Using Django on existing data

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In this new entry, we will continue our Simpsons quote search engine. Up to this point, we have been accessing only data created by the application. Now, we are going to access to a pre-existing database. This is a very important step, because it enables us to create an interface to a more complex data collection and processing system that uses other technologies to create the database.
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Introducing Django REST Framework

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In the last four entries, we have been getting to know Django and its basic use. We want to use Django to create a good data source that responds to simple queries. We have seen how to get the responses in HTML. Since HTML is a structured language, we can kind-of consider that the mission is accomplished. But to serve data, a better way is to return JSON files. In this entry, we will get to know the Django REST framework that helps in creating RESTful applications, that is what we are seeking.
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A Simpsons quote search engine with Django

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In the previous entry, we created a simple Django app that returned random Simpsons quotes. The application was not interactive; that is, it did not really process the request from the client. In this entry, we will modify the previous application so it is interactive. Specifically, we will create a very simple search engine that returns the Simpson quotes that have a specific word in them.

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Drawing better graphics with Seaborn

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Drawing graphics is a key step in the process of data analysis; not only for presenting final results to other people, but also to better understand what we have in our hands. As shown in the previous entry, Pandas has a very handy graphical subsystem. Nevertheless, sometimes the simple graphics provided by Pandas may not be enough for a clear visualization. Seaborn comes to the rescue here, providing some specialized graphic types targeted for complex data sets and with emphasis on clean visualization.

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