Package: django_chartit2
The fork of Django Charit that adds support for Python 3 and Django 1.8+!Django Chartit is a Django app that can be used to easily create charts from the data
in your database. The charts are rendered usingHighchartsandjQueryJavaScript libraries. Data in your database can be plotted as simple line
charts, column charts, area charts, scatter plots, and many more chart types.
Data can also be plotted as Pivot Charts where the data is grouped and/or
pivoted by specific column(s).FeaturesPlot charts from models.Plot data from multiple models on the same axis on a chart.Plot pivot charts from models. Data can be pivoted by across multiple
columns.Legend pivot charts by multiple columns.Combine data from multiple models to plot on same pivot charts.Plot a pareto chart, paretoed by a specific column.Plot only a top few items per category in a pivot chart.Improvements from the original Django-ChartitAdded Python 3 compatibilityAdded Django 1.8 and 1.9 compatibilityAdded documentation to ReadTheDocsAdded automated testing via Travis CIAdded test coverage tracking via CoverallsInstallationYou can install Django-Chartit 2 from PyPI. Just do$ pip install django_chartit2You also need supporting JavaScript libraries. See theRequired JavaScript Librariessection for more details.How to UsePlotting a chart or pivot chart on a webpage involves the following steps.Create aDataPoolorPivotDataPoolobject that specifies what data
you need to retrieve and from where.Create aChartorPivotChartobject to plot the data in theDataPoolorPivotDataPoolrespectively.Return theChart/PivotChartobject from a djangoviewfunction
to the django template.Use theload_chartstemplate tag to load the charts to HTML tags with
specificids.It is easier to explain the steps above with examples. So read on.How to Create ChartsHere is a short example of how to create a line chart. Let’s say we have a
simple model with 3 fields - one for month and two for temperatures of Boston
and Houston.class MonthlyWeatherByCity(models.Model):
    month = models.IntegerField()
    boston_temp = models.DecimalField(max_digits=5, decimal_places=1)
    houston_temp = models.DecimalField(max_digits=5, decimal_places=1)And let’s say we want to create a simple line chart of month on the x-axis
and the temperatures of the two cities on the y-axis.from chartit import DataPool, Chart

def weather_chart_view(request):
    #Step 1: Create a DataPool with the data we want to retrieve.
    weatherdata = \
        DataPool(
           series=
            [{'options': {
               'source': MonthlyWeatherByCity.objects.all()},
              'terms': [
                'month',
                'houston_temp',
                'boston_temp']}
             ])

    #Step 2: Create the Chart object
    cht = Chart(
            datasource = weatherdata,
            series_options =
              [{'options':{
                  'type': 'line',
                  'stacking': False},
                'terms':{
                  'month': [
                    'boston_temp',
                    'houston_temp']
                  }}],
            chart_options =
              {'title': {
                   'text': 'Weather Data of Boston and Houston'},
               'xAxis': {
                    'title': {
                       'text': 'Month number'}}})

    #Step 3: Send the chart object to the template.
    return render_to_response({'weatherchart': cht})And you can use theload_chartsfilter in the django template to render
the chart.<head>
    <!-- code to include the highcharts and jQuery libraries goes here -->
    <!-- load_charts filter takes a comma-separated list of id's where -->
    <!-- the charts need to be rendered to                             -->
    {% load chartit %}
    {{ weatherchart|load_charts:"container" }}
</head>
<body>
    <div id='container'> Chart will be rendered here </div>
</body>How to Create Pivot ChartsHere is an example of how to create a pivot chart. Let’s say we have the
following model.class DailyWeather(models.Model):
    month = models.IntegerField()
    day = models.IntegerField()
    temperature = models.DecimalField(max_digits=5, decimal_places=1)
    rainfall = models.DecimalField(max_digits=5, decimal_places=1)
    city = models.CharField(max_length=50)
    state = models.CharField(max_length=2)We want to plot a pivot chart of month (along the x-axis) versus the average
rainfall (along the y-axis) of the top 3 cities with highest average
rainfall in each month.from chartit import PivotDataPool, PivotChart

def rainfall_pivot_chart_view(request):
    #Step 1: Create a PivotDataPool with the data we want to retrieve.
    rainpivotdata = \
        PivotDataPool(
           series =
            [{'options': {
               'source': DailyWeather.objects.all(),
               'categories': ['month']},
              'terms': {
                'avg_rain': Avg('rainfall'),
                'legend_by': ['city'],
                'top_n_per_cat': 3}}
             ])

    #Step 2: Create the PivotChart object
    rainpivcht = \
        PivotChart(
            datasource = rainpivotdata,
            series_options =
              [{'options':{
                  'type': 'column',
                  'stacking': True},
                'terms':[
                  'avg_rain']}],
            chart_options =
              {'title': {
                   'text': 'Rain by Month in top 3 cities'},
               'xAxis': {
                    'title': {
                       'text': 'Month'}}})

    #Step 3: Send the PivotChart object to the template.
    return render_to_response({'rainpivchart': rainpivcht})And you can use theload_chartsfilter in the django template to render
the chart.<head>
    <!-- code to include the highcharts and jQuery libraries goes here -->
    <!-- load_charts filter takes a comma-separated list of id's where -->
    <!-- the charts need to be rendered to                             -->
    {% load chartit %}
    {{ rainpivchart|load_charts:"container" }}
</head>
<body>
    <div id='container'> Chart will be rendered here </div>
</body>DocumentationFull documentation is availablehere.Required JavaScript LibrariesThe following JavaScript Libraries are required for using Django-Chartit 2.jQueryHighchartsNoteWhileDjango-Chartit2itself is licensed under the BSD license,Highchartsis licensed under theHighcharts licenseandjQueryis licensed under both
MIT License and GNU General Public License (GPL) Version 2. It is your own
responsibility to abide by respective licenses when downloading and using
the supporting JavaScript libraries.