Reputation: 5074
I have a Pandas data frame that I have converted to JSON like so:
json_data = data_df.to_json()
The original data frame looks like something similar to this:
col1 col2 col3 col4
0 1 2 2 -1
1 2 4 3 -2
2 3 6 4 -3
3 4 8 5 -4
4 5 10 6 -5
...
And the JSON string looks similar to this:
[{"col1":1,"col2":2,"col3":2,"col4":-1},{"col1":2,"col2":4,"col3":3,"col4":-2},{"col1":3,"col2":6,"col3":4,"col4":-3},{"col1":4,"col2":8,"col3":5,"col4":-4}]
My Highcharts
implementation is as follows:
$(document).ready(function() {
var my_data = '{{ json_data }}'
// create data chart
$('#container').highcharts({
chart: {
renderTo: 'chart_panel',
type: 'line',
},
legend: {layout: 'vertical',
align: 'right',
verticalAlign: 'middle',
borderWidth: 0,
},
title: {text: 'Roehrig Damper Data',
x: -20 // center title
},
xAxis: {title: {text: 'Velocity (m/sec)'}},
yAxis: {title: {text: 'Force (N)'}},
series: [ {data: my_data} ],
});
});
The {{ json_data }}
is from my Django python view and I have confirmed that it's properly formatted through the browser console. Currently my code is only displaying a blank Highcharts
chart with zero data being populated. I have tried a few different ways to manipulate the data that I desire, but without success.
My goal is to plot col2
against col1
and on the same chart plot col4
against col3
, or in other words the x-axis will be defined by both col1
and col3
.
Is there a way to accomplish my goal stated above, and if so, how?
With the help of @Andrew_Lvov I now have a JSON object that looks like this:
json_data = [
{
'name': "col1",
'data': array([1, 2, 3, 4, 5])},
{
'name': "col2",
'data': array([2, 4, 6, 8, 10])},
// etc.
]
Now my problem is that it is adding the word array
to the data.
Upvotes: 2
Views: 3635
Reputation: 4668
Try
var myData = {{ json_data | safe }};
UPDATE:
Your data should be in format:
json_data = [
{
'name': "col1",
'data': [1, 2, 3, 4, 5]},
{
'name': "col2",
'data': [2, 4, 6, 8, 10]},
]
Series parameter:
series: myData
UPDATE #2:
json_data = [{'data': list(value.values), 'name': key} for key, value in data_df.items()]
Upvotes: 3