While a data scientist might have a variety of tools which they use for different purpose, most will that the Structured Query Language (SQL) is the one most important work tool a data scientist should have. For this reason, it is quite imperative and essential for a data scientist to be able to work with databases as the bulk of work done as a data scientist requires accessing and querying real life databases.
In this post, I will be highlighting the steps of working with databases from your Python terminal/script. We will be using a popular Python library named sqlalchemy for connecting our python script to the database. However, I will first be going into the process of creating a database locally on your system. For starters, there are different database management systems; MySQL, PostgreSQL, MongoDB etc. For this post, we will be creating a postgres database. Need to say that all the database systems listed previously have very similar syntax with just little variations.

#python #database #sqlalchemy