abcd

knitr::opts_chunk$set(echo = FALSE , message = FALSE, warning = FALSE)

Click the Code, Plot and References tabs to read about the issues and how they were fixed along with references

Flying is said to be the safest form of transport, certainly in terms of fatalities by distance travelled. According to the Civil Aviation Authority, the fatality rate per billion kilometres travelled by plan is 0.003 compared to 0.27 by rail and 2.57 by car (Allianz Global Corporate & Specialty, 2022). In fact, the aviation sector has experienced robust growth since the dawn of this era, the past 60 years have seen an ongoing decline in fatal accidents, underpinned by a continuous improvement in safety. (Dobie, 2014, p. 4). Perhaps there are other factors such as world region, advances or iterations in technology or number of travellers which may also have an impact on air travel. This publication aims to reflect on the history of flight disasters to gain some future insights.

Code

knitr::opts_chunk$set(echo = FALSE , message = FALSE, warning = FALSE)
library(flexdashboard)
library(tidyverse)

## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --

## v ggplot2 3.3.5     v purrr   0.3.4
## v tibble  3.1.6     v dplyr   1.0.8
## v tidyr   1.2.0     v stringr 1.4.0
## v readr   2.1.2     v forcats 0.5.1

## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()

library(gganimate)
library(janitor)

## 
## Attaching package: 'janitor'

## The following objects are masked from 'package:stats':
## 
##     chisq.test, fisher.test

library(plotly)

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

library(viridis)

## Loading required package: viridisLite

library(reshape2)

## 
## Attaching package: 'reshape2'

## The following object is masked from 'package:tidyr':
## 
##     smiths

data <- read.csv("Excel SS Airline project V2.csv")
data <- clean_names(data)

#Removing region that has no name in it  and other region
data <- data[-which(data$region == "" | data$region == "Other"), ]

data$fatalities <- as.numeric(as.character(data$fatalities))

## Warning: NAs introduced by coercion

#When we convert to numeric we see there's 1 missing value as Vietnam has ? in data so we remove that

data <- na.omit(data)

agg = aggregate(fatalities~region+year, data, mean)


data2 <- agg %>%
 group_by(year) %>%
 # Rank the fatalities by year
 mutate(rank = rank(-fatalities),
        fatalities_rel = fatalities/fatalities[rank==1],
        fatalities_lbl = paste0(" ",round(fatalities,2))) %>%
 group_by(region) %>% 
 ungroup()

p_static <- ggplot(data2, aes(rank, group = region,
                               fill = as.factor(region), color = as.factor(region))) +
 geom_tile(aes(y = fatalities/2,
               height = fatalities,
               width = 0.9), alpha = 0.8, color = NA) +
 geom_text(aes(y = 0, label = paste(region, " ")), vjust = 0.2, hjust = 1, size = 9) +
 geom_text(aes(y = fatalities, label = fatalities_lbl, hjust = 0), size = 9) +
 coord_flip(clip = "off", expand = FALSE) +
 scale_y_continuous(labels = scales::comma) +
 scale_x_reverse() +
 guides(color = FALSE, fill = FALSE) +
 theme(axis.line = element_blank(),
       axis.text.x = element_blank(),
       axis.text.y = element_blank(),
       axis.ticks = element_blank(),
       axis.title.x = element_blank(),
       axis.title.y = element_blank(),
       legend.position = "none",
       panel.background = element_blank(),
       panel.border = element_blank(),
       panel.grid.major = element_blank(),
       panel.grid.minor = element_blank(),
       panel.grid.major.x = element_line(size = 0.1, color = "grey"),
       panel.grid.minor.x = element_line(size = 0.1, color = "grey"),
       plot.title = element_text(size = 30),
       plot.subtitle = element_text(size=25, face = "italic", color = "grey",  hjust = 0.5, vjust = -1),
       plot.background = element_blank(),
       plot.margin = margin(4, 4, 4, 4, "cm"))

## Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
## "none")` instead.

anim <- p_static + 
 transition_states(year, transition_length = 4, state_length = 1) +
 view_follow(fixed_x = TRUE)  +
 labs(title = 'Fatalities per year : {closest_state}') + ggtitle(" Animated bar chart of fatalities per region")

world_flight <- read.csv("world-air-passenger-traffic-evolution-1980-2020.csv",sep = ";")
world_flight_long <- melt(world_flight, id="Year")  # convert to long format

world_flight_long$Year <- as.numeric(world_flight_long$Year)

colnames(world_flight_long)[2] <- "Flights"
colnames(world_flight_long)[3] <- "Total_passengers_in_Billion"


p <- ggplot(data=world_flight_long,
       aes(x=Year, y=Total_passengers_in_Billion, colour=Flights)) +
    geom_line() + ggtitle("Line chart of passengers 1980- 2020")

p1 = ggplot(world_flight_long, aes(Year, Total_passengers_in_Billion, colour = Flights)) +
    geom_line() +
    transition_reveal(Year) +
    labs(title = 'Year: {frame_along}') + ggtitle("Animated Line chart of passengers 1980- 2020")

Plot

References