Take-home Exercise 1
Creating enlightening and truthful data visualizations involves focusing on accuracy, transparency, and the ability to effectively communicate insights. It’s about presenting data in a way that is both informative and aesthetically pleasing, ensuring the audience can grasp the information quickly and accurately.
Overview
This handout provides the context, task, expectations and grading criteria of Take-home Exercise 1. Students must review and understand them before getting started with the take-home exercise.
Setting the scene
A local online media company that publishes daily content on digital platforms is planning to release an article on demographic structures and distribution of Singapore in 2024.
The Task
Assuming the role of the graphical editor of the media company, you are tasked to prepare at most three data visualisation for the article.
The task will be completed in two phases:
- Phase 1: Designing your own data visualisation.
- Phase 2: Selecting one submission provided by your classmate, critic three good design principles and three areas for further improvement. With reference to the comment, prepare the makeover version of the data visualisation.
The Data
To accomplish the task, Singapore Residents by Planning Area / Subzone, Single Year of Age and Sex, June 2024 dataset shares by Department of Statistics, Singapore (DOS) should be used.
The Designing Tool
The data should be processed by using appropriate tidyverse family of packages and the data visualisation must be prepared using ggplot2 and its extensions.
No interactive data visualisation are required.
The Write-up
The write-up of the take-home exercise should include but not limited to the followings:
A reproducible description of the procedures used to prepare the analytical visualisation. Please refer to the senior submission I shared below.
A write-up of not more than 150 words per each data visualisation, describing and discussing the patterns reveal by each visualisation prepared.
Submission Instructions
This is an individual assignment. You are required to work on the take-home exercises and prepare submission individually.
The specific submission instructions are as follows:
- The analytical visualisation must be prepared by using R and appropriate R packages.
- The write-up of the take-home exercise must be in Quarto html document format. You are required to publish the write-up on Netlify.
Submission date
There are two submission deadlines for this take-home exercise, they are:
- Phase 1: 4th May 2025 mid-night
12:00am11:59pm. - Phase 2: 11th May 2025 mid-night
12:00am11:59pm
Learning from senior
Peer Learning
- ANDRE ONG JIA KANG
- CALVIN TAN SONG HAO
- CHAN HAN JIE
- CHIAM SHUNZHONG DAVID
- DO QUYNH TRANG
- ENRICO SEBASTIAN ENRICO SEBASTIAN DANUSANTOSO
- EVANGELINE OLIVIA SIDIHARTO
- FU YILIN
- GOH YI FANG
- HAO LIU
- HUANG PENGXIN
- HUANG ZIHAN
- JESSE EMMANUEL LUCAS
- LAU JIA YI
- LI JIANYI
- LI YUQUAN
- LIAW YING TING CELIN
- LIM KAH SIEW BELINDA
- LIU CHIH-YUAN
- LU LINSEN
- LUO YUMING
- MARGA THURA
- MIN HTET AUNG
Specially highlighted: 3.2 Age Pyramid of Top 24 Planning Areas.
- NG JIN YAO
- NG WEE TINN SHERMAINN
- NGUYEN NGUYEN HA
- NGUYEN PHUONG HOA
- NOR HENDRA BIN ABDUL RAHMAN
- PATRICIA TRISNO
- PENG HSIAO-YUAN
- RAJESH BABU SANTIGARI
- SANDRA JACOB
- SARIYANTI HARTIONO
- STEFANIE FELICIA
- TA NGUYEN THAO NGUYEN
- TAI QIUYAN
- TAI YU YING
- TAN WENYING AUDREY
Special mentioned: Excellence design efforts 7.1 Population Pyramid and innovative idea 8. Daily Article
- TEO WEE SIANG ROY
- VANESSA RIADI
- WANG ANQI
- WANG SHENSI
- XU XINYI
- YANG LU
- YANG YAYONG
- YUAN YIHAO
- ZHANG JINGHAN
- ZHANG XUERONG