I am not a developer. I've never really written code. Sure, I can write a pretty crazy Excel function, and I've played a bit with some basic web languages, but I've never been able to feed a computer instructions, and have it spit out a result that I wanted.
When I joined Dataiku, I started getting more and more exposed to people working in Python, R, and other languages.
As I started doing more advanced demos with prospects and clients, I realized that I needed to be able to present the code-oriented capabilities of Data Science Studio more confidently. So I took the plunge, and decided to learn to write a bit of Python.
And you know what? I should have done it much earlier.
What's a Jupyter Notebook anyway?
Jupyter Notebooks give you a quick and easy way to develop and debug your code. The basic principle is that you break your code up into chunks ("cells" in Notebook terminology) that you can then execute one by one.
This is important because it allows you to quickly identify where in your 50 (or 500, or 5,000) lines of code you made a mistake. And when you're getting started, you're going to make lots of mistakes.
Notebooks also give you the ability to insert text cells into your code. Going well beyond simple code comments, these cells allow you track what you are working on, exchange ideas with colleagues, and put your code into order
How can I get started with a Jupyter Notebook?
Jupyter Notebooks are an open source tool that you can download directly from the project page.
They are also built into Data Science Studio (DSS). With the free Community Edition, you can download and install DSS and start working with your data quickly.
Specifically, the fact that DSS manages connections to data and gives you an environment where you can develop your code and then integrated it into your workflow is a big time saver. For a beginner like me, it made getting started that much easier.
Any tips to using Jupyter Notebooks in Data Science Studio?
Indeed, there are a few points that will help you get going more quickly, especially in terms of connecting to your data.
I've recorded a short video that walks you through these steps:
The combination of Jupyter Notebook and Data Science Studio made learning to code in Python super simple. I wouldn't have known where to start without them!