Create a web page using R Markdown that features a map created with Leaflet.
Host your webpage on either GitHub Pages, RPubs, or NeoCities.
Your webpage must contain the date that you created the document, and it must contain a map created with Leaflet. We would love to see you show off your creativity!
Note: This assignment have done on R Studio Cloud.
library(leaflet)library(htmltools)From Kagle: Dataset about the best restaurants in the world. By Megh Mayur.
Contains the list of The World’s 50 Best Restaurants for 2018
(https://www.kaggle.com/mmayur/the-worlds-50-best-restaurants)
##setwd("/Cloud/project")
datamap <- read.csv(file = "TheWorlds50BestRestaurants2018.csv", header = TRUE, sep = ",")restaurant_lists <- data.frame(Ranking = datamap$Ranking,
Name = datamap$Name,
City = datamap$City,
Country = datamap$Country,
Latitude = datamap$Latitude,
Longitude = datamap$Longitude
)restaurant_lists## Ranking Name City Country
## 1 1 Osteria Francescana Modena Italy
## 2 2 El Celler de Can Roca Girona Spain
## 3 3 Mirazur Menton France
## 4 4 Eleven Madison Park New York USA
## 5 5 Gaggan Bangkok Thailand
## 6 6 Central Lima Peru
## 7 7 Maido Lima Peru
## 8 8 Arpège Paris France
## 9 9 Mugaritz San Sebastian Spain
## 10 10 Asador Etxebarri Axpe Spain
## 11 11 Quintonil Mexico City Mexico
## 12 12 Blue Hill at Stone Barns Pocantico Hills USA
## 13 13 Pujol Mexico City Mexico
## 14 14 Steirereck Vienna Austria
## 15 15 White Rabbit Moscow Russia
## 16 16 Piazza Duomo Alba Italy
## 17 17 Den Tokyo Japan
## 18 18 Disfrutar Barcelona Spain
## 19 19 Geranium Copenhagen Denmark
## 20 20 Attica Melbourne Australia
## 21 21 Alain Ducasse au Plaza Athénée Paris France
## 22 22 Narisawa Tokyo Japan
## 23 23 Le Calandre Rubano Italy
## 24 24 Ultraviolet by Paul Pairet Shanghai China
## 25 25 Cosme New York USA
## 26 26 Le Bernardin New York USA
## 27 27 Boragó Santiago Chile
## 28 28 Odette Singapore Singapore
## 29 29 Alléno Paris au Pavillon Ledoyen Paris France
## 30 30 D.O.M. São Paulo Brazil
## 31 31 Arzak San Sebastian Spain
## 32 32 Tickets Barcelona Spain
## 33 33 The Clove Club London UK
## 34 34 Alinea Chicago USA
## 35 35 Maaemo Oslo Norway
## 36 36 Reale Castel di Sangro Italy
## 37 37 Restaurant Tim Raue Berlin Germany
## 38 38 Lyle's London UK
## 39 39 Astrid y Gastón Lima Peru
## 40 40 Septime Paris France
## 41 41 Nihonryori RyuGin Tokyo Japan
## 42 42 The Ledbury London UK
## 43 43 Azurmendi Larrabetzu Spain
## 44 44 Mikla Istanbul Turkey
## 45 45 Dinner by Heston Blumenthal London UK
## 46 46 Saison San Francisco USA
## 47 47 Schloss Schauenstein Fürstenau Switzerland
## 48 48 Hiša Franko Kobarid Slovenia
## 49 49 Nahm Bangkok Thailand
## 50 50 The Test Kitchen Cape Town South Africa
## Latitude Longitude
## 1 44.64310 10.934100
## 2 41.98080 2.818700
## 3 43.77470 7.504600
## 4 40.71460 -74.007100
## 5 13.75000 100.516000
## 6 -12.04300 -77.028000
## 7 -12.04300 -77.028000
## 8 48.85690 2.341200
## 9 43.31740 -1.978400
## 10 43.13000 -2.583611
## 11 19.42850 -99.127700
## 12 41.09444 -73.835833
## 13 19.42850 -99.127700
## 14 48.20250 16.368800
## 15 55.75200 37.615000
## 16 44.69610 8.034100
## 17 35.62490 139.585600
## 18 41.38750 2.168400
## 19 55.67500 12.565000
## 20 -37.81400 144.963000
## 21 48.85690 2.341200
## 22 35.62490 139.585600
## 23 45.43333 11.783333
## 24 31.22200 121.458000
## 25 40.71460 -74.007100
## 26 40.71460 -74.007100
## 27 -33.42600 -70.566000
## 28 1.28900 103.850000
## 29 48.85690 2.341200
## 30 -23.54700 -46.636000
## 31 43.31740 -1.978400
## 32 41.38750 2.168400
## 33 51.50640 -0.127200
## 34 41.88430 -87.632400
## 35 59.91200 10.746000
## 36 41.78333 14.100000
## 37 52.51610 13.377000
## 38 51.50640 -0.127200
## 39 -12.04300 -77.028000
## 40 48.85690 2.341200
## 41 35.62490 139.585600
## 42 51.50640 -0.127200
## 43 43.26194 -2.794722
## 44 41.01300 28.949000
## 45 51.50640 -0.127200
## 46 37.77710 -122.419600
## 47 46.71667 9.433333
## 48 46.24644 13.578006
## 49 13.75000 100.516000
## 50 -33.91600 18.416000restaurant_on_map <- restaurant_lists %>%
leaflet() %>%
addTiles() %>%
addMarkers(popup=paste
("<br>Country: ",
htmlEscape(restaurant_lists$Country),
"<br>City: ",
htmlEscape(restaurant_lists$City),
"<br>Restaurant: ",
htmlEscape(restaurant_lists$Name),
"<br>Ranking: ",
formatC(datamap$Ranking, format = "d", big.mark = ",")
)
)## Assuming "Longitude" and "Latitude" are longitude and latitude, respectivelyrestaurant_on_map