---
title: "Birds Collision With Planes"
output:
flexdashboard::flex_dashboard:
theme: flatly
orientation: rows
source_code: embed
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(fig.showtext=TRUE, fig.retina = 1,
dpi = 300)
library(flexdashboard)
library(echarts4r)
library(tidyverse)
library(ggchicklet)
library(lubridate)
library(showtext)
library(ggsci)
library(scico)
font_add_google("IBM Plex Serif","IBM Plex Serif")
bird_impacts <- readr::read_csv(here::here("data/wildlife_impacts.csv"))
birds <- bird_impacts %>%
mutate(incident_month = month(ymd(incident_date),label = TRUE))
```
Sidebar {.sidebar}
===========================================================================
This data collected from the [FAA (Federal Aviation Administration) Wildlife Strike Database](https://wildlife.faa.gov/) which contains records of reported wildlife (Birds) strikes since 1990. Strike reporting is voluntary.
Therefore, this database only represents the information we have received from airlines, airports, pilots, and other sources like Report on wildlife impacts. And this data is just for the big 4: American Airlines, Delta, Southwest, and United as they account for [almost 70% of passengers](https://en.wikipedia.org/wiki/List_of_largest_airlines_in_North_America) in the USA but there are many many more available airlines.
Timeline {data-icon="fa-chart-line"}
======================================================================
Row {.tabset .tabset-fade}
-----------------------------------------------------------------------
### Year-Month stat
```{r page01-tile-yearMonth, fig.width=10, fig.height=5.5}
showtext_auto()
birds %>%
count(incident_year, incident_month = fct_rev(incident_month)) %>%
ggplot(aes(x = factor(incident_year),y = incident_month))+
geom_tile(aes(fill = n))+
scale_fill_gsea()+
labs(x = NULL, y = NULL,
subtitle = "Bird's collision with airplanes from 1990 to 2018",
title = "Reported Wildlife collision With The Big Four USA Airlines")+
guides(fill = guide_colorbar(title = "Number of Strikes", title.position = "top",
barheight = unit(1,"lines"),
barwidth = unit(20,"lines"),
title.theme = element_text(angle = 0,
family = "IBM Plex Serif"),
label.theme = element_text(angle = 0,
family = "IBM Plex Serif")
))+
theme_minimal()+
theme(
text = element_text(family = "IBM Plex Serif"),
legend.position = "bottom",
legend.direction = "horizontal",
axis.ticks = element_blank(),
axis.text = element_text(color = "grey20", face = "plain"),
legend.text = element_text(color = "grey20", face = "bold",
angle = 90, vjust = 0.5, hjust = 0.5),
legend.title = element_text(angle = 90, hjust = 0.5, vjust = 0.5),
plot.subtitle = element_text(size = 12, color = "grey20"),
plot.title = element_text(size = 15, face = "bold"),
)
```
### Collision-Timeline
```{r page01-line-total, fig.width=9.5, fig.height=5.5}
e_common(
font_family = "IBM Plex Serif"
)
year_total <- birds %>%
count(incident_year,name = "Collision") %>%
mutate(
yr = as.character(as.integer(incident_year))
)
year_total %>%
e_charts(x = yr) %>%
e_line(Collision) %>%
e_title("Year-wise Total Bird Strike incidents From 1990 to 2018") %>%
e_theme("infographic") %>%
e_legend(right = 0) %>%
e_x_axis(axisTick = list(show=FALSE)) %>%
e_tooltip(
axisPointer = list(
type = "cross"
)
)
```
### Collision-Timeline for each Airlines
```{r page01-line-operator, fig.width=9.5, fig.height=5.5}
year_op <- birds %>%
count(operator, incident_year) %>%
mutate(
yr = as.character(as.integer(incident_year))
)
year_op %>%
group_by(operator) %>%
e_charts(x = yr) %>%
e_line(serie = n) %>%
e_title("Year-wise Bird Strike incidents for Each Airlines") %>%
e_theme("infographic") %>%
e_legend(right = 0) %>%
e_x_axis(axisTick = list(show=FALSE)) %>%
e_tooltip(trigger = "axis")
```
Stats {data-icon="fas fa-chart-bar" data-orientation=columns}
=======================================================================
Column
-----------------------------------------------------------------------
### Total Number of Bird Strike Incidents
```{r page02-bar-total, fig.width=6, fig.height=4}
showtext_auto()
birds %>%
count(operator)%>% drop_na() %>%
mutate(operator = fct_reorder(operator,n)) %>%
ggplot(aes(operator,n, fill = operator))+
geom_chicklet()+
scale_fill_scico_d(palette = "devon", direction = -1,begin=0.2, end = 0.5)+
scale_x_discrete(labels = scales::label_wrap(10))+
theme_minimal()+
coord_flip()+
theme(legend.position = "none",
text = element_text(family = "IBM Plex Serif")
)+
labs(x = NULL, y = NULL,
title = "Which Airlines Faced Most Birds Collision"
)
```
Column
-----------------------------------------------------------------------
### Proportion of Damage-Level Specific incidents
```{r page02-bar-operator, fig.width=6, fig.height=4}
showtext_auto()
birds %>%
count(operator,damage) %>% drop_na() %>% filter(!damage == "N") %>%
# mutate(damage = factor(damage, levels = c("M", "M"))) %>%
ggplot(aes(operator, n, fill = fct_rev(damage)))+
geom_chicklet(position = "fill")+
scale_fill_manual(values = c("S" = "#800503", "M" = "#010c5e", "M?" = "#3d3737"),
labels = c("M" = "Minor", "M?" = "Uncertain",
"S" = "Substantial"),
name = "Damage level",)+
guides(fill = guide_legend(title.position = "top",
label.hjust = 0.5,
keywidth=unit(3.5, "lines"),
reverse = TRUE))+
scale_x_discrete(labels = scales::label_wrap(10))+
coord_flip()+
labs(y = "Proportion", x = NULL,
title = str_wrap("Which Airlines Faced Most Collision incidents that were Substantially-Damaged", width = 50))+
theme_minimal()+
theme(
text = element_text(family = "IBM Plex Serif"),
legend.position = "bottom",
legend.spacing.x = unit(0.9,"lines"))
```
More Info {data-icon="fa-th" data-orientation=rows}
=========================================================
Row{.tabset .tabset-fade}
-----------------------------------------------------------------------
### Phase of Flight
```{r page03-tile-phaseFlight}
df <- birds %>%
mutate(phase_of_flt = case_when(
phase_of_flt %in% c("TAKE-OFF RUN","Take-off run","take-off run","Take-off Run")~"Take-off Run",
phase_of_flt %in% c("Landing Roll","landing roll","LANDING ROLL","Landing roll")~"Landing Roll",
phase_of_flt %in% c("DEPARTURE")~"Departure",
phase_of_flt %in% c("CLIMB","climb")~"Climb",
phase_of_flt %in% c("ARRIVAL")~"Arrival",
phase_of_flt %in% c("approach","APPROACH")~"Approach",
TRUE~phase_of_flt)
) %>%
filter(!phase_of_flt %in% c("Unknown",NA) )
showtext_auto()
df %>%
count(operator, phase_of_flt) %>%
mutate(operator = str_to_title(operator),
operator = str_replace(operator," ","\n")) %>%
ggplot(aes(operator, phase_of_flt))+
geom_raster(aes(fill = n), interpolate = TRUE)+
scale_fill_gradient2(low = "#04bfd4", high = "#FF3200",mid = "#faec82", midpoint = 4000)+
guides(fill = guide_colorbar(title = "Number of Strikes", title.position = "top",
barheight = unit(1,"lines"),
barwidth = unit(15, "lines"),
label.position = "bottom" ),
title.theme = element_text(angle = 0,
family = "IBM Plex Serif"),
label.theme = element_text(angle = 0,
family = "IBM Plex Serif")
)+
theme_minimal()+
labs(y = NULL, x = NULL,
title = str_wrap("In Which Flight-state planes are most likely to Collide with birds ?!", width = 50))+
theme(legend.position = "bottom",
legend.direction = "horizontal",
text = element_text(family = "IBM Plex Serif")
)
```
### Sky and Day-Time
```{r page03-sky-daytime}
con <- birds %>%
count(operator, time_of_day, sky) %>% filter(!is.na(time_of_day) & !is.na(sky))
showtext_auto()
con %>% ggplot(aes(x = time_of_day,y = sky, fill = n))+
geom_tile()+
guides(fill = guide_colorbar(title = "Number of Strikes", title.position = "top",
barheight = unit(1,"lines"),
barwidth = unit(15,"lines"),
title.theme = element_text(angle = 0,
family = "IBM Plex Serif"),
label.theme = element_text(angle = 0,
family = "IBM Plex Serif")
))+
labs(
x=NULL, y = NULL,
title=str_wrap("In which Sky Condition and when of the Day-time Planes Collided with Birds Mostly ?!", width = 50)
)+
ggthemes::scale_fill_gradient_tableau(palette = "Classic Red", )+
facet_wrap(~operator)+
theme_minimal() +
theme(
text = element_text(family = "IBM Plex Serif"),
legend.position = "bottom",
legend.direction = "horizontal"
)
```
### Speed and Height
```{r page03-speed-height-scatter}
pts <- birds %>%
drop_na(speed, height) %>%
select(height, speed, operator)
pts %>%
group_by(operator) %>%
e_charts(height) %>%
e_scatter(speed, bind = operator,
scale=NULL, symbol_size = 7) %>%
e_tooltip(
formatter = htmlwidgets::JS("
function(params){
return('' + params.name +
'
Height: ' + params.value[0] +
'
Speed: ' + params.value[1])
}
")
) %>%
e_axis_labels(
x = "Height at Impact",
y = "Speed at Impact"
) %>%
e_title("Most of the Collision happened at low height ??") %>%
e_theme("infographic") %>%
e_legend(right = 0, bottom = 0)
```
