《饮威地图》

Whisky map

Whisky

Author

Tony D

Published

May 10, 2021

library(openxlsx)
library(readxl)
library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ ggplot2   3.5.2     ✔ tibble    3.3.0
✔ lubridate 1.9.4     ✔ tidyr     1.3.1
✔ purrr     1.1.0     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(tidygeocoder)

#data

data=read_excel('data/data.xlsx')

glimpse(data)

Rows: 27
Columns: 6
$ name    <chr> "Aloha Whisky", "J's Bar", "Tamahiko", "Bar Nadurra", "Campbel…
$ address <chr> "Japan, 〒171-0021 Tokyo, Toshima City, Nishiikebukuro, 3 Chome…
$ date    <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
$ region  <chr> "japan", "japan", "japan", "japan", "japan", "japan", "japan",…
$ type    <chr> "bar", "bar", "bar", "bar", "bar", "bar", "bar", "distillery",…
$ common  <chr> "whisky bar", "whisky bar", "whisky bar", "whisky bar", "whisk…

from address to latitude, longitude

geo("485 Niseko, Abuta District, Hokkaido 048-1511, Japan")

Passing 1 address to the Nominatim single address geocoder

Query completed in: 1.5 seconds

# A tibble: 1 × 3
  address                                                lat  long
  <chr>                                                <dbl> <dbl>
1 485 Niseko, Abuta District, Hokkaido 048-1511, Japan  42.8  141.

from latitude, longitude to address

reverse_geo(lat=35.73616,long=139.7142)

Passing 1 coordinate to the Nominatim single coordinate geocoder

Query completed in: 1 seconds

# A tibble: 1 × 3
    lat  long address                                                       
  <dbl> <dbl> <chr>                                                         
1  35.7  140. 川越街道, 上池袋二丁目, 上池袋, 豊島区, 東京都, 170-0014, 日本

search all address to latitude, longitude

# geocode the addresses
data002 <- data %>%
  geocode(address, method = 'arcgis', lat = latitude , long = longitude)

Passing 27 addresses to the ArcGIS single address geocoder

Query completed in: 17.5 seconds

glimpse(data002)

Rows: 27
Columns: 8
$ name      <chr> "Aloha Whisky", "J's Bar", "Tamahiko", "Bar Nadurra", "Campb…
$ address   <chr> "Japan, 〒171-0021 Tokyo, Toshima City, Nishiikebukuro, 3 Cho…
$ date      <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
$ region    <chr> "japan", "japan", "japan", "japan", "japan", "japan", "japan…
$ type      <chr> "bar", "bar", "bar", "bar", "bar", "bar", "bar", "distillery…
$ common    <chr> "whisky bar", "whisky bar", "whisky bar", "whisky bar", "whi…
$ latitude  <dbl> 35.73130, 35.73252, 35.73231, 35.73202, 35.67363, 35.67134, …
$ longitude <dbl> 139.7067, 139.7104, 139.7077, 139.7151, 139.7609, 139.7611, …

write.xlsx(data002,'data002.xlsx')

show map

library(mapview)
library(sp)
library(leaflet)

#m=mapview(data002, map.types='OpenStreetMap',label='name',xcol = "longitude", ycol = "latitude", crs = 4269, grid = FALSE,zcol='type')

m=mapview(data002,label='name',xcol = "longitude", ycol = "latitude", crs = 4269, grid = FALSE,zcol='type')
m

# set initial zoom level for mapview
#cntr_crds <- c(mean(data002$longitude),mean(data002$latitude))
#m@map %>% setView(cntr_crds[1], cntr_crds[2],zoom = 12)

resource:

https://github.com/r-spatial/mapview