MATH2270 Assignment 2

Introduction

This visualisation gives insight about the distribution of climatic temperature over different cities in Australia. The data for the visualisation has been taken from: Bureau of Meteorology is Australia’s national weather, climate and water agency.

library(readr)
library(googleVis)
library(dplyr)
op <- options(gvis.plot.tag="chart")


Sydney <- read_csv("~/Downloads/Sydney.csv", 
    col_types = cols(Date = col_date(format = "%d/%m/%Y")))
Syd <- gvisCalendar(Sydney, 
                    datevar="Date", 
                    numvar="Temperature",
                    options=list(
                      title="Daily Temperature in Sydney",
                      height=120,
                      calendar="{yearLabel: { fontName: 'Times-Roman',
                               fontSize: 32, color: '#1A8763', bold: true},
                               cellSize: 8,
                               cellColor: { stroke: 'red', strokeOpacity: 0.2 },
                               focusedCellColor: {stroke:'red'}}")
)

Perth <- read_csv("~/Downloads/Perth.csv", 
    col_types = cols(Date = col_date(format = "%d/%m/%Y")))
Per <- gvisCalendar(Perth, 
                    datevar="Date", 
                    numvar="Temperature",
                    options=list(
                      title="Daily Temperature in Perth",
                      height=120,
                      calendar="{yearLabel: { fontName: 'Times-Roman',
                               fontSize: 32, color: '#1A8763', bold: true},
                               cellSize: 8,
                               cellColor: { stroke: 'red', strokeOpacity: 0.2 },
                               focusedCellColor: {stroke:'red'}}")
)

Brisbane <- read_csv("~/Downloads/Brisbane.csv", 
    col_types = cols(Date = col_date(format = "%d/%m/%Y")))
Bri <- gvisCalendar(Brisbane, 
                    datevar="Date", 
                    numvar="Temperature",
                    options=list(
                      title="Daily Temperature in Brisbane",
                      height=120,
                      calendar="{yearLabel: { fontName: 'Times-Roman',
                               fontSize: 32, color: '#1A8763', bold: true},
                               cellSize: 8,
                               cellColor: { stroke: 'red', strokeOpacity: 0.2 },
                               focusedCellColor: {stroke:'red'}}")
)

Adelaide <- read_csv("~/Downloads/Adelaide.csv", 
    col_types = cols(Date = col_date(format = "%d/%m/%Y")))
Ade <- gvisCalendar(Adelaide, 
                    datevar="Date", 
                    numvar="Temperature",
                    options=list(
                      title="Daily Temperature in Adelaide",
                      height=120,
                      calendar="{yearLabel: { fontName: 'Times-Roman',
                               fontSize: 32, color: '#1A8763', bold: true},
                               cellSize: 8,
                               cellColor: { stroke: 'red', strokeOpacity: 0.2 },
                               focusedCellColor: {stroke:'red'}}")
)

Melbourne <- read_csv("~/Downloads/Melbourne.csv", 
    col_types = cols(Date = col_date(format = "%d/%m/%Y")))
Mel <- gvisCalendar(Melbourne, 
                    datevar="Date", 
                    numvar="Temperature",
                    options=list(
                      title="Daily Temperature in Melbourne",
                      height=120,
                      calendar="{yearLabel: { fontName: 'Times-Roman',
                               fontSize: 32, color: '#1A8763', bold: true},
                               cellSize: 8,
                               cellColor: { stroke: 'red', strokeOpacity: 0.2 },
                               focusedCellColor: {stroke:'red'}}")
)

Darwin <- read_csv("~/Downloads/Darwin.csv", 
    col_types = cols(Date = col_date(format = "%d/%m/%Y")))
Dar <- gvisCalendar(Darwin, 
                    datevar="Date", 
                    numvar="Temperature",
                    options=list(
                      title="Daily Temperature in Darwin",
                      height=120,
                      calendar="{yearLabel: { fontName: 'Times-Roman',
                               fontSize: 32, color: '#1A8763', bold: true},
                               cellSize: 8,
                               cellColor: { stroke: 'red', strokeOpacity: 0.2 },
                               focusedCellColor: {stroke:'red'}}")
)

Coordinates <- read_csv("~/Downloads/Coordinates.csv")
google.location <- paste(Coordinates$Lat, Coordinates$Long, sep = ":")
monitors.google <- data.frame(Coordinates, google.location)
gmap <- gvisGeoChart(monitors.google, "google.location", 
                          colorvar="Value", 
                          hovervar = "Place",
                          options=list(width=500, height=300,region= "AU"))




GT <- gvisMerge(Syd,Dar, horizontal=TRUE)
GT1 <- gvisMerge(Per,Mel, horizontal=TRUE)
GT2 <- gvisMerge(Ade,Bri, horizontal=TRUE)
GT3 <- gvisMerge(GT,GT1, horizontal=FALSE)
GT4 <- gvisMerge(GT3,GT2, horizontal=FALSE)

Average Temperature for 2016 in Major Cities in Australia

The calendars show the temperature variation over the year 2016 and the comparison map is plotted for comparing average temperature for the year 2016 in these cities.