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توضیحات

A Django app to plot charts and pivot charts directly from the models. Uses HighCharts and jQuery JavaScript libraries to render the charts on the webpage.

ویژگی	مقدار
سیستم عامل	-
نام فایل	django_chartit2-0.2.2
نام	django_chartit2
نسخه کتابخانه	0.2.2
نگهدارنده	[]
ایمیل نگهدارنده	[]
نویسنده	Grant McConnaughey
ایمیل نویسنده	grantmcconnaughey@gmail.com
آدرس صفحه اصلی	https://github.com/grantmcconnaughey/django-chartit2
آدرس اینترنتی	https://pypi.org/project/django_chartit2/
مجوز	BSD

################ Django-Chartit 2 ################ .. image:: https://readthedocs.org/projects/django-chartit2/badge/?version=latest :target: http://django-chartit2.readthedocs.org/en/latest/?badge=latest :alt: Documentation Status .. image:: https://travis-ci.org/grantmcconnaughey/django-chartit2.svg?branch=master :target: https://travis-ci.org/grantmcconnaughey/django-chartit2 .. image:: https://coveralls.io/repos/grantmcconnaughey/django-chartit2/badge.svg?branch=master&service=github :target: https://coveralls.io/github/grantmcconnaughey/django-chartit2?branch=master 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 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). ======== 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. ============================================= Improvements from the original Django-Chartit ============================================= - Added Python 3 compatibility - Added Django 1.8 and 1.9 compatibility - Added documentation to ReadTheDocs - Added automated testing via Travis CI - Added test coverage tracking via Coveralls ============ Installation ============ You can install Django-Chartit 2 from PyPI. Just do :: $ pip install django_chartit2 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. 1. Create a ``DataPool`` or ``PivotDataPool`` object that specifies what data you need to retrieve and from where. 2. Create a ``Chart`` or ``PivotChart`` object to plot the data in the ``DataPool`` or ``PivotDataPool`` respectively. 3. Return the ``Chart``/``PivotChart`` object from a django ``view`` function to the django template. 4. 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>    {% 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 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 the ``load_charts`` filter in the django template to render the chart. :: <head>    {% load chartit %} {{ rainpivchart|load_charts:"container" }} </head> <body> <div id='container'> Chart will be rendered here </div> </body> =============== Documentation =============== Full documentation is available `here <http://chartit.shutupandship.com/docs>`_ . ============================= Required JavaScript Libraries ============================= The following JavaScript Libraries are required for using Django-Chartit 2. - `jQuery <http://jquery.com>`_ - `Highcharts <http://highcharts.com>`_ .. note:: While ``Django-Chartit 2`` itself is licensed under the BSD license, ``Highcharts`` is licensed under the `Highcharts license <http://www.highcharts.com/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.

نحوه نصب

نصب پکیج whl django_chartit2-0.2.2:

pip install django_chartit2-0.2.2.whl

نصب پکیج tar.gz django_chartit2-0.2.2:

pip install django_chartit2-0.2.2.tar.gz