If you’re a data scientist or hoping to become one, learning Python is a necessity for your work. Even if you already know another programming language, learning Python allows you to deal with more situations and pick which language is best for the job at hand. Python is free to use and easily accessible online, so there are no excuses for neglecting to learn this important tool in any data scientist’s kit.
In this article, we’ll go through the top 10 reasons Python can boost your data science career and why it’s a must-learn programming language.
Python is one of the most popular programming languages
Not only is Python currently one of the most popular programming languages, it is also still growing! This easy-to-learn language overtook its competitors in 2014 to become the most taught introductory programming language at top universities . Not only this, but those with previous coding experience are moving away from other languages in favor of Python. According to research, 12% of coders migrate to or adopt Python over their previous coding language, this is the highest value for all languages and puts learning Python squarely on top as the best language to learn for data science careers.
There’s a huge community to help you learn
So we’ve established that Python is popular, but why does that matter? Well, more popular languages enjoy larger communities. These larger communities help new coders learn the language quicker and can provide more support when something goes wrong. Google any Python problem and you’ll quickly see that there are tonnes of other users, reporting and solving the same issues. With less time spent trying to solve issues, a data scientist can spend more time getting things done.
Easy to learn, good for beginners- powerful enough to build an app
Python is one of the easiest programming languages to learn. It’s simple enough for beginners to grasp but is also powerful enough to be able to do many different and difficult tasks. If you’re training as a data scientist, you’re probably not already familiar with the job. Python is easy to manage, this allows you to spend more time focusing on other aspects of data science.
It has easily readable coding
Some programming languages can seem like huge walls of incomprehensible text. Python is different. Instead of the typical code format, Python contains a lot of whitespace. This makes the code more clear and easily read, which means anyone can quickly and efficiently find specific sections of code to change or remove.
On top of this whitespace use, Python uses simplified syntax with natural language. This not only allows the code to write more quickly but also makes it more easily readable, so that you can have an easier time sorting and understanding data.
It’s strong and powerful
Out of all the 10 reasons to learn Python for data science this reason is one of the most important. In other languages, doing trivial or repetitive tasks would take up a lot of unnecessary time. Python can automate these trivial tasks and is so powerful that it can be used to code many large tasks other languages might struggle with.
Python is quicker than other languages
Python has a wide variety of applications
Python is incredibly versatile. There’s a wide range of frameworks available for the language and it’s great for cross-platform development . Frameworks available include Django, which encourages fast and clean high-level design and Odoo, perfect for many business applications a data scientist may need to use.
Python has deep learning libraries that are helpful for sensing and AI and can even easily and quickly interpret other languages.
Opens up other potential areas to move into
Learning Python opens up many other data science-related areas and uses; if you decide in the future to change your career, or use data science to lead into another sector, Python is the perfect language to help you get there. Here are some other potential jobs that use Python:
- Python Developer
- Software engineer
- Data journalist
- Product manager
Python users have a high salary
According to research, jobs that involve the use of Python typically pay more . On top of this, jobs that rely heavily on the programming language offer even higher salaries. Even if money isn’t your goal, it should be clear from this information that Python knowledge is in-demand and may give you an edge over other candidates when applying for a data science position.
The libraries and frameworks Python offers are best for data science
Python is a diverse language, but it also offers some specific libraries and frameworks that are simply the best option out there for data scientists. Learn Python to use frameworks such as NumPy, Theano and Keras, all of which allow you to integrate, manage and reshape large datasets.