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Once you've finished reading the tutorial, you know how to use the
Django-dataplot API to make plot files. The next step is to make these
plots dynamically generated by passing them input data from your
database using Django models.

Here is an example from the bike app (dataplot/bike/models.py) that is
bundled with dataplot.

from dataplot import R
class RideManager(models.Manager):
    def __init__(self):
        self.odoplot=R.TimeSeries(
            'allrides', # base plot name after MEDIA_ROOT
            self.get_odoplot_args, # callable that returns args for R
            )
    def get_odoplot_args(self):
        qs=self.all()
        return {
            'd':[ride.date.strftime("%s") for ride in qs],
            'y':[ride.distance for ride in qs],
            'transform':'cumulative',
            }

In this example, RideManager is instantiated (dataplot/bike/models.py)
as Ride.objects. From the URLconf (dataplot/bike/urls.py), we see that
Ride.objects.odoplot is mapped to the context variable
"plot". Finally, from the template
(dataplot/bike/templates/bike/ridelist.html), we see that the template
code {{plot.to_html}} is all that is needed to render the plot.

If you want to see some examples of dataplot in action, you can give
the bike app a test drive. This needs some more setup:

- Add 'dataplot.bike' to your settings.INSTALLED_APPS.

- Add the following line to your URLconfs:
  (r'^bike/',include('dataplot.bike.urls')),

- Create the data tables with 

$ python manage.py syncdb

Now try vising that bike/ URL you specified in your URLconf. You
should be able to see a time series plot and 2 scatterplots.

Inspecting the other plots in bike/models.py should reveal some
strategies for making your own plots.