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Task 3
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library(dplyr) | |
library(shiny) | |
library(nycflights13) | |
library(ggplot2) | |
library(ggthemes) | |
options(scipen = 999) | |
flights <- flights | |
airlines <- airlines | |
# łączenie dwóch dataframe'ów | |
modFlights <- flights %>% | |
inner_join(airlines, by = 'carrier') | |
# wybór siedmu linii lotniczych | |
chosenCarrier <- modFlights %>% count(name) %>% | |
arrange(desc(n)) %>% | |
head(7) | |
# filtrowanie danych | |
modFlights <- modFlights %>% | |
filter(!is.na(dep_delay), name %in% chosenCarrier$name) |
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shinyServer(function(input, output, session) { | |
output$ddelay_plot <- renderPlot({ | |
aggDelayFlights <- modFlights %>% | |
group_by(hour) %>% | |
summarise(delayed_flight_perc = sum(dep_delay > 0) / n()) | |
ggplot(aggDelayFlights, aes(hour, delayed_flight_perc)) + | |
geom_col(position = 'dodge') + | |
theme_hc(base_size = 18) + | |
scale_fill_hc() + | |
xlab("Departure hour") + | |
ylab("Percentage of delayed flights") + | |
scale_y_continuous(labels = scales::percent) + | |
scale_x_continuous(limits = c(0,24), breaks = seq(0, 24, 2)) + | |
guides(fill=guide_legend(title="")) | |
}) | |
output$table <- renderTable({ | |
modFlights %>% | |
group_by(hour) %>% | |
summarise(delayed_flight_perc = sum(dep_delay > 0) / n()) %>% | |
mutate( | |
delayed_flight_perc = scales::percent(delayed_flight_perc) | |
) | |
}) | |
}) |
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fluidPage( | |
titlePanel(title = "Introduction to Shiny"), | |
sidebarPanel( | |
selectInput("carrierName", | |
label = "Select carrier:", | |
choices = sort(chosenCarrier$name), | |
selected = sort(chosenCarrier$name)[1], | |
multiple = T), | |
sliderInput('delayFlightRange', | |
label = "Choose minutes range of delay flights:", | |
min = 0, max = 1000, value = c(0, 1000), step = 5), | |
numericInput("distance_val", label = "Flight distance longer than (miles):", value = 500) | |
), | |
mainPanel( | |
tabsetPanel( | |
tabPanel("Delay over day", | |
plotOutput('ddelay_plot') | |
), | |
tabPanel("Explore data", | |
tableOutput("table") | |
) | |
) | |
) | |
) |
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