Data Visualisation | Nicola Rennie

Data Visualisation

By Nicola Rennie in Data Visualisation

October 1, 2022

Data visualisation is essential for exploratory analysis, and for effectively communicating results. Although I primarily use R for data visualisation, I also have experience of using Python, Tableau, rawgraphs, Inkscape, and Figma. I began researching what makes an effective data visualisation during my PhD when trying to visualise large volumes of data, and started contributing to #TidyTuesday (a weekly data challenge aimed at the R community). You can view my #TidyTuesday contributions on a separate page: nrennie.rbind.io/portfolio/tidytuesday.

#30DayChartChallenge

The #30DayChartChallenge is a data visualisation challenge organised by Cédric Scherer and Dominic Royé. Participants make one chart each day of the challenge, inspired by the daily prompt. The prompts are also split across 5 different categories. Check out the challenge at twitter.com/30DayChartChall. I used a range of tools to create my charts, including R, Python, Tableau, rawgraphs, Inkscape, and Figma. Most of the charts I created were built in R, but I used at least one “new” tool for each of the six categories.

See More #30DayChartChallenge 2022

Comparisons

Day 1 (Part to whole) in R

Day 2 (Pictogram) in R

Day 3 (Historical) in R

Day 4 (Flora) in Tableau (left) and R (right)

Day 5 (Slope) in R

Day 6 (Our World in Data) in R

Distributions

Day 7 (Physical) in R

Day 8 (Mountains) in Figma

Day 9 (Statistics) in R

Day 10 (Experimental) in R

Day 11 (Circular) in R

Day 12 (The Economist) in R

Relationships

Day 13 (Correlation) in R

Day 14 (3-Dimensional) in Python and R

Day 15 (Multivariate) in R

Day 16 (Environment) in R

Day 17 (Connections) in R

Day 18 (OECD) in R

Time Series

Day 19 (Global Change) in R

Day 20 (New Tool) in Inkscape

Day 21 (Down and Upwards) in R

Day 22 (Animation) in R

Day 23 (Tiles) in R

Day 24 (Financial Times) in R

Uncertainties

Day 25 (Trend) in R

Day 26 (Interactive) in R

Day 27 (Future) in R

Day 28 (Deviations) in RAWgraphs and Inkscape

Day 29 (Storytelling) in R and Inkscape

Day 30 (UN Population) in R

#30DayMapChallenge

The #30DayMapChallenge is a data visualisation challenge organised by Topi Tjukanov. Participants make one map each day of the challenge, inspired by the daily prompt. Check out the challenge on GitHub, or see contributions on the official website.

See More #30DayMapChallenge 2021

Day 1 (Points)

Day 2 (Lines)

Day 3 (Polygons)

Day 4 (Hexagons)

Day 5 (OpenStreetMap)

Day 6 (Red)

Day 7 (Green)

Day 8 (Blue)

Day 9 (Monochrome)

Day 10 (Raster)

Day 11 (3D)

Day 12 (Population)

Day 13 (Natural Earth)

Day 14 (Map with a new tool)

Day 15 (Map without a computer)

Day 16 (Urban/rural)

Day 17 (Land)

Day 18 (Water)

Day 19 (Island(s))

Day 20 (Movement)

Day 21 (Elevation)

Day 22 (Boundaries)

Day 23 (GHSL)

Day 24 (Historical map)

Day 25 (Interactive map)

Day 26 (Choropleth map)

Day 27 (Heatmap)

Day 28 (The Earth is not flat)

Day 29 (Null)

Day 30 (Metamapping)

Viz For Social Good

Viz For Social Good volunteers create informative and impactful data visualizations for mission-driven organizations across the globe. Check out the organisation here. All code is available at: github.com/nrennie/Viz_For_Social_Good

See More Viz For Social Good

Tap Elderly Women’s Wisdom for Youth (TEWWY)

Tap Elderly Women’s Wisdom for Youth (TEWWY) is an organisation which taps the wisdom of grandmothers to serve the mental health needs of vulnerable populations. TEWWY’s Mental Health Intervention Programs (MHIPs) have reached 17,975 people through its initiatives in Dar-es-Salaam’s 5 municipalities and in Kilwa, Lindi rural community. Nearly 1 in 10 people have a mental health disorder, but only 1% of the global health workforce provides mental health care. 1,397 patients answered questions about their mental health, giving scores from 0 to 3 on how often, over the last 2 weeks, they have been bothered by different problems. A score of 0 indicates that the patient answered No, whilst a score above 0 indicates the patient answered Yes. The infographics indicate the percentage of people answering Yes to each questions, split by male and female patients.

Build Up Nepal

Build up Nepal is a social business dedicated to building resilient communities and fighting poverty in rural areas of Nepal.

VFSG: Visualize Our Community

Non-profits around the world are driving positive social change but some of them lack the in-house resources to effectively tell their story with the data they have. Viz For Social Good (VFSG) helps non-profits thrive by connecting talented community members with organizations in need of data visualization skill sets. In November 2021, Viz For Social Good ran a community poll, the results of which will help shape their diversity & inclusion efforts. 224 people responded from 38 different countries.

Sunny Street

Sunny Street is changing the world by providing healthcare to the most vulnerable people in Eastern Australia. One conversation between a Sunny Street volunteer and a patient can change the course of both of their lives. Although the Covid-19 pandemic caused many clinics to be cancelled, Sunny Street volunteers had the same (or more) conversations and consultations. There has been little change in patient demographic throughout the pandemic.

DuBois Challenge

The Du Bois Challenge is part of a celebration of the data visualization legacy of W.E.B Du Bois which attempts to recreate the visualizations from the 1900 Paris Exposition using modern tools. Check out the challenge here. Born in 1868, William Edward Burghardt Du Bois was an activist, author, and scholar, being the first African-American to receive a doctorate from Harvard University. In addition, his approach to data visualisations was incredibly innovative, both in terms of his stylistic methods and in his use of using visualisations to build data-driven arguments.

Note that the text in the visualisations is taken from the original charts and uses antiquated terms to refer to populations of colour.

See More DuBois Challenge 2022

Below are my contributions to the 2022 Du Bois Challenge, with my reproduction on the left and the original on the right. The code for the reproductions can be found on GitHub.

Challenge 1

Challenge 2

Challenge 3

Challenge 4

Challenge 5

Challenge 6

Challenge 7

Challenge 8

Challenge 9

Challenge 10

See More DuBois Challenge 2021

Below are my contributions to the 2021 Du Bois Challenge, with my reproduction on the left and the original on the right. The code for the reproductions can be found on GitHub.

Challenge 1

Challenge 2

Challenge 3

Challenge 4

Challenge 5

Challenge 6

Challenge 7

Challenge 8

Challenge 9

Challenge 10

#TableauTuesday

Tableau is an interactive data visualization tool, used to make plots, dashboards, and presentations of data. Although I primarily use R to create plots and dashboards for visualising data, I’ve recently started to explore less-programmatic ways of visualising data. My portfolio of data visualisation is still under construction, and the following represents some preliminary examples of plots and dashboards I have built using Tableau. My Tableau data visualisations and dashboards can be found on my Tableau Public profile.

In order to improve my Tableau skills, I’ve started visualising #TidyTuesday data sets in Tableau as well as in R (and calling it #TableauTuesday). I dug deeper into some data from one of the #TidyTuesday challenges on European flights data from Eurocontrol. I constructed a dashboard to display information of flights leaving or arriving from six European countries, where users can filter by a date range and a set of countries they are interested in. The dashboard is available on Tableau Public. I also recreated the same dashboard using {shiny} in R, and embedded it as a new tab in the Tableau dashboard for a side-by-side comparison of R and Tableau.

See More #TableauTuesday

Posted on:
October 1, 2022
Length:
6 minute read, 1273 words
Categories:
Data Visualisation