RFE: Support for list sources

Django-Chartit

Django Chartit is a Django app that can be used to easily create charts from the data in your database. The charts are rendered using Highcharts and jQuery JavaScript 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).

Changelog

master
- Update demo with an example of how to pass legendIndex as an option to a data serie. Closes #48.
- Update demo with an example of how to change the label of any term instead of using the default one. Closes #46.
0.2.9 (January 17, 2017)
- Enable pylint during testing but don't block Travis-CI on failures. Closes #42.
- Handle unicode data in pie and scatter plot charts under Python 2.7. PR#47.
0.2.8 (December 4, 2016)
- PivotChart and PivotDataPool will be deprecated soon. Both are marked with deprecation warnings. There is a lot of duplication and special handling between those classes and the Chart and DataPool classes which make it harder to expand the feature set for django-chartit. The next release will focus on consolidating all the functionality into Chart and DataPool so that users will still be able to draw pivot charts. You will have to construct your pivot charts manually though!
- DataPool terms now supports model properties. Fixes #35. Model properties are not supported for PivotDataPool! WARNING: when using model properties chartit can't make use of ``QuerySet.values()`` internally. This means results will not be groupped by the values of the fields you supplied. This may lead to unexpected query results/charts!
- DataPool now supports RawQuerySet as data source. Fixes #44. RawQuerySet is not supported for PivotDataPool! WARNING: when using ``RawQuerySet`` don't use double underscores in field names because these are interpreted internally by chartit and will cause exceptions. For example don't do this ``SELECT AVG(rating) as rating__avg`` instead write it as ``SELECT AVG(rating) as rating_avg``!
- README now tells how to execute demoproject/
0.2.7 (September 14, 2016)
- Don't use super(self.__class__) b/c that breaks chart class inheritance. Fixes #41
0.2.6 (August 16, 2016)
- Merge chartit_tests/ with demoproject/
- Load test DB with real data to use during testing
- Add more tests
- Update the path to demoproject.settings when building docs. Fixes a problem which caused some API docs to be empty
- Fix ValueError: not enough values to unpack (expected 2, got 0) with PivotChart when the QuerySet returns empty data
- Dropped requirement on simplejson
- Properly handle unicode data in Pivot charts. Fixes #5
- Demo project updated with Chart and PivotChart examples of rendering DateField values on the X axis
- Allow charting of extra() or annotate() fields. Fixes #8 and #12
- Refactor RecursiveDefaultDict to allow chart objects to be serialized to/from cache. Fixes #10
- Add information about supported 3rd party JavaScript versions. Fixes #14
0.2.5 (August 3, 2016)
- Workaround Python 3 vs. Python 2 list sort issue which breaks charts with multiple data sources displayed on the same axis!
- Make demoproject/ compatible with Django 1.10
0.2.4 (August 2, 2016)
- Fix for get_all_field_names() and get_field_by_name() removal in Django 1.10. Fixes #39
- Updated for django.db.sql.query.Query.aggregates removal
0.2.3 (July 30, 2016)
- New to_json() method for charts. Useful for creating Highcharts in AJAX
- Merged with django-chartit2 fork by Grant McConnaughey which adds Python 3 and latest Django 1.8.x and 1.9.x support
- Allow dictionary fields in conjunction with lambda fields. Closes #26
- Documentation improvements
- Lots of code cleanups and style improvements
0.2.2 as django-chartit2 (January 28, 2016)
- Fixed another issue that prevented installation via PyPI
0.2.0 as django-chartit2 (January 20, 2016):
- Fixed issue that could prevent installation via PyPI
0.1 (November 5, 2011)
- Initial release of django-chartit

Features

Plot 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.
Python 3 compatibility
Django 1.8 and 1.9 compatibility
Documentation to ReadTheDocs
Automated testing via Travis CI
Test coverage tracking via Coveralls

Installation

You can install Django-Chartit from PyPI. Just do :

$ pip install django_chartit

Then, add chartit to INSTALLED_APPS in "settings.py".

You also need supporting JavaScript libraries. See the Required JavaScript Libraries section for more details.

How to Use

Plotting a chart or pivot chart on a webpage involves the following steps.

Create a DataPool or PivotDataPool object that specifies what data you need to retrieve and from where.
Create a Chart or PivotChart object to plot the data in the DataPool or PivotDataPool respectively.
Return the Chart/PivotChart object from a django view function to the django template.
Use the load_charts template tag to load the charts to HTML tags with specific ids.

It is easier to explain the steps above with examples. So read on.

How to Create Charts

Here 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 the load_charts filter 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 Charts

Here 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 django.db.models import Avg
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'],
                'legend_by': 'city',
                'top_n_per_cat': 3,
            },
            'terms': {
                'avg_rain': Avg('rainfall'),
            }
        }]
    )

    # 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 the load_charts filter 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>

Rendering multiple charts

It is possible to render multiple charts in the same template. The first argument to load_charts is the Chart object or a list of Chart objects, and the second is a comma separated list of HTML IDs where the charts will be rendered.

When calling Django's render you have to pass all you charts as a list:

return render(request, 'index.html',
             {
                'chart_list' : [chart_1, chart_2],
             }
        )

Then in your template you have to use the proper syntax:

<head>
    {% load chartit %}
    {{ chart_list|load_charts:"chart_1,chart_2" }}
</head>
<body>
    <div id="chart_1">First chart will be rendered here</div>
    <div id="chart_2">Second chart will be rendered here</div>
</body>

Demo

The above examples are just a brief taste of what you can do with Django-Chartit. For more examples and to look at the charts in actions, check out the demoproject/ directory. To execute the demo run the commands :

cd demoproject/
PYTHONPATH=../ python ./manage.py migrate
PYTHONPATH=../ python ./manage.py runserver

Documentation

Full documentation is available here .

Required JavaScript Libraries

The following JavaScript Libraries are required for using Django-Chartit.

jQuery - versions 1.6.4 and 1.7 are known to work well with django-chartit.
Highcharts - versions 2.1.7 and 2.2.0 are known to work well with django-chartit.

Note

While Django-Chartit itself is licensed under the BSD license, Highcharts is licensed under the Highcharts license and jQuery is 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.

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django-chartit's Introduction

Django-Chartit

Changelog

Features

Installation

How to Use

How to Create Charts

How to Create Pivot Charts

Rendering multiple charts

Demo

Documentation

Required JavaScript Libraries

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