---
title: "Airline Reliability Dashboard: New York Flights 2013"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
---

```{r setup, include=FALSE}
library(flexdashboard)
library(ggplot2)
library(dplyr)
library(plotly)
library(nycflights13)
library(forcats)
library(tidyr)

flights_new <- flights
flights_new$dep_del_status <- ifelse(flights_new$dep_delay>=15, 1, 0)
flights_new$arr_del_status <- ifelse(flights_new$arr_delay>=15, 1, 0)
```

Column {data-width=650}
-----------------------------------------------------------------------

### Proportion of Flights Delayed (Departure and Arrival) by Carrier

```{r}
flights_delay <- flights_new %>% group_by(carrier) %>% 
  summarise(dep_del = sum(dep_del_status,na.rm = TRUE),
            arr_del = sum(arr_del_status,na.rm = TRUE),
            n = n(),
            prop_dep_del = round(dep_del/n,2),
            prop_arr_del = round(arr_del/n,2)
  )

flights_delay$carrier <- fct_reorder(flights_delay$carrier, flights_delay$prop_dep_del)

flights_delay_long <- flights_delay %>% gather(key = "Delay", value = "prop", 5:6)

flights_delay_long$Delay <- factor(flights_delay_long$Delay,
                                   levels = c("prop_dep_del","prop_arr_del"),
                                   labels = c("Departure","Arrival"),
                                   order = TRUE)

p1 <- ggplot(flights_delay_long, aes(x = carrier, y = prop)) + 
  geom_bar(stat = "identity", fill = "steelblue") + facet_grid(.~Delay) +
  labs(x = "Carrier Code", y = "Proportion on time (+/- 15 mins of schedule)") +
  theme_grey()
ggplotly(p1)
```

Column {data-width=350}
-----------------------------------------------------------------------

### Proportion of Flights Delayed (Departure) by Carrier by Month

```{r}
flights_delay_month <- flights_new %>% group_by(carrier,month) %>% 
  summarise(dep_del = sum(dep_del_status,na.rm = TRUE),
            arr_del = sum(arr_del_status,na.rm = TRUE),
            n = n(),
            prop_dep_del = round(dep_del/n,2),
            prop_arr_del = round(arr_del/n,2)
  )

flights_delay_month$carrier <- fct_reorder(flights_delay_month$carrier, flights_delay_month$prop_dep_del)

p2 <- ggplot(flights_delay_month, aes(x = carrier, y = as.factor(month))) + 
  geom_tile(aes(fill = prop_dep_del)) + 
  scale_fill_gradient(name = "Proportion", low = "white",high = "steelblue") +
  labs(x = "Carrier", y = "Month")
ggplotly(p2)
```

### Proportion of Flights Delayed (Arrival) by Carrier by Month

```{r}
flights_delay_month <- flights_new %>% group_by(carrier,month) %>% 
  summarise(dep_del = sum(dep_del_status,na.rm = TRUE),
            arr_del = sum(arr_del_status,na.rm = TRUE),
            n = n(),
            prop_dep_del = round(dep_del/n,2),
            prop_arr_del = round(arr_del/n,2)
  )

flights_delay_month$carrier <- fct_reorder(flights_delay_month$carrier, flights_delay_month$prop_dep_del)

p3 <- ggplot(flights_delay_month, aes(x = carrier, y = as.factor(month))) + 
  geom_tile(aes(fill = prop_arr_del)) + 
  scale_fill_gradient(name = "Proportion", low = "white",high = "steelblue") +
  labs(x = "Carrier", y = "Month")

ggplotly(p3)
```