Getting started ========================================= About Highcharts and easychart ----------------------------------------- Highcharts is an interactive charting library, written in Javascript and designed for the web browser. The `Highcharts demo page `_ is rich with examples that you can use as inspiration. easychart is an open-source Python library designed for building Highcharts visualizations in Python and rendering them in a Jupyter notebook or a HTML file. Installation ----------------------------------------- Installing :code:`easychart` is simple with pip: :: pip install easychart Your first chart ----------------------------------------- Creating and rendering a chart involves constructing a chart *definition* which contains both data and some (optional) configurations, such as the chart's background-color, the format of the axis labels etc. Here's a simple example: :: import easychart chart = easychart.new() chart.plot([1,1,2,3,5,8], name="Fibonacci series") chart .. raw:: html
.. note:: Under the hood, easychart serializes the chart definition to JSON, which is interpreted by the highcharts Javascript library in your browser. Serialization ----------------------------------------- Serialization involves converting a chart object back into a native Python object (a dictionary of only native types). This can be useful for exporting and debugging. :: import easychart chart = easychart.new("column", title="US 2016 Presidential election results") chart.yAxis.labels.format = "{value}%" chart.categories = ["Electoral vote", "Popular vote"] chart.plot([46.1,48.2], name="Hillary Clinton", color="rgb(18,8,55)") chart.plot([57.3,42.7], name="Donald Trump", color="rgb(202,0,4)") chart.serialize() { "series": [ { "data": [ 46.1, 48.2 ], "name": "Hillary Clinton", "color": "rgb(18,8,55)" }, { "data": [ 57.3, 42.7 ], "name": "Donald Trump", "color": "rgb(202,0,4)" } ], "chart": { "type":"column", "zoomType": "x" }, "title": { "text": "US 2016 Presidential election results" }, "yAxis": { "labels": { "format": "{value}%" } }, "xAxis": { "categories": [ "Electoral vote", "Popular vote" ] } }