In your journey to becoming a data analyst, you’ll encounter some difficulties and challenges. There are some important skills and notions to remember through this journey.
Keep it simple
99.5% of your problems in programming won’t involve complex solutions. You can do a lot by just manipulating lists, dictionaries, loops…
Trying to keep your code simple, documented and explainable is highly important. Follow the PEP8 standards (we’ll talk about it later) and everything will be alright.
Code, Code, Code
This is a hard truth about programming, you’ll have to practice it almost daily to get better. Think about it as learning a new language. If you want to speak russian, you’ll barely improve if you read a textbook once every two weeks.
Programming is the same, you learn a language, a logic, keywords, syntax… This needs to be practiced almost daily when you learn.
Get out of your comfort zone
Sometimes, we identify a certain way of solving a problem, and tend to approach the next problems with this same solution. It’s generally a bad idea. We do it because we are lazy. We understood a solution, we remember it, but it’s not always optimal. It’s not always the most straight-forward, the fastest, the shortest… Challenge yourself.
Learn how to search
It is extremely likely (and almost sure) that the problem you are currently stuck on has already been solved somewhere on the internet. You just need to know how to look for it.
Google is a good starting point. By making enough Python-related queries, Google will adapt its results on your result page. The first times, you might want to search “python add element to list”, but after a few weeks, if you forgot again how to do it, simply typing “add elem to list” will land the same results.
You’ll often find results of Stack Overflow, a giant tech forum, really useful. Some of the answers might be on Github too, look for a similar package, a similar project, how things were implemented…
Data analysis and data science are fields that evolve really quickly. Tools you master today might not be relevant anymore in 2 or 3 years. You need to adapt, keep training and keep learning. In this training, you’ll learn about Python. But Python is already being challenged by other languages which might become leaders in 5-6 years, who knows…
You also might want to follow relevant experts on LinkedIn or subscribe to some newsletters to see the news coming. This is great to identify new softwares, papers, libraries… to try.
Share your projects
It’s easy to share a project using Github or a personal blog. Do it. It will force you to write good code, to provide a write-up of your work and it will definitely show recruiters (if this is what you are looking for) that you know what you talk about.
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