Jupyter uses requirejs to manage its Javascript libraries, which means we can "require" Highcharts into the notebook.
Since Highcharts does not expose itself according to the requirejs standard, I have made it into a shim. The exporting feature is a separate file in the Highcharts source, so I loaded it as a separate shim.
%%javascript
require.config({
paths: {
highcharts: "http://code.highcharts.com/highcharts",
highcharts_exports: "http://code.highcharts.com/modules/exporting",
jquery: "https://code.jquery.com/jquery-3.1.1.min",
},
shim: {
highcharts: {
exports: "Highcharts",
deps: ["jquery"]
},
highcharts_exports: {
exports: "Highcharts",
deps: ["highcharts"]
}
}
});
To translate the data from the Python realm into the Javascript realm felt a little "hacky", but it works. This takes the Python variable chart_data
and binds it to Javascript's global window
variable as window.chartData
. If anyone has a prettier method please tweet me (@codeweavr) and I will edit this post with your recommendations.
import json
from IPython.display import Javascript
chart_data = [
{
'name': 'Tokyo',
'data': [7.0, 6.9, 9.5, 14.5, 18.2, 21.5, 25.2, 26.5, 23.3, 18.3, 13.9, 9.6]
},
{
'name': 'New York',
'data': [-0.2, 0.8, 5.7, 11.3, 17.0, 22.0, 24.8, 24.1, 20.1, 14.1, 8.6, 2.5]
},
{
'name': 'Berlin',
'data': [-0.9, 0.6, 3.5, 8.4, 13.5, 17.0, 18.6, 17.9, 14.3, 9.0, 3.9, 1.0]
},
{
'name': 'London',
'data': [3.9, 4.2, 5.7, 8.5, 11.9, 15.2, 17.0, 16.6, 14.2, 10.3, 6.6, 4.8]
}
]
Javascript("window.chartData={};".format(json.dumps(chart_data)))
To display the graph, I used the %%Javascript cell magic method and used the Highcharts demo code:
%%javascript
// Since I append the div later, sometimes there are multiple divs.
$("#container").remove();
// Make the cdiv to contain the chart.
element.append('<div id="container" style="min-width: 310px; height: 400px; margin: 0 auto"></div>');
// Require highcarts and make the chart.
require(['highcharts_exports'], function(Highcharts) {
$('#container').highcharts({
title: {
text: 'Monthly Average Temperature',
x: -20 //center
},
subtitle: {
text: 'Source: WorldClimate.com',
x: -20
},
xAxis: {
categories: ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun',
'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']
},
yAxis: {
title: {
text: 'Temperature (°C)'
},
plotLines: [{
value: 0,
width: 1,
color: '#808080'
}]
},
tooltip: {
valueSuffix: '°C'
},
legend: {
layout: 'vertical',
align: 'right',
verticalAlign: 'middle',
borderWidth: 0
},
// This is where I used the chart_data from Python
series: window.chartData
});
});