I have received my share of unhelpful advice such as: follow your dreams, don’t eat eggs, and eat eggs. However, the most repetitive and annoying thing that I am told to do is “learn to code.”

I would bet that most of the people that say learn to code do not know how to code themselves. Anyone with any sort of working knowledge in programming languages would add some specificity to that statement such as: learn web development, data analysis, front-end, or back-end. Secondly, 99% of people do not need to understand computer science. All they need to know how to make simple scripts to automate some of their administrative tasks.

My chosen field is finance, which involves a lot of data analysis. So, it would make sense for me to learn how to learn how to program using “Data Science” methods. Python and R are great languages for finance as they are intuitive and have extensive finance related libraries that allows non-native programmers to stand on the shoulders of giants.

Not standing on the shoulders of giants and trying to learn programming from the ground up is the biggest mistake I’ve seen a lot of people make and is probably the reason why a lot of people give up or don’t even try in the first place.

In order to understand the basics of Python syntax and it’s capabilities, I shelled out the $250 or so for Code Academy Pro. While this isn’t necessary, I found that I would be more inclined to stick with something that I paid for as opposed to going through the various free online courses. Code Academy also includes a bunch of projects that you can use to demonstrate your skills on LinkedIn or for an interview.

Next I’m going provide some instructions so you will be able to run Python.

First thing you’re going to have to do is install a distribution so you will be able to write code on your own computer. If you are primarily doing data analysis, Anaconda is your best bet. (Link below for the download and installation instructions).

https://docs.conda.io/en/latest/miniconda.html

After installation run the Anaconda powershell prompt and you’ll see something like this.

And you’ll feel something like this.

As I mentioned there are tons of packages so we can stand on the shoulders of giants. For data analysis there are a few essentails.

• pandas
• scipy
• matplotlib
• statsmodels
• seaborn
• jupyter notebook

To install these packages, type the commands below into the powershell.At this point, you’ll get prompted to install package dependencies. Answer ‘y’ and you’re almost there. Once you do this for all the packages listed above, and you will be ready to go.

conda install pandas

Jupyter notebook allows you to run code by blocks as opposed to running an entire program. This makes it easy to run code, see the output, and explain the process/results. To open it type the following into the powershell prompt.

jupyter notebook

After a few moments, jupyter notebook will open in a tab in your browser. From there you can open up python files, run code, and perform analysis like the image I have below.

Stay tuned for more posts on data analysis for finance as I learn new skills!