Data With Dorrie

Hi there, welcome to Data with Dorrie! This is a 7-part walkthrough where we'll dive into the process of exploring and visualizing a dataset. I've been wanting to make something like this for a while now, and I'm excited to get started.

Just to give you some context on my background, I'm a software engineer by trade and have been working specifically in the data analytics space for the last 5 years. I'm particularly interested in interactive data visualizations and think they have tremendous potential in empowering people to explore and understand the data they're interested in.

Goals

The goal of this walkthrough is to explore the whole process of building an interactive visualization, from getting our hands on some data all the way to building a tool that anyone can use. I'll chat about data, design, and coding and bring you with me in my process. I hope this guide will be a helpful tool for you in bridging a gap between raw data and creativity.

I'll be using the technologies and processes that I'm most familiar with, but overall I want to tailor this to be a little less about technical details and more about the concepts behind them. That being said, I'll share some of the technical details as we go along and will include a section at the bottom of each part with links to resources that might be helpful if you want to dive deeper into any of the topics we cover.

Defining "Interactive Data Visualization"

To understand what an "interactive data visualization" is, let's first talk about what a "data visualization" is. A data visualization is a visual respresentation of data. That's it! It's a way to take a bunch of numbers and turn them into something that we can see and understand. Ranging from simple charts to complex infographics, there is a huge spectrum of different types of data visualization. The goal of most data visualization, however, is generally universal: letting people do what we're good at (seeing and understanding patterns) and, often, letting computers do what we're bad at (processing lots of numbers).

Interactive data visualization is just data visualization with one extra dimension: interaction. While data visualization gives us some fundamental tools to tell stories with data, like color, shape, and size, interactive data visualization gives us even more, like animation, filtering, and tooltips. There are situations where a static visualization is the right tool for the job (like a printed report), but an interactive data visualization can be incredibly powerful in the right context.

You can see some examples of interactive data visualizations we've built by clicking around the Tools section on PerThirtySix's home page!

The Dataset

Now that we have an idea about what interactive data visualization is, let's talk about the data for this project. We'll be looking at a fabricated (but realistic) dataset of how my cat Dorrie and I might spend our time together during a week.

Here's the data below in table form as well as links to download it as a CSV or JSON, the two most common file formats for modern data analysis, or open it in Google Sheets:

This is an interesting dataset because it's both simple and rich. There's some element of time to this data, a bunch of different labels for activities, and different ways we can aggregate the data (combining a lot of data together to get a smaller set of data). If you want to follow along and build your own visualization, feel free to change the names and activities to something meaningful for you!

In the next section, we'll look at what we need to do with this data before we're ready to start building on top of it.