STA 492 2.0/ ASP 460 2.0 Data Visualisation

Lecturer-in-charge:

Dr Thiyanga S. Talagala

Email:

ttatalagala@sjp.ac.lk

Course outline:

Available on LMS

Policies and regulations:

To access important information regarding the unit, please go to the course Learning Management System (LMS) page. Click here to go directly to the LMS.

Weekly Schedule:

Week No. Date Topic Reading Exercise Assignments
1 April 30, 2024 Introduction to Data Viualisation Gestalt Law in Photography Assignment 1
2 May 14, 2024 Grammar of Graphics ggplot2: Elegant Graphics for Data Analysis (3e) Perform an EDA on penguins dataset using ggplot2. None
3/4 May 21, 2024/ May 28, 2024 Beyond Basics: Elevate Your Plots Perform EDA on worldbank dataset. None
5 June 4, 2024 Visualising Qualitative Variables (on their own, with another qualitative variable, with quantitative variables) None
6 June 11, 2024 Visualising Distributions The Data Visualisation Catalogue - Distributions Visualize the distribution of dengue in 25 districts in Sri Lanka. Data available at: https://denguedatahub.netlify.app/
7 June 18, 2024 Time series visualisation - part 1 Chapter 2: Time Series Graphics denguedatahub::srilanka_weekly_data - visualise the data
8 June 25, 2024 Feature-based time series visualisation [Calendar-based graphics]https://pkg.earo.me/sugrrants/articles/frame-calendar.html Visualising pedestrian counts in Melbourne city
9 July 2, 2024 Creating Interactive dashboards with R Assignment 2 - Part 1 visit Google Classroom
10 July 9, 2024 Spatial Visualisation Assignment 2 - Part 2 visit Google Classroom
11 July 16, 2024 Discussion of Answers to Assignment 2-part 1
12 July 23, 2024 Spatial Visualisation with leaflet and mapview
13 July 30, 2024 High-dimensional Visualisation

Datasets

  1. Pedestrian counts in Melbourne city
library(sugrrants)
data(hourly_peds)
  1. Tickets issued for parking violations in the city of Philadelphia, Pennsylvania in 2017
library(tidyverse)

philly <- read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-12-03/tickets.csv")
  1. Emission data
emissions <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2024/2024-05-21/emissions.csv')
emissions

4 ToothGrowth

ToothGrowth

Take an appropriate visualization to show the relationship between supp, dose and mean tooth growth.