There is no doubt that Python has become one of the premier programming languages operating under open–source guidelines. If you were anything like I was pre–programming, Python sounded more like an animal than a coding platform. Thinking back to the time I spent pre–Data Science and pre–Python, there are a few questions that I would have been much better off finding the answer to then.
- What is ‘Python’ and how do I know if I need to learn it?
Python is an open–sourced programming language that can be used for operations as complex as image recognition, deep learning, and machine learning models to operations as simple as addition and subtraction. The ‘open–sourced’ part of Python is one of the reasons that the language is so beloved and used so extensively. In short, Python being open–source means that all of the code that is written to make the language what it is, is posted online — for free — to the public. Python, in its own right, is technically a language with its own library of operations. However, most of its value comes from the libraries that are written and revised for it by its users. Libraries can be thought of as complex packages that equip users with the ability to modify text, numbers, visualizations, and more.
You will know that you need to learn Python when the other data management programs that you use begin to fall short of the amount of your data that they can process or the things that they can do for you (in Microsoft Excel that’s 1,048,576 rows by 16,384 columns). Depending on your employment situation and the kind of data that you are working with, you could find yourself being introduced to Python as early as your first day.
2. What do I do when I have a question or find bugs/errors in my code?
There are a seemingly innumerable amount of forums and pages dedicated to answering even the most obscure or granular question that you can think of. The community surrounding Python (as well as many other programming languages) is as wise as it is voluminous. Nearly all of the libraries built for Python have extensive documentation detailing the inputs and outputs of different functions and methods that you can use with your data.
3. How do I know when I’ve finished learning Python?
You will never truly be done learning Python because it is constantly being updated and modified (inserts pun about a python’s molting). There are hundreds and possibly even thousands of libraries that are available for use in Python, each of which having many different built–in capabilities.
The answer to this final question has had me equally frustrated and curious. I am someone who prides myself on my tenacity and unwillingness to quit. This is a quality that has gotten me through huge amounts of work and has given me just as much of it. It can be said that there is always room to improve at anything that you do; that is twice as true when it comes to Python. There is a vast collection of documentation already out there and by the time that you’ve read through one library, another one will have already been developed .