Analyzing API Data with MongoDB, Seaborn, and Matplotlib

python_tutorials

Introduction

A commonly requested skill for software development positions is experience with NoSQL databases, including MongoDB. This tutorial will explore collecting data using an API, storing it in a MongoDB database, and doing some analysis of the data.

However, before jumping into the code let’s take a moment to go over MongoDB and APIs, to make sure we understand how we’ll be dealing with the data we’re collecting.

MongoDB and NoSQL

MongoDB is a form of NoSQL database, enabling the storage of data in non-relational forms. NoSQL databases are best understood by comparing them to their progenitor/rivals – SQL databases.

SQL stands for Structure Query Language and it is a type of relational database management tool. A relational database is a database that stores data as a series of keys and values, with each row in a data table having its own unique key. Values in the database can be retrieved by looking up the corresponding key. This is how SQL databases store data, but NoSQL databases can store data in non-relational ways.

NoSQL stands for “Not Only SQL”, which refers to the fact that although SQL-esque queries can be done with NoSQL systems, they can also

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