---
title: "Corona19 DashBoard"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
    social: menu
    theme: cosmo
    storyboard: true
    thumbnails: true
    source: embed
    logo: Gareth_Frank_Bale_circle.png
    favicon:  Gareth_Frank_Bale_circle.png
    navbar:
      - { icon: "fa-facebook-f", href: "https://www.facebook.com/shjj08", align: right }
      - { icon: "fa-github", href: "https://github.com/Unfinishedgod", align: right }   
---







        



```{r setup, include=FALSE}
library(flexdashboard)
library(readr)
library(tidyverse)
library(leaflet)
library(DT)
library(httr)
library(jsonlite)
library(plotly)
library(glue)
```


```{r}
corona_haspital <- read_csv("corona_haspital.csv",locale=locale('ko',encoding='euc-kr'))

corona_clinic <- read_csv("corona_clinic.csv",locale=locale('ko',encoding='euc-kr'))


# 지리정보 API를 사용한 위경도 추출
Lat_lon_fun <- function(addr) {
  data_list <-
    GET(url = 'https://dapi.kakao.com/v2/local/search/address.json',
        query = list(query = addr),
        add_headers(Authorization = paste0("KakaoAK ", "2ecacbafd523802f293b245103346b06"))) %>%
    content(as = 'text') %>%
    fromJSON()


  lon_lat_df <- tibble(주소 = addr,
                       long = as.numeric(data_list$documents$x),
                       lat = as.numeric(data_list$documents$y))

  return(lon_lat_df)
}




# 병원 ------------------------

hos_location_list <- corona_haspital$주소


not_hos_list <- c(2,30,39,102,168,227,280)

hos_location_long_lat <- map_dfr(hos_location_list[-not_hos_list], function(x) {
  Lat_lon_fun(x)
})

hos_info <- corona_haspital %>%
  left_join(hos_location_long_lat)  %>%
  # select(시도, 시군구, 기관명, 주소, 전화번호, long, lat) %>%
  rename(유형 = 신청유형)

# 진료소 ------------------------
cli_location_list <- corona_clinic$주소

not_cli_list <- c(128,131,158, 321,419,484, 538,540, 612)

cli_location_long_lat <- map_dfr(cli_location_list[-not_cli_list], function(x) {
  Lat_lon_fun(x)
})


cli_info <- corona_clinic %>%
  left_join(cli_location_long_lat) %>%
  # select(시도, 시군구, 의료기관명, 주소, `대표 전화번호`, long, lat) %>%
  rename(전화번호 = `대표 전화번호`, 기관명 = 의료기관명, 유형 = `검체채취 가능여부`)

cli_info$유형 <- case_when(
  cli_info$유형 == "Y" ~ "검체체취 가능",
  TRUE ~ "검체체취 불가"
)


hos_cli_info <- hos_info %>%
  mutate(구분 = "국민안심병원") %>%
  bind_rows((cli_info %>%
               mutate(구분 = "선별진료소"))) %>%
  drop_na(long) %>%
  replace_na(list(운영가능일자 = "운영가능")) %>%
  select(구분, 시도, 시군구, 기관명, 주소, 유형, 전화번호, 운영가능일자, long, lat)

# write.csv(hos_cli_info, file = "hos_cli_info.csv")
# hos_cli_info <- read_csv("hos_cli_info.csv")

# hos_cli_info

hos_cli_info_seoul <- hos_cli_info %>% 
  filter(시도 == "서울")

hos_cli_info_daegu <- hos_cli_info %>% 
  filter(시도 == "대구")
```


전국 {data-navmenu="보건복지부 안심병원과 진료소"}
=======================================================================

columns 1 {data-width=40%}
-----------------------------------------------------------------------

### 전국 안심병원&진료소 위치지도

```{r}
# 보건복지부 안심병원&진료소
hos_cli_leaflet <- hos_cli_info %>% 
  mutate(ratingcol = case_when(
    구분 == "국민안심병원" ~ "green",
    TRUE ~ "blue"
  ))

leaflet() %>% 
  addTiles() %>% 
  addCircleMarkers(hos_cli_leaflet$long, 
                   hos_cli_leaflet$lat, 
                   color = hos_cli_leaflet$ratingcol, 
                   radius = 8, 
                   fill = T,
                   fillOpacity = 0.5,
                   opacity = 0.1,
                   popup = paste0(hos_cli_leaflet$기관명, " \n(", hos_cli_leaflet$전화번호,")")) %>%
  addLegend("topright", 
            colors = c("green","blue"),
            labels = c("보건복지부 국민안심병원",
                       "보건복지부 선별진료소"), 
            opacity = 1)
```

columns 2 { data-width=60%, data-height=200}
-------------------------------------

### 시도별 안심병원 & 진료소 그래프 {data-height=40%}

```{r}
theme_set(theme_classic())

# hos_cli_info$구분 <- as.factor(hos_cli_info$구분)
# 
# p <- hos_cli_info %>% 
#   group_by(구분,시도) %>% 
#   summarise(개수 = n()) %>% 
#   arrange(구분, 시도) %>% 
#   ggplot(aes(x = 시도, y = 개수, fill = 구분)) +
#   geom_col(position="dodge") +
#   scale_fill_manual(values = c("green3", "blue3")) +
#   labs(title = "지역별 병원, 진료소 파악", x = "", y = "") +
#   theme(legend.position = "bottom")
# 
# 
# ggplotly(p)

df_plotly <- hos_cli_info %>% 
  group_by(구분,시도) %>% 
  summarise(개수 = n()) %>% 
  arrange(구분, 시도) %>% 
  spread(key = "구분", value = "개수") %>% 
  replace_na(list(국민안심병원 = 0)) 

m <- list(
  l = 50,
  r = 50,
  b = 100,
  t = 100,
  pad = 4
)

df_plotly %>% 
  plot_ly(
    x = ~시도,
    y = ~국민안심병원,
    type = "bar",
    name = "보건복지부 국민안심병원",
    textposition = 'auto',
    marker = list(color = 'green')
  ) %>% 
  add_trace(y = ~선별진료소,
            name = "보건복지부 선별진료소",
            textposition = 'auto',
            marker = list(color = 'blue')) %>% 
  layout(legend = list(orientation = "v",   # show entries horizontally
                       xanchor = "center",  # use center of legend as anchor
                       x = 0.9,
                       y = 1.09,
                       autosize = F, width = 200, height = 100, margin = m)) 
```

### 데이터(전국) {data-height=60%}

```{r}
hos_cli_info %>% 
  select(구분, 시도, 시군구, 기관명, 주소, 유형, 전화번호, 운영가능일자) %>% 
  datatable(rownames  = FALSE)
```

서울 {data-navmenu="보건복지부 안심병원과 진료소"}
=======================================================================

columns 1 {data-width=40%}
-----------------------------------------------------------------------

### 서울 - 안심병원&진료소 위치지도

```{r}
# 보건복지부 안심병원&진료소
hos_cli_leaflet <- hos_cli_info_seoul %>% 
  mutate(ratingcol = case_when(
    구분 == "국민안심병원" ~ "green",
    TRUE ~ "blue"
  ))

leaflet() %>% 
  addTiles() %>% 
  addCircleMarkers(hos_cli_leaflet$long, 
                   hos_cli_leaflet$lat, 
                   color = hos_cli_leaflet$ratingcol, 
                   radius = 8, 
                   fill = T,
                   fillOpacity = 0.5,
                   opacity = 0.1,
                   popup = paste0(hos_cli_leaflet$기관명, " \n(", hos_cli_leaflet$전화번호,")")) %>%
  addLegend("topright", 
            colors = c("green","blue"),
            labels = c("보건복지부 국민안심병원",
                       "보건복지부 선별진료소"), 
            opacity = 1)
```

columns 2 { data-width=60%, data-height=200}
-------------------------------------

### 서울 - 구별 안심병원 & 진료소 그래프 {data-height=40%}

```{r}
theme_set(theme_classic())

# hos_cli_info$구분 <- as.factor(hos_cli_info$구분)
# 
# p <- hos_cli_info %>% 
#   group_by(구분,시도) %>% 
#   summarise(개수 = n()) %>% 
#   arrange(구분, 시도) %>% 
#   ggplot(aes(x = 시도, y = 개수, fill = 구분)) +
#   geom_col(position="dodge") +
#   scale_fill_manual(values = c("green3", "blue3")) +
#   labs(title = "지역별 병원, 진료소 파악", x = "", y = "") +
#   theme(legend.position = "bottom")
# 
# 
# ggplotly(p)

df_plotly <- hos_cli_info_seoul %>% 
  group_by(구분,시군구) %>% 
  summarise(개수 = n()) %>% 
  arrange(구분, 시군구) %>% 
  spread(key = "구분", value = "개수") %>% 
  replace_na(list(국민안심병원 = 0)) 

m <- list(
  l = 50,
  r = 50,
  b = 100,
  t = 100,
  pad = 4
)

df_plotly %>% 
  plot_ly(
    x = ~시군구,
    y = ~국민안심병원,
    type = "bar",
    name = "보건복지부 국민안심병원",
    textposition = 'auto',
    marker = list(color = 'green')
  ) %>% 
  add_trace(y = ~선별진료소,
            name = "보건복지부 선별진료소",
            textposition = 'auto',
            marker = list(color = 'blue')) %>% 
  layout(legend = list(orientation = "v",   # show entries horizontally
                       xanchor = "center",  # use center of legend as anchor
                       x = 0.9,
                       y = 1.09,
                       autosize = F, width = 200, height = 100, margin = m)) 
```

### 데이터(서울) {data-height=60%}

```{r}
hos_cli_info_seoul %>% 
  select(구분, 시군구, 기관명, 주소, 유형, 전화번호, 운영가능일자) %>% 
  datatable(rownames  = FALSE)
```



대구 {data-navmenu="보건복지부 안심병원과 진료소"}
=======================================================================

columns 1 {data-width=40%}
-----------------------------------------------------------------------

### 대구 - 안심병원&진료소 위치지도

```{r}
# 보건복지부 안심병원&진료소
hos_cli_leaflet <- hos_cli_info_daegu %>% 
  mutate(ratingcol = case_when(
    구분 == "국민안심병원" ~ "green",
    TRUE ~ "blue"
  ))

leaflet() %>% 
  addTiles() %>% 
  addCircleMarkers(hos_cli_leaflet$long, 
                   hos_cli_leaflet$lat, 
                   color = hos_cli_leaflet$ratingcol, 
                   radius = 8, 
                   fill = T,
                   fillOpacity = 0.5,
                   opacity = 0.1,
                   popup = paste0(hos_cli_leaflet$기관명, " \n(", hos_cli_leaflet$전화번호,")")) %>%
  addLegend("topright", 
            colors = c("green","blue"),
            labels = c("보건복지부 국민안심병원",
                       "보건복지부 선별진료소"), 
            opacity = 1)
```

columns 2 { data-width=60%, data-height=200}
-------------------------------------

### 대구 - 구별 안심병원 & 진료소 그래프 {data-height=40%}

```{r}
theme_set(theme_classic())

# hos_cli_info$구분 <- as.factor(hos_cli_info$구분)
# 
# p <- hos_cli_info %>% 
#   group_by(구분,시도) %>% 
#   summarise(개수 = n()) %>% 
#   arrange(구분, 시도) %>% 
#   ggplot(aes(x = 시도, y = 개수, fill = 구분)) +
#   geom_col(position="dodge") +
#   scale_fill_manual(values = c("green3", "blue3")) +
#   labs(title = "지역별 병원, 진료소 파악", x = "", y = "") +
#   theme(legend.position = "bottom")
# 
# 
# ggplotly(p)

df_plotly <- hos_cli_info_daegu %>% 
  group_by(구분,시군구) %>% 
  summarise(개수 = n()) %>% 
  arrange(구분, 시군구) %>% 
  spread(key = "구분", value = "개수") %>% 
  replace_na(list(국민안심병원 = 0)) 

m <- list(
  l = 50,
  r = 50,
  b = 100,
  t = 100,
  pad = 4
)

df_plotly %>% 
  plot_ly(
    x = ~시군구,
    y = ~국민안심병원,
    type = "bar",
    name = "보건복지부 국민안심병원",
    textposition = 'auto',
    marker = list(color = 'green')
  ) %>% 
  add_trace(y = ~선별진료소,
            name = "보건복지부 선별진료소",
            textposition = 'auto',
            marker = list(color = 'blue')) %>% 
  layout(legend = list(orientation = "v",   # show entries horizontally
                       xanchor = "center",  # use center of legend as anchor
                       x = 0.9,
                       y = 1.09,
                       autosize = F, width = 200, height = 100, margin = m)) 
```

### 데이터(대구) {data-height=60%}

```{r}
hos_cli_info_daegu %>% 
  select(구분, 시군구, 기관명, 주소, 유형, 전화번호, 운영가능일자) %>% 
  datatable(rownames  = FALSE)
```



전국 {data-navmenu="마스크 제공 정보"}
=======================================================================

```{r}
# 마스크 정보 API ------------------------

# 1. 주소/좌표 기준 판매처별 공적 마스크 판매정보 제공 서비스
url_1 <- "https://8oi9s0nnth.apigw.ntruss.com/corona19-masks/v1/stores/json?page=1&perPage=5000"
# 2. 판매처별 공적 마스크 판매처 정보 제공 서비스
url_2 <- "https://8oi9s0nnth.apigw.ntruss.com/corona19-masks/v1/sales/json?page=1&perPage=5000"


file_1 <- fromJSON(url_1)
file_2 <- fromJSON(url_2)

# 1번
df_1 <- file_1$storeInfos %>%
  as_tibble()

# 2번
df_2 <- file_2$sales %>%
  as_tibble()


asdf <- df_1 %>%
  left_join(df_2) %>%
  # replace_na(list(created_at = "정보 없음", remain_stat = "정보없음", stock_at = "정보 없음")) %>%
  drop_na() %>%
  mutate(remain_stat_kr = case_when(
    remain_stat == "plenty" ~ "100개 이상",
    remain_stat == "some" ~ "30개 이상 100개 미만",
    remain_stat == "few" ~ "2개 이상 30개 미만",
    remain_stat == "empty" ~ "1개 이하",
    remain_stat == "break" ~ "2개 이상 30개 미만",
    TRUE ~ "정보 없음"
  ), 구분 = case_when(
    type == "01" ~ "약국",
    type == "02" ~ "우체국",
    TRUE ~ "농협"
  ))



lng_lat_list <- map_chr(1:nrow(asdf), function(x) {
  glue("x={asdf[x,4]}&y={asdf[x,3]}")
})


# 위경도를 사용한 지리정보 추출
addr_fun <- function(lng_lat) {
  data_list <- GET(url = glue("https://dapi.kakao.com/v2/local/geo/coord2regioncode.json?{lng_lat}"),
                   # query = list(query = addr),
                   add_headers(Authorization = paste0("KakaoAK ", "2ecacbafd523802f293b245103346b06"))) %>%
    content(as = 'text') %>%
    fromJSON()

  lng_processing <- lng_lat %>%
    str_split("&")

  raw_lng <- lng_processing[[1]][1] %>%
    str_sub(3,max(nchar(lng_processing[[1]][1]))) %>%
    as.numeric()

  addr_df <- tibble(
    # lng = data_list$documents$x[1],
    lng = raw_lng,
    시도 = data_list$documents$region_1depth_name[1],
    시군구 = data_list$documents$region_2depth_name[1],
    동 = data_list$documents$region_3depth_name[1])

  return(addr_df)
}


addr_info <- map_dfr(lng_lat_list , function(x) {
  addr_fun(x)
})



asdf_2 <- asdf %>%
  left_join(addr_info)
# 
# 
# write.csv(asdf_2, file = "mask_df.csv")

# asdf_2 <- read_csv("mask_df.csv")

asdf <- asdf_2

asdf_seoul <- asdf_2 %>% 
  filter(시도 == "서울특별시")

asdf_daegu <- asdf_2 %>% 
  filter(시도 == "대구광역시")
```


Colunms 1  {data-width=40%}
-----------------------------------------------------------------------

### 전국 마스크 제공 위치지도

```{r}
# 마스크 판매처 leaflet ------------------------

asdf_leaflet <- asdf %>% 
  mutate(ratingcol = case_when(
    type == "01" & remain_stat != "정보없음" ~ "green",
    type == "02" & remain_stat != "정보없음"~ "orange",
    type == "03" & remain_stat != "정보없음"~ "blue",
    TRUE ~ "black"
  ))


leaflet() %>% 
  addTiles() %>% 
  addCircleMarkers(asdf_leaflet$lng, 
                   asdf_leaflet$lat, 
                   color = asdf_leaflet$ratingcol, 
                   radius = 8, 
                   fill = T,
                   fillOpacity = 0.6,
                   opacity = 0.1,
                   popup = paste0(asdf_leaflet$name," (",asdf_leaflet$addr, "(",asdf_leaflet$remain_stat_kr,"))")) %>%
  addLegend("topright", 
            colors = c("green","orange","blue"),
            labels = c("약국",
                       "우체국",
                       "농협"), 
            opacity = 1)
```

Colunms 2 { data-width=60%, data-height=200}
-----------------------------------------------------------------------

### 시도별 마스크 제공 기관 그래프 {data-height=40%}

```{r}
df_plotly <- asdf_2 %>% 
  group_by(구분,시도) %>% 
  summarise(개수 = n()) %>% 
  arrange(구분, 시도) %>% 
  spread(key = "구분", value = "개수") %>% 
  replace_na(list(농협 = 0, 약국 = 0, 우체국=0)) 



df_plotly %>% 
  plot_ly(
    x = ~시도,
    y = ~약국,
    type = "bar",
    name = "약국",
    textposition = 'auto',
    marker = list(color = 'green')
  ) %>% 
  add_trace(y = ~우체국,
            name = "우체국",
            textposition = 'auto',
            marker = list(color = 'orange')) %>% 
  add_trace(y = ~농협,
            name = "농협",
            textposition = 'auto',
            marker = list(color = 'blue')) %>% 
  layout(legend = list(orientation = "v",   # show entries horizontally
                       xanchor = "center",  # use center of legend as anchor
                       x = 0.9,
                       y = 1.09)) 
```

### 데이터(전국) {data-height=60%}

```{r}
asdf_2 %>% 
  select(구분, 시도, 시군구, name,addr, created_at, stock_at, remain_stat_kr) %>% 
  rename(기관명 = name, 주소 = addr, 입고일시 = stock_at, 생성일시 = created_at, 재고정보 = remain_stat_kr) %>% 
  datatable(rownames  = FALSE)
```

서울 {data-navmenu="마스크 제공 정보"}
=======================================================================

columns 1 {data-width=40%}
-----------------------------------------------------------------------

### 서울 마스크 제공 위치지도

```{r}
# 마스크 판매처 leaflet ------------------------
asdf_leaflet <- asdf_seoul %>% 
  mutate(ratingcol = case_when(
    type == "01" & remain_stat != "정보없음" ~ "green",
    type == "02" & remain_stat != "정보없음"~ "orange",
    type == "03" & remain_stat != "정보없음"~ "blue",
    TRUE ~ "black"
  ))


leaflet() %>% 
  addTiles() %>% 
  addCircleMarkers(asdf_leaflet$lng, 
                   asdf_leaflet$lat, 
                   color = asdf_leaflet$ratingcol, 
                   radius = 8, 
                   fill = T,
                   fillOpacity = 0.6,
                   opacity = 0.1,
                   popup = paste0(asdf_leaflet$name," (",asdf_leaflet$addr, "(",asdf_leaflet$remain_stat_kr,"))")) %>%
  addLegend("topright", 
            colors = c("green","orange","blue"),
            labels = c("약국",
                       "우체국",
                       "농협"), 
            opacity = 1)
```

columns 2 { data-width=60%, data-height=200}
-------------------------------------

### 서울 구별 마스크 제공 기관 그래프 {data-height=40%} 

```{r}
df_plotly <- asdf_seoul %>% 
  group_by(구분,시군구) %>% 
  summarise(개수 = n()) %>% 
  arrange(구분, 시군구) %>% 
  spread(key = "구분", value = "개수") %>% 
  replace_na(list(농협 = 0, 약국 = 0, 우체국=0)) 

df_plotly <- df_plotly %>% 
  mutate("농협" = 0,
         "우체국" = 0) 


df_plotly %>% 
  plot_ly(
    x = ~시군구,
    y = ~약국,
    type = "bar",
    name = "약국",
    textposition = 'auto',
    marker = list(color = 'green')
  ) %>% 
  add_trace(y = ~우체국,
            name = "우체국",
            textposition = 'auto',
            marker = list(color = 'orange')) %>% 
  add_trace(y = ~농협,
            name = "농협",
            textposition = 'auto',
            marker = list(color = 'blue')) %>% 
  layout(legend = list(orientation = "v",   # show entries horizontally
                       xanchor = "center",  # use center of legend as anchor
                       x = 0.9,
                       y = 1.09)) 
```

### 데이터(서울) {data-height=60%}

```{r}
asdf_seoul %>% 
  select(구분, 시도, 시군구, name,addr, created_at, stock_at, remain_stat_kr) %>% 
  rename(기관명 = name, 주소 = addr, 입고일시 = stock_at, 생성일시 = created_at, 재고정보 = remain_stat_kr) %>% 
  datatable(rownames  = FALSE)
```





대구 {data-navmenu="마스크 제공 정보"}
=======================================================================

columns 1 {data-width=40%}
-----------------------------------------------------------------------

### 대구 마스크 제공 위치지도

```{r}
# 마스크 판매처 leaflet ------------------------
asdf_leaflet <- asdf_daegu %>% 
  mutate(ratingcol = case_when(
    type == "01" & remain_stat != "정보없음" ~ "green",
    type == "02" & remain_stat != "정보없음"~ "orange",
    type == "03" & remain_stat != "정보없음"~ "blue",
    TRUE ~ "black"
  ))


leaflet() %>% 
  addTiles() %>% 
  addCircleMarkers(asdf_leaflet$lng, 
                   asdf_leaflet$lat, 
                   color = asdf_leaflet$ratingcol, 
                   radius = 8, 
                   fill = T,
                   fillOpacity = 0.6,
                   opacity = 0.1,
                   popup = paste0(asdf_leaflet$name," (",asdf_leaflet$addr, "(",asdf_leaflet$remain_stat_kr,"))")) %>%
  addLegend("topright", 
            colors = c("green","orange","blue"),
            labels = c("약국",
                       "우체국",
                       "농협"), 
            opacity = 1)
```

columns 2 { data-width=60%, data-height=200}
-------------------------------------

### 대구 구별 마스크 제공 기관 그래프 {data-height=40%}

```{r}
df_plotly <- asdf_daegu %>% 
  group_by(구분,시군구) %>% 
  summarise(개수 = n()) %>% 
  arrange(구분, 시군구) %>% 
  spread(key = "구분", value = "개수") %>% 
  replace_na(list(농협 = 0, 약국 = 0, 우체국=0)) 

df_plotly <- df_plotly %>% 
  mutate("농협" = 0) 

df_plotly %>% 
  plot_ly(
    x = ~시군구,
    y = ~약국,
    type = "bar",
    name = "약국",
    textposition = 'auto',
    marker = list(color = 'green')
  ) %>% 
  add_trace(y = ~우체국,
            name = "우체국",
            textposition = 'auto',
            marker = list(color = 'orange')) %>% 
  add_trace(y = ~농협,
            name = "농협",
            textposition = 'auto',
            marker = list(color = 'blue')) %>% 
  layout(legend = list(orientation = "v",   # show entries horizontally
                       xanchor = "center",  # use center of legend as anchor
                       x = 0.9,
                       y = 1.09)) 
```

### 데이터(대구) {data-height=60%}

```{r}
asdf_daegu %>% 
  select(구분, 시도, 시군구, name,addr, created_at, stock_at, remain_stat_kr) %>% 
  rename(기관명 = name, 주소 = addr, 입고일시 = stock_at, 생성일시 = created_at, 재고정보 = remain_stat_kr) %>% 
  datatable(rownames  = FALSE)
```



Reference
=======================================================================
**0. 데이터 **

- 공공데이터 포털 - 코로나 : https://www.data.go.kr/issues/3/show.do

**1. Flexdashboard 참고 자료**

- Flexdashboard 튜토리얼: https://rmarkdown.rstudio.com/flexdashboard/index.html
- 테마: http://www.sangerw.com/blog/flexdashboardthemes/#IDreadable
- Flexdashboard CRAN: https://cran.r-project.org/web/packages/flexdashboard/flexdashboard.pdf
- bookdown in Flexdashboard: https://bookdown.org/yihui/rmarkdown/dashboards.html
- Making Dashboards in R Markdown: https://arm.rbind.io/slides/flexdashboard.html

**1-1. Flexdashboard 예제**

- 예제 1: https://beta.rstudioconnect.com/juliasilge/policeshooting/policeshooting.html
  - 예제코드: https://gist.github.com/juliasilge/9acbe97c549502bac85404779edceba0
- 예제 2: https://jenthompson.me/examples/progressdash.html
  - 예제코드: https://github.com/jenniferthompson/MOSAICProgress/blob/master/progressdash.Rmd
- 예제 3: https://jenthompson.me/examples/insight_progress.html
  - 예제코드: https://github.com/jenniferthompson/INSIGHTProgress/blob/master/insight_progress.Rmd
- 예제 4: https://tonyelhabr.rbind.io/files/nba-tms.html

**2. leaflet 참고자료**

- https://rstudio.github.io/leaflet/
- https://leafletjs.com/examples.html
- https://rstudio.github.io/leaflet/

**3. 대시보드 UI 참고자료**

- http://ncov.mohw.go.kr/
- http://www.bix5.net/examples

**4. 위경도로 행정구역 추출 참고자료**

- https://developers.kakao.com/docs/restapi/local#좌표-행정구역정보-변환


**5. 아이콘 List**

- https://fontawesome.com/v4.7.0/icons/