My R Journey: Harkanwal Singh

Harkanwal Singh is a data visualisation programmer, currently working at Westpac NZ. Previously, he established and led the data journalism desk at the New Zealand Herald. He is passionate about visualisation as code. He programs in R, JavaScript and Python. He enjoys teaching data visualisation in his own time. He loves reading words and code, both preferably of others.

Why did you decide to learn R?

In 2012, I convinced the editors in parent company of my newspaper to hire me as a data journalist. There was no roadmap in NZ newsrooms, as I was the first hire. I was ardently following the New York Times graphics work and discovered they used R. That's how I decided to learn R.

I was ardently following the New York Times graphics work and discovered they used R. That's how I decided to learn R.

It was amusing that a programming language developed at the University of Auckland wasn't known in NZ newsrooms. But the fact that there was a local community available via Twitter played a part in the decision as well. I remember one of my earliest interactions on Twitter was looking at Luis Apiolaza's analysis of NZ school data using R.

How easy or difficult was learning R?

I found the interactive data analysis alluring, but pre-tidyverse the challenge was having a coherent learning model. In hindsight, everything appears easy once you have learnt it. I was learning without structure and resources most helpful at the time included StackOverflow. The growth in the amount of material available to learn has been astonishing. I greatly admire Tidy Tuesday screencasts from David Robinson. The two resources that caused the biggest shift were R for Data Science and Advanced R.

In what ways has learning changed your work?

Working in visualisation, one of the hardest things is figuring out the audience questions. R has helped me greatly in developing quick prototypes, visualising data quickly to test with the audience. As a journalist, it meant sharing work early with sources and other journalists I collaborated with. For example, if I was developing a crime visualisation, at the same time I was providing few hundred static plots to journalists to understand the data.

I found value in automating and recording tasks which others might do in Excel.

The most significant change has been how I think about data analysis. R is my first language for data inquiry. I found value in automating and recording tasks which others might do in Excel. Lately, the combination of developing simple data pipelines and RMarkdown is allowing me to unlock value in a more corporate environment.

What do you think people considering learning R might not appreciate about it?

Firstly, the value of community. Learning is a social act, it is easy to draw value from a community which takes such joy in sharing.

Learning is a social act, it is easy to draw value from a community which takes such joy in sharing.

As a beginner, it's worthwhile to know that it doesn't take long for R to make a significant impact on your work. As an intermediate user, the surprising thing is how much you keep unlocking as you spend more time writing and thinking about your code.