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COMU3120 Assessment 3: Coding and Conceptualising Student: Kewen Zhao Tutor: Leah Henrickson Due date: 13/5/2024 The dataset: https://rspca.sfo2.cdn.digitaloceanspaces.com/public/Uploads/annual- statistics/RSPCA-Australia-Annual-Statistics-2022-2023.pdf

The high cost of living in Australia has led to a notable rise in the surrender and abandonment

of pets; while popular pets like cats and dogs often find new homes in RSPCA shelters, other

animals face the unfortunate reality of being euthanised due to overcrowding; thus, this

dataset seeks to raise awareness among Australians about the challenges faced by less popular

animals (Travers & French, 2023).

Part 1:  Visualisation 1- Barplot Source: RSPCA, (2023), RSPCA Australia Annual Statistics The barplot displays the outcomes of dogs received by RSPCA shelters nationwide from

2022 to 2023, arranged in descending order. 'Rehomed' claims the top spot on the chart, as the

RSPCA successfully placed nearly 8,000 dogs in new homes. It is followed by 'reclaimed',

with almost 5,000 dogs being reunited with their owners.

It is evident that dogs are a

favoured choice among Australians when it comes to adopting pets. Unfortunately, the shelter

continues to euthanise around 3000 dogs. Within the community, there is a disagreement

regarding the health and treatability of some of these dogs (Chua et al., 2023).

The codes used to generate the first visualisation #import the dataset int R

dogsreceived<-read.csv ("22-23 received dogs.csv") #using barplot()function and 'Count' values in the dataset to make our base plot barplot (dogsreceived$Count) #using only the first 7 of the dataset= only dogs barplot (dogsreceived$Count[1:7]) #naming each bar and making each label perpendicular to the axis barplot (dogsreceived$Count[1:7], name.arg=dogsreceived$Status[1:7], las=2) #sorting 1-7 data from the most to the least

dogsreceived_sorted<-dogsreceived[order (-dogsreceived$Count[1:7]),] #using barplot()function again, and adding xlab, ylab,and main barplot (dogsreceived_sorted$Count[1:7], names.arg =dogsreceived_sorted$Status[1:7],

xlab="Outcomes of dogs ", ylab="Number of dogs", las=2, main=" Dogs outcomes from

2022-2023") #installing and activating RColorBrewer install.packages ("RColorBrewer") library (RColorBrewer) #YlGnBu is the variable for the palette's first 7 colours

display.brewer.all () YlGnBu<- brewer.pal (7, "YlGnBu") #adding the colours to the barplot barplot (dogsreceived_sorted$Count[1:7], names.arg =dogsreceived_sorted$Status[1:7],

xlab="Outcomes of dogs", ylab="Number of dogs", las=2, main="Dogs outcomes from 2022- 2023", col=YlGnBu) # extending the y-axis scale and decreasing the size of main and axis words barplot (dogsreceived_sorted$Count[1:7], names.arg =dogsreceived_sorted$Status[1:7],

xlab=" Outcomes of dogs ", ylab="Number of dogs", las=2, main="Dogs outcomes from

2022-2023", col=YlGnBu, ylim=c(0,8000), cex.axis = 0.8, cex.names = 0.6, cex.main=0.9)  Visualisation 2- Stacked barchart Source: RSPCA, (2023), RSPCA Australia Annual Statistics This stacked bar chart presents a comparison of the outcomes of various animals, including

dogs, cats, and other animals, between the years 2022 and 2023. There is no denying that a

much larger number of other animals are euthanised compared to dogs and cats, more than

doubling the count. Nevertheless, their adoption rate is significantly lower than that of dogs

and cats. Despite the financial constraints and lack of necessary infrastructure in many

Australian households, the low adoption rate of other animals like horses can be attributed to

a general disregard for their well-being. The codes used to generate the second visualisation #importing the same dataset into R animalsreceived<-read.csv ("22-23 received animals.csv") #installing and activating ggplot2 Install.packages ("ggplot2") library (ggplot2) #creating data animalsreceived$Status<-factor (animalsreceived$Status, level=c ("Reclaimed", "Returned",

"Rehomed", "Currently in Care", "Transferred", "Euthanased", "Other", replace=TRUE)) animalsreceived$Animals<-factor (animalsreceived$Animals, level=c ("Dogs", "Cats",

"Other animals", replace=TRUE)) #using ggplot()function and gemo_bar() to make base stacked chart ggplot (animalsreceived, aes (x=Status, y=Count, fill=Animals))+geom_bar (stat = "identity",

position = "stack")

#installing and activating RColorBrewer install.packages ("RColorBrewer") library (RColorBrewer) #Set2 is the variable for the palette's first 3 colours

Set2<- brewer.pal (3, "Set2") #adding the colours, legend title, title, xlab, ylab ggplot (animalsreceived, aes(x=Status, y=Count, fill=Animals))+geom_bar (stat = "identity",

position = "stack") + scale_fill_brewer (Set2) + guides (fill=guide_legend (title="Animals")) + labs(title="Animals received nationally by the RSPCA for 2022-2023")+ xlab ("Outcomes

of animials")+ ylab ("Number of animals") # tilting each label by 15 degrees along the x-axis to make labels readable, and extending

the y-axis scale ggplot (animalsreceived, aes(x=Status, y=Count, fill=Animals))+geom_bar (stat = "identity",

position = "stack") + scale_fill_brewer (Set2) + guides (fill=guide_legend (title="Animals")) + labs(title="Animals received nationally by the RSPCA for 2022-2023")+ xlab ("Outcomes

of animials")+ ylab ("Number of animals")+ theme_classic()+ theme (axis.text.x =

element_text (angle=15))+ ylim (0,40000) Training sources that I used in my self-directed learning： R CHARTS, (2024), https://r-charts.com/part-whole/stacked-bar-chart-ggplot2/ Holtz, (n.d.), https://r-graph-gallery.com/48-grouped-barplot-with-ggplot2.html RPubs, (2021), https://rpubs.com/techanswers88/stackedbarcharts

Part 2:

References: Chua, D., Rand, J., & Morton, J. (2023). Stray and Owner-Relinquished Cats in Australia— Estimation of Numbers Entering Municipal Pounds, Shelters and Rescue Groups and

Their Outcomes, 13(11). https://doi.org/10.3390/ani13111771 Holtz, Y. (n.d.). Grouped, stacked and percent stacked barplot in GGPLOT2. The R Graph

Gallery. https://r-graph-gallery.com/48-grouped-barplot-with-ggplot2.html Palladino, V. (2013, February 6). Gun-death data boldly illustrates stolen years. Wired.

https://www.wired.com/2013/02/periscopic-gun-statistic-visualization/ R CHARTS. (2024, January 4). Stacked bar chart in GGPLOT2. A collection of charts and

graphs made with the R programming language.

https://r-charts.com/part-whole/stacked-bar-chart-ggplot2/ RPubs. (n.d.). Stacked Bar Charts. https://rpubs.com/techanswers88/stackedbarcharts Travers, P., & French, E. (2023, May 2). “rate of abandonment unacceptable”: Animal

shelters overflowing as pet surrenders reach all-time high. ABC News.

https://www.abc.net.au/news/2023-05-02/animal-shelters-overflowing-with-record-pet- surrenders/102284546 Zhang, Y., Reynolds, M., Lugmayr, A., Damjanov, K., & Hassan, G. M. (2022). A visual

data storytelling framework. Informatics, 9(4), 73.

https://doi.org/10.3390/informatics9040073 Appendix: The eyes in Part 2’s visualisaton in Part 2 were taken from posts by “Faye L” on Little Red

Book (Xiaohongshu).