Working with SQLite Databases using Python and Pandas

SQLite is a database engine that makes it simple to store and work with relational data. Much like the csvformat, SQLite stores data in a single file that can be easily shared with others. Most programming languages and environments have good support for working with SQLite databases. Python is no exception, and a library to access SQLite databases, called sqlite3, has been included with Python since version 2.5. In this post, we’ll walk through how to use sqlite3 to create, query, and update databases. We’ll also cover how to simplify working with SQLite databases using the pandas package. We’ll be using Python 3.5, but this same approach should work with Python 2.

Before we get started, let’s take a quick look at the data we’ll be working with. We’ll be looking at airline flight data, which contains information on airlines, airports, and routes between airports. Each route represents a repeated flight that an airline flies between a source and a destination airport.

All of the data is in a SQLite database called flights.db, which contains three tables – airports, airlines, and routes. You can download the data here.

https://www.dataquest.io/blog/python-pandas-databases/

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