Python is a programming language that is a crucial ingredient for Data Science and vice versa. Python provides excellent functionality to deal with mathematics, statistics and scientific functions. It also provides libraries that facilitate the work of a Data Scientist. What sets Python apart is the fact that it’s a general-purpose language. This Swiss army knife of programming languages used to build websites and at the same time lets you train autonomous vehicles. When it comes to more specialised data science fields like Deep learning, Python again offers possibilities like no other. Nowadays, even for the most specific statistical or machine learning tasks, Python outperforms (or is at least as good as) statistical programming language R.
But there is more:
- Open Source
Python is open source, which makes it freely usable and distributable. Python runs on Windows and Linux environments, but it can also be ported to multiple platforms. Python is developed by a large community, and they work on the needs of the users with resulting in many open source libraries for Data Processing, Data Analysis, Data Visualisation, Statistics, Machine Learning and so on.
- Simple & Easy to Learn
The syntax of Python focusses on simplicity and readability, which makes it easy to learn for beginners. Moreover, Python offers the possibility to achieve the same task using fewer lines of code compared to older programming languages such as Java. Instead of focussing on the code, this allows you to focus on the primary goal.
- Good Support
Since Python is gaining popularity and used in both the academic world and the industrial world, more users contribute information on their user experience. This results in more support material available for free, such as open-source projects, active Q&A forums and documentation.
Python is the most commonly used programming language when it comes to data science. Therefore, this is our first choice when it comes to developing data science solutions. However, if the circumstances require it, we are also happy to work in, for example, R.