This map gives the location of public drinking fountains in Vienna, Austria. Coffee, wine and beer might be the local favorites, though drinking sufficient water is a grossly underestimated way to support good health.
To illustrate a Viennese drinking fountain:
Drinking water in Vienna comes from the nearby mountains through pipelines, first built by the ancient Romans. More information:
https://www.wien.info/en/sightseeing/green-vienna/viennese-water
https://www.wien.gv.at/english/environment/watersupply/supply/way.html
https://www.wien.gv.at/english/environment/watersupply/supply/history/index.html
The data is obtained on Wed Sep 04 18:05:07 2019 from the open data site of the city Vienna, capital of Austria:
https://www.data.gv.at/katalog/dataset/stadt-wien_trinkbrunnenstandortewien
library(leaflet)
url <- "https://data.wien.gv.at/daten/geo?service=WFS&request=GetFeature&version=1.1.0&typeName=ogdwien:TRINKBRUNNENOGD&srsName=EPSG:4326&outputFormat=csv"
file <- "fountain.csv"
download.file(url, file)
fountains <- read.csv(file)
dim(fountains)
## [1] 1056 5
str(fountains)
## 'data.frame': 1056 obs. of 5 variables:
## $ FID : Factor w/ 1056 levels "TRINKBRUNNENOGD.1630715",..: 443 444 445 446 447 448 449 450 451 452 ...
## $ SHAPE : Factor w/ 1055 levels "POINT (16.196657548806762 48.22938270280184)",..: 430 522 800 743 345 245 264 294 769 757 ...
## $ NAME : Factor w/ 7 levels "Auslaufbrunnen",..: 6 5 5 5 6 6 5 5 5 5 ...
## $ SE_SDO_ROWID : int 1631159 1631160 1631161 1631162 1631163 1631164 1631165 1631166 1631167 1631168 ...
## $ SE_ANNO_CAD_DATA: logi NA NA NA NA NA NA ...
head(fountains)
## FID SHAPE
## 1 TRINKBRUNNENOGD.1631159 POINT (16.353336048311327 48.25835730621713)
## 2 TRINKBRUNNENOGD.1631160 POINT (16.366715771245584 48.253918542007916)
## 3 TRINKBRUNNENOGD.1631161 POINT (16.40755714609697 48.25523423000769)
## 4 TRINKBRUNNENOGD.1631162 POINT (16.39935948031539 48.26154427339184)
## 5 TRINKBRUNNENOGD.1631163 POINT (16.342633757619602 48.22079843675031)
## 6 TRINKBRUNNENOGD.1631164 POINT (16.331390865439342 48.23463889565421)
## NAME SE_SDO_ROWID SE_ANNO_CAD_DATA
## 1 Trinkbrunnen mit Tränke 1631159 NA
## 2 Trinkbrunnen 1631160 NA
## 3 Trinkbrunnen 1631161 NA
## 4 Trinkbrunnen 1631162 NA
## 5 Trinkbrunnen mit Tränke 1631163 NA
## 6 Trinkbrunnen mit Tränke 1631164 NA
### WGS84: POLYGON ((16.577511 48.322571, 16.18218 48.117668))
Extract coordinates and get icon
tmp <- as.character(fountains$SHAPE)
tmp <- sub("(", "", tmp,fixed=TRUE)
tmp <- sub(")", "", tmp,fixed=TRUE)
tmp <- strsplit(tmp, " ")
lat <- unlist(as.numeric(lapply(tmp, `[[`, 3)))
lng <- unlist(as.numeric(lapply(tmp, `[[`, 2)))
latlng <- data.frame(lat, lng)
wassertropfen <- makeIcon(
# https://icon-icons.com/icons2/567/PNG/512/drop_icon-icons.com_54400.png,
# https://image.flaticon.com/icons/png/523/523386.png,
# https://image.flaticon.com/icons/png/179/179529.png
iconUrl = "https://image.flaticon.com/icons/png/512/427/427112.png",
iconWidth = 35*215/230, iconHeight = 35,
iconAnchorX = 35*215/230/2, iconAnchorY = 35
)
This interactive map was created on 4th of September 2019:
latlng %>%
leaflet() %>%
addTiles() %>%
addMarkers(clusterOptions = markerClusterOptions(),icon = wassertropfen, popup= "Drink water!")
Icon made by Vectors Market from www.flaticon.com
This analysis was a project for the course “Developing Data Products” from Johns Hopkins on Coursera.