CHANNELS CHANNELS EVERYWHERE When I joined the DVS in February of 2019, the amount of activity on DVS’s Slack was thrilling! I met incredible friends, shared various dataviz projects, learned A LOT and fanboyed/fangirled over some of my favourite data visualization practitioners. In fact, I got so inspired by our vibrant Slack community that I […]
Visualizing Indian curries and sabzis to help your family cook healthier. At Gramener, we each took up a personal data challenge over the month of December. Since my family at home had been fighting over how to share efforts in the kitchen, I chose to track the food we cooked at home across three meals […]
I’ll start off with a confession — when I was a kid, I had no idea what data visualization was. Or, should I be totally frank? Growing up, I didn’t even know the meaning of “data.” It wasn’t until my early teens that I started understanding the meaning and value of “data.” After that, it […]
Choosing good colors for your charts is hard. This article tries to make it easier. I want you to feel more confident in your color choices. And if you have no sense for colors at all, here’s my attempt to help you find good ones anyway. We’ll talk about common color mistakes I see out […]
Rolling or moving averages are a way to reduce noise and smooth time series data. During the Covid-19 pandemic, rolling averages have been used by researchers and journalists around the world to understand and visualize cases and deaths. This post will cover how to compute and visualize rolling averages for the new confirmed cases and […]
This post is an update from the previous post, “How to geocode a CSV of addresses in R”. We will be using the ggmap package again, and be sure to investigate the usage and billing policy for Google’s Geocoding API. Read full post here.
This is a quick introduction on how to get and visualize Google search data with both time and geographical components using the R packages gtrendsR, maps and ggplot2. In this example, we will look at search interest for named hurricanes that hit the U.S. mainland and then plot how often different states search for “guns.” […]
From the post: Creating a customized graph that communicates your ideas effectively can be challenging. This tutorial will introduce you to the popular R package ggplot2, its underlying grammar of graphics, and show you how to create stylish and simple graphs quickly. We will also go over some basic principles of data visualization. Read more […]
