another plot specification and it will update it.\n",
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"\n",
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"First we install the `pyobsplot` package in the Colab environment:\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Install pyobsplot\n",
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"! pip install pyobsplot[typst]"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Then we load the needed modules and data:\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import polars as pl\n",
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"from IPython.display import display\n",
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"from ipywidgets import IntSlider\n",
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"\n",
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"from pyobsplot import Plot\n",
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"\n",
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"penguins = pl.read_csv(\n",
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" \"https://github.com/juba/pyobsplot/raw/main/doc/data/penguins.csv\"\n",
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")"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"The next step is to create a `generate_plot` function which takes an opacity value as input and returns a plot specification. We create our starting plot with an opacity value of 1.\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"def generate_plot_spec(opacity):\n",
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" return {\n",
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" \"grid\": True,\n",
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" \"marks\": [\n",
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" Plot.rectY(\n",
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" penguins,\n",
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" Plot.binX(\n",
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" {\"y\": \"count\"},\n",
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" {\"x\": \"body_mass_g\", \"fill\": \"steelblue\", \"fillOpacity\": opacity},\n",
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" ),\n",
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" ),\n",
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" Plot.ruleY([0]),\n",
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" ],\n",
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" }\n",
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"\n",
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"\n",
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"plot = Plot.plot(generate_plot_spec(1))"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Now we create an `IntSlider` input widget and observe its value with a new `update_plot` function which generates a new specification with the updated opacity value, and stores it as the `spec` plot attribute.\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"def update_plot(change):\n",
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" new = change[\"new\"]\n",
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" plot.spec = generate_plot_spec(new / 100) # type: ignore\n",
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"\n",
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"\n",
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"w = IntSlider(value=100, min=0, max=100)\n",
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"w.observe(update_plot, names=\"value\")"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Finally we can display both our input widget and our plot.\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"display(w)\n",
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"display(plot)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.9"
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},
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"widgets": {
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"application/vnd.jupyter.widget-state+json": {
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"state": {},
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"version_major": 2,
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"version_minor": 0
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

‎examples/introduction.ipynb‎

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"metadata": {},
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"outputs": [],
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"source": [
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"# Only needed in Colab, cleanup environment\n",
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"! pip uninstall -y pandas-gbq\n",
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"# Install pyobsplot\n",
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"! pip install pyobsplot"
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"! pip install pyobsplot[typst]"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Sometimes a plot specification includes some JavaScript code. To add those to a plot specification we have to pass it as a string and wrap it into the `js()` method:\n"
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"Sometimes an Observable Plot specification includes some JavaScript code. To add those to a `pyobsplot` specification we have to pass it as a string and wrap it into the `js()` method:\n"
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]
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},
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{
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],
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"metadata": {
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"kernelspec": {
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"display_name": "pyobsplot-IeWpVr3Z-py3.10",
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.9"
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"version": "3.12.9"
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},
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"orig_nbformat": 4
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"widgets": {
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"application/vnd.jupyter.widget-state+json": {
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"state": {},
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"version_major": 2,
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"version_minor": 0
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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"nbformat_minor": 4
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}

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