Since D3.js v3 has a nice collection of methods to load data from external resources¹, It's better to you not embed data into your page, you just load it.

This will be an answer by example.

Let's start with a model definition:

# models.py
from django.db import models


class Play(models.Model):
    name = models.CharField(max_length=100)
    date = models.DateTimeField()

A urlconf:

# urls.py
from django.conf.urls import url


from .views import graph, play_count_by_month

urlpatterns = [
    url(r'^$', graph),
    url(r'^api/play_count_by_month', play_count_by_month, name='play_count_by_month'),
]

We are using two urls, one to return the html (view graph), and the other url (view play_count_by_month) as an api to return only data as JSON.

And finally our views:

# views.py
from django.db import connections
from django.db.models import Count
from django.http import JsonResponse
from django.shortcuts import render

from .models import Play


def graph(request):
    return render(request, 'graph/graph.html')


def play_count_by_month(request):
    data = Play.objects.all() \
        .extra(select={'month': connections[Play.objects.db].ops.date_trunc_sql('month', 'date')}) \
        .values('month') \
        .annotate(count_items=Count('id'))
    return JsonResponse(list(data), safe=False)

Here we defined an view to return our data as JSON, note that I changed extra to be database agnostic, since I did tests with SQLite.

And follows our graph/graph.html template that shows a graph of play counts by month:

<!DOCTYPE html>
<meta charset="utf-8">
<style>

body {
  font: 10px sans-serif;
}

.axis path,
.axis line {
  fill: none;
  stroke: #000;
  shape-rendering: crispEdges;
}

.x.axis path {
  display: none;
}

.line {
  fill: none;
  stroke: steelblue;
  stroke-width: 1.5px;
}

</style>
<body>
<script src="http://d3js.org/d3.v3.js"></script>
<script>

var margin = {top: 20, right: 20, bottom: 30, left: 50},
    width = 960 - margin.left - margin.right,
    height = 500 - margin.top - margin.bottom;

var parseDate = d3.time.format("%Y-%m-%d").parse; // for dates like "2014-01-01"
//var parseDate = d3.time.format("%Y-%m-%dT00:00:00Z").parse;  // for dates like "2014-01-01T00:00:00Z"

var x = d3.time.scale()
    .range([0, width]);

var y = d3.scale.linear()
    .range([height, 0]);

var xAxis = d3.svg.axis()
    .scale(x)
    .orient("bottom");

var yAxis = d3.svg.axis()
    .scale(y)
    .orient("left");

var line = d3.svg.line()
    .x(function(d) { return x(d.month); })
    .y(function(d) { return y(d.count_items); });

var svg = d3.select("body").append("svg")
    .attr("width", width + margin.left + margin.right)
    .attr("height", height + margin.top + margin.bottom)
  .append("g")
    .attr("transform", "translate(" + margin.left + "," + margin.top + ")");

d3.json("{% url "play_count_by_month" %}", function(error, data) {
  data.forEach(function(d) {
    d.month = parseDate(d.month);
    d.count_items = +d.count_items;
  });

  x.domain(d3.extent(data, function(d) { return d.month; }));
  y.domain(d3.extent(data, function(d) { return d.count_items; }));

  svg.append("g")
      .attr("class", "x axis")
      .attr("transform", "translate(0," + height + ")")
      .call(xAxis);

  svg.append("g")
      .attr("class", "y axis")
      .call(yAxis)
    .append("text")
      .attr("transform", "rotate(-90)")
      .attr("y", 6)
      .attr("dy", ".71em")
      .style("text-anchor", "end")
      .text("Play count");

  svg.append("path")
      .datum(data)
      .attr("class", "line")
      .attr("d", line);
});

</script>
</body>
</html>

This will return a nice graph like this (random data): Graph of Play counts by month

Update 1: D3 v4 will move the code to load external data to a dedicated lib, please see d3-request. Update 2: In order to help, I've put all files together into an example project, on github: github.com/fgmacedo/django-d3-example


I loved what fernando-macedo put together and it got me to a certain point with my data.

However I struggled with filtering of data as opposed to passing the entire dataset via this api setup. This is very similar to other peoples problem of passing JSON data from a Queryset and Pavel Patrin's answer helped me with that.

So this will now allow people to filter their data and send it as a json for use in d3. Now I am using the same hypothetical example but it should work for

# views.py
from django.db import connections
from django.db.models import Count
# from django.http import JsonResponse  #no longer needed
from django.shortcuts import render
import json


from .models import Play


def graph(request):
    data = Play.objects.filter(name__startswith='Test') \ #change here for filter. can be any kind of filter really
        .extra(select={'month': connections[Play.objects.db].ops.date_trunc_sql('month', 'date')}) \
        .values('month') \
        .annotate(count_items=Count('id'))
    formattedData=json.dumps([dict(item) in list(data)]) #This is a two-fer. It converts each item in the Queryset to a dictionary and then formats it using the json from import json above
    #now we can pass formattedData via the render request
    return render(request, 'graph/graph.html',{'formattedData':formattedData})

Now to get that appropriately on the other side (the html side)

<script src="{% static 'd3.v3.min.js' %}" charset="utf-8"></script>
<script type='text/javascript'> // the type text/javascript is key here!
var data= {{formattedData|safe}} // now you can just reference data with no need to use d3.json.
//Critical that there is no quotation marks here and this is where you denote safe!

//Insert the rest
//of Fernando's code here
//minus the last '});'
//as that ends the d3.json function call
</script>

Anyways, I hope this saves someone some time with Django and/or D3 as this solves two issues at once.