# stable
install.packages("omwr")
# unstable
remotes::install_github("crazycapivara/owmr")First of all you have to store your API key in an environment variable called OWM_API_KEY. For the current session this can be done with:
Sys.setenv(OWM_API_KEY = "yourSuperSecretApiKey")Due to the ... parameter in R you can pass all parameters defined in the openweathermap-api-reference to the functions fetching data.
library(owmr)
current <- get_current("Kassel", units = "metric", lang = "de")
class(current)## [1] "list" "owmr_weather"forecast <- get_forecast("Malaga", units = "metric")
class(forecast)## [1] "list" "owmr_forecast"(nyc <- search_city_list("New York City"))## id nm lat lon countryCode
## 32214 5128581 New York City 40.71427 -74.00597 UScurrent_multiple <- find_cities_by_geo_point(
nyc$lat,
nyc$lon,
cnt = 5,
units = "metric"
)
class(current_multiple)## [1] "list" "owmr_find"bbox_greater_london <- c(-0.489, 51.28, 0.236, 51.686, 10)
current_greater_london <- find_cities_by_bbox(bbox_greater_london)
class(current_greater_london)## [1] "list" "owmr_box_city"owmr_as_tibble
columns <- c("dt_txt", "temp","pressure", "humidity" ,"temp_min", "temp_max")
current %>% owmr_as_tibble() %>%
.[, columns]## # A tibble: 1 x 6
## dt_txt temp pressure humidity temp_min temp_max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2019-12-12 07:20:02 1.81 1002 95 -0.56 4.44forecast %>% owmr_as_tibble() %>%
.[1:4, columns]## # A tibble: 4 x 6
## dt_txt temp pressure humidity temp_min temp_max
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2019-12-12 09:00:00 37.9 1015 9 37.9 38.1
## 2 2019-12-12 12:00:00 32.0 1016 16 32.0 32.2
## 3 2019-12-12 15:00:00 28.7 1017 14 28.7 28.8
## 4 2019-12-12 18:00:00 28.1 1015 16 28.1 28.2current_multiple %>% owmr_as_tibble() %>%
.[, c(columns, "name")]## # A tibble: 5 x 7
## dt_txt temp pressure humidity temp_min temp_max name
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <chr>
## 1 2019-12-12 07:17:29 -1.76 1035 54 -4.44 0.56 New York
## 2 2019-12-12 07:17:25 -1.81 1035 54 -4.44 0.56 Hoboken
## 3 2019-12-12 07:17:25 -1.88 1035 54 -4.44 0.56 Hudson County
## 4 2019-12-12 07:17:25 -1.89 1035 54 -4.44 0.56 Jersey City
## 5 2019-12-12 07:17:29 -1.75 1035 54 -4.44 0.56 Long Island Citycurrent_greater_london %>% owmr_as_tibble() %>%
.[, c(columns, "name")]## # A tibble: 5 x 7
## dt_txt temp pressure humidity temp_min temp_max name
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <chr>
## 1 2019-12-12 07:0… 1.16 1000 86 -0.56 3 City of London
## 2 2019-12-12 07:1… 1.27 999 86 -1.11 3.33 Blackheath
## 3 2019-12-12 07:1… 1.43 999 100 -0.56 3.33 London Borough of …
## 4 2019-12-12 07:0… 0.78 1000 74 -1.11 2.22 Dagenham
## 5 2019-12-12 07:0… 1.34 1000 100 0 3 Watfordrio <- search_city_list("Rio de Janeiro")
# Get data for 9 cities around Rio
owm_data <- find_cities_by_geo_point(
lat = rio$lat,
lon = rio$lon,
cnt = 9,
units = "metric"
) %>% owmr_as_tibble()
owm_data %<>% parse_columns(list(temp = round))
head(owm_data)## # A tibble: 6 x 22
## dt_txt temp pressure humidity temp_min temp_max weather_id weather_main
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <chr>
## 1 2019-… 22 1008 94 20 23 300 Drizzle
## 2 2019-… 22 1008 94 19.4 23 300 Drizzle
## 3 2019-… 22 1008 94 19.4 23 300 Drizzle
## 4 2019-… 22 1007 94 20 23 500 Rain
## 5 2019-… 22 1008 94 20 23 500 Rain
## 6 2019-… 22 1008 94 20 23 300 Drizzle
## # … with 14 more variables: weather_description <chr>, weather_icon <chr>,
## # wind_speed <dbl>, wind_deg <dbl>, clouds_all <dbl>, id <int>, name <chr>,
## # dt <int>, rain <lgl>, snow <lgl>, coord_lat <dbl>, coord_lon <dbl>,
## # feels_like <dbl>, sys_country <chr># Create a popup template
popup_tpl <- paste0(
"<b>{{name}}</b></br>",
"{{coord_lon}}, {{coord_lat}}</br>",
"{{temp}}°C, ",
"<i>{{weather_description}}</i>"
)
# Test it ...
popup_tpl %$$% owm_data %>% head(2)## [1] "<b>Rio de Janeiro</b></br>-43.21, -22.9</br>22°C, <i>light intensity drizzle</i>"
## [2] "<b>São Cristóvão</b></br>-43.23, -22.9</br>22°C, <i>light intensity drizzle</i>"library(leaflet)
leaflet(width = "100%") %>%
addProviderTiles("CartoDB.DarkMatter") %>%
add_weather(owm_data, icon = owm_data$weather_icon, template = popup_tpl)Furthermore, you can add weather map layers from OpenWeatherMap to the map object via add_owm_tiles. For available layers see owm_layers.