---
title: "dashboards"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
    source: embed
---

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

library(p8105.datasets)
library(tidyverse)
library(ggplot2)
library(plotly)

options(scipen = 999)
```


```{r load data}
data(rest_inspec)

rest_inspec = 
  rest_inspec %>% 
  mutate(
    camis = format(camis, scientific = F),
    camis = as.integer(camis)
  )
```


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

### Distribution for the 7 common food in New York

```{r boxplot}

# # boxplot for the 5 boros' pizzas
# plot_box1 =
#   rest_inspec %>% 
#   filter(cuisine_description == c("Pizza","Mexican","Chinese")) %>% 
#   mutate(
#     boro = fct_reorder(boro, score)
#   ) %>% 
#   plot_ly(
#     y = ~ score,
#     color = ~boro,
#     type = "box"
#   )

# boxplot for the 7 common cuisines
rest_inspec %>% 
  filter(
    inspection_date <= "2017/01/01",
    cuisine_description == c("Bakery","Donuts","Pizza","Hotdogs","Mexican","Chinese","Hamburgers")
  ) %>% 
  mutate(
    cuisine_description = fct_reorder(cuisine_description, score)
  ) %>% 
  plot_ly(
    y = ~ score,
    color = ~cuisine_description,
    type = "box",
    colors = "viridis"
  )

```






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

### Top 15 Cuisines outside Manhattan

```{r barchart}

# top 15 cuisines at boros outside manhattan
rest_inspec %>% 
  filter(boro == c("BRONX","STATEN ISLAND","BROOKLYN", "QUEENS")) %>% 
  count(cuisine_description)%>% 
  top_n(n = 15) %>% 
  mutate(
    cuisine_description = fct_reorder(cuisine_description, n)
  ) %>%
  plot_ly(
    x = ~cuisine_description,
    y = ~n,
    color = ~cuisine_description,
    type = "bar",
    colors = "viridis"
  ) %>% 
  hide_legend()

```


### Scores by Inspection Date

```{r scatter plot}

# for 2013 - 2016, scatter plot on date, score, and grades for all pizzas

rest_inspec %>% 
  filter(cuisine_description == "Pizza") %>% 
  filter(inspection_date <= "2017/01/01") %>% 
  mutate(
    text_label = str_c("borogh: ", boro)
  ) %>% 
  plot_ly(
    x = ~inspection_date,
    y = ~score,
    color = ~grade,
    type = "scatter",
    text = ~text_label,
    colors = "viridis"
  )

```