---
title: "Dashboard"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
    source_code: embed
---

```{r setup, include=FALSE}
library(flexdashboard)
library(tidyverse)
library(p8105.datasets)

library(plotly)
data("instacart")
```

```{r}
instacart = 
  instacart %>% 
  mutate(
    day = order_dow +1,
    day_of_week = lubridate::wday(day, label = TRUE, locale = "English_United States")
    ) %>%
  select(order_id, product_id, order_number, day_of_week, order_hour_of_day, product_name, aisle, department) %>% 
  drop_na() 
```


Column {data-width=600}
-----------------------------------------------------------------------

### Chart A

```{r}
instacart %>%
  count(order_hour_of_day, department) %>%
  plot_ly(
    x = ~order_hour_of_day, y = ~n, type = "scatter", mode = "lines", color = ~department, colors = "viridis"
  )%>% 
  layout(title = "Number of Orders during the day")
```

Column {data-width=400}
-----------------------------------------------------------------------

### Chart B

```{r}
instacart %>% 
  sample_n(4000) %>% 
  plot_ly(
    y = ~order_number, color = ~day_of_week, type = "box", colors = "viridis"
  )%>% 
  layout(title = "Order number distribution during the week")
```

### Chart C

```{r}
instacart %>% 
  group_by(aisle) %>% 
  summarise(num_order = n()) %>% 
  filter(num_order > 20000) %>% 
  mutate(aisle = reorder(aisle, num_order)) %>% 
  plot_ly(
    x = ~aisle, y = ~num_order, color = ~aisle, type = "bar", colors = "viridis"
  ) %>% 
  layout(title = "Number of orders of different aisles")
```