While SQL and Python are both programming languages they are both used for vastly different things. SQL is used to extract data and gather or manipulate a database, with Python being a general-purpose programming language that allows data experimentation used to develop mobile apps, web apps, and artificial intelligence.
Below we will be having a look at both of these languages, the differences in what they can do, and how they can be used together for better results.
What is Python?
Python is a versatile high-level language scripting program language known for its wide range of applied uses in fields such as the development of web applications, machine learning, parsing, and more. It’s an easy language with flexibility and simplicity, containing only a few keywords. The language is found on most platforms and operating systems today, giving it a big advantage over others.
Many programmers prefer Python as they believe it to be the more powerful programming language. With its ease of learning, elegance, and features it can be simple for even beginners to learn how coding works, and with the right tools it can create practically anything.
What is SQL?
A few decades ago we were storing all of our data on paper, a “hard copy” that would be kept on hand in case we needed to access its information. Now that we’re moving into a digital age, we store all of our data online in what we call a database.
Whenever you think of databases, you think of SQL. SQL was created as a way for us to manipulate, access, and update any of our databases.
SQL stands for Structured Query Language and is needed for us to communicate with our databases or make any changes to it.
The most popular SQL databases are:
- MySQL
- PostgreSQL
- SQLite
Benefits of using SQL & Python
Whether you are using SQL or Python doesn’t matter as every programming language has its own assets that make them unique and allow them to do different things. For Example; SQL was created as a way for us to query and extract data with one of its most powerful features allowing us to combine data from multiple tables inside a single database. But SQL is unable to process higher-level data manipulation and transformations which is where Python comes in. Python has a data package called Pandas that makes performing data analysis more manageable. Python and SQL could be used together by using SQL to extract that data and Python to make edits to that database.
Which one to study first?
SQL is more beneficial when starting out. While not every task requires data manipulation, it’s important to know how to extract the data if you plan on going into the data analyst field. While SQL’s script is significantly larger than Python’s and, as a result, can seem overwhelming, it’s actually the easier of the two to execute as it is written in English. Having a basic understanding of SQL in Data Science can eventually lead you to understand Python a lot quicker.
