dashboard code.Rmd

---
title: "<Ваше название>"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
---

```{r setup, include=FALSE}
library(flexdashboard)

# загрузка данных, предобработка 
```

Column {data-width=500}
-----------------------------------------------------------------------

### **График аэропортов, в которых оценка чистоты лаундж-зон превышает оценку чистоты самого аэропорта**

```{r}
# самый важный график или таблица

library(data.table)
library(lubridate)
library(dplyr)
library(ggplot2)
library(R3PO)
library(stringr)
airport = get_hw1_airport_df()
lounge = get_hw1_lounge_df()


airport = data.frame(name = airport$airport_name, ratin = airport$terminal_cleanliness_rating)
airport = na.omit(airport)

airport = airport %>% group_by(name) %>% summarise(A_rate = mean(ratin))
airport = na.omit(airport)


lounge_airport = str_replace_all(lounge$airport,' ', '-')
lounge = data.frame(name = str_to_lower(lounge_airport), ratin = lounge$cleanliness_rating, lounge_name = lounge$lounge_name)
lounge = na.omit(lounge)

lounge = lounge %>% group_by(name, lounge_name) %>% summarise(L_rate = mean(ratin))


united_dataset = left_join(lounge, airport, by = 'name')


a = case_when(
        united_dataset$L_rate > united_dataset$A_rate ~ 'YES',
        TRUE ~ 'NO'
)


united_dataset$L_more_than_R = a
united_dataset = united_dataset %>% filter(L_more_than_R == 'YES')


k = str_to_title(united_dataset$lounge_name)
k = unique(k)

a = data.table('Список лаудж-зон' = k)


united_dataset1 = data.frame(name = united_dataset$name, L_rate = united_dataset$L_rate, A_rate = united_dataset$A_rate)

b = case_when(
        united_dataset1$L_rate > united_dataset1$A_rate ~ 'YES',
        TRUE ~ 'NO'
)


united_dataset1$L_more_than_R = b
united_dataset1 = united_dataset1 %>% filter(L_more_than_R == 'YES')

frequency_of_a_name = str_count(united_dataset1$name)

united_dataset1 = united_dataset1 %>% mutate(num = frequency_of_a_name) %>% group_by(name) %>% summarise(frequency_of_a_name = num)

united_dataset1 <- united_dataset1[!duplicated(united_dataset1$name),]

united_dataset1 = united_dataset1 %>% filter(frequency_of_a_name >= 23)


name = str_to_title(united_dataset1$name)
name = str_replace_all(name, '-', ' ')
final = data.frame('Название_аэропорта' = name, 'Количество_отзывов' = united_dataset1$frequency_of_a_name) 

final = arrange(final, -Количество_отзывов)
final = data.table(final)


ggplot(data = final) + geom_bar(aes(x=reorder(Название_аэропорта, -Количество_отзывов), y = Количество_отзывов, width = 0.7), , fill = 'cornflowerblue', col = 'black', stat = 'identity') + xlab("") + ylab('Количество таких оценок') + theme_light() + theme(axis.text.x = element_text(angle = 65, hjust = 1, size=7)) + scale_x_discrete(labels = c('Bangkok Suvarnabhumi', 'Sao Paulo Guarulhos', 'Amsterdam Schiphol', 'Atlanta Hartsfield', 'Brussels Zaventem', 'Klia Kuala Lumpur', 'Washington Dulles', 'Amman Queen Alia', 'Istanbul Ataturk', 'London Heathrow', 'Los Angeles Lax', 'Shanghai Pudong', 'Toronto Pearson')) + theme(axis.text.x = element_text(size = 8)) + theme(legend.position="none") + theme(axis.title.y = element_text(size=8)) + xlab('Название аэропорта') + theme(axis.title.x = element_text(size=8))
```

Column {data-width=500, data-height=50}
-----------------------------------------------------------------------

### Общее количество лаундж-зон в датафрейме

```{r}

number_all = str_count(unique(lounge$lounge_name))
lll = length(number_all)

valueBox(lll, icon = 'fa-hand-peace')
```

### **Лаундж-зоны, рейтинг чистоты которых выше рейтинга чистоты аэропортов, в которых они находятся**

```{r}
# график или таблица


DT::datatable(a, options = list(
bPaginate = TRUE
))

```

### Количество лаундж-зон, подходящих по критериям

```{r}
length = length(str_count(k))

valueBox(length, icon = 'fa-broom')
```