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 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

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"
        ]
    }
}