I have a data frame with columns id, latitude, longitude. I need to find near by meteorological stations and download data using RNOAA. The first step is to get station names with meteo_nearby_stations then download data with meteo_pull_monitors.
My question, is how do I retain the site id from df in the results from meteo_pull_monitors?
desired result can be seen here
library(rnoaa)
id<-c("07227500", "07308500", "07311700")
latitude<-c(35.47033,34.11009, 33.82064)
longitude<-c(101.87963,98.53172,-99.78648)
df<-data.frame(id,latitude,longitude)
met_test<-meteo_nearby_stations(df, lat_colname = "latitude",
lon_colname = "longitude", station_data = ghcnd_stations(),
var = c("TMAX","TMIN"), year_min = NULL, year_max = NULL,
radius = 200, limit = 3)
met_test_df<-do.call(rbind, lapply(met_test,as.data.frame))
met_id<-as.vector(met_test_df$id)
met_data<-meteo_pull_monitors(met_id, var = c("date","TMAX","TMIN"), date_min = "2020-01-01", date_max = "2020-06-01")
We can join the site_id data to the results of the meteo_nearby_stations() function by pulling the names of each element in the met_test list.
library(rnoaa)
id<-c("07227500", "07308500", "07311700")
latitude<-c(35.47033,34.11009, 33.82064)
longitude<-c(101.87963,98.53172,-99.78648)
df<-data.frame(id,latitude,longitude)
met_test<-meteo_nearby_stations(df, lat_colname = "latitude",
lon_colname = "longitude", station_data = ghcnd_stations(),
var = c("TMAX","TMIN"), year_min = NULL, year_max = NULL,
radius = 200, limit = 3)
Fortunately, each element of met_list contains the name of the site_id associated with the meter_nearby_stations() request. We can access this information with the names() function.
> names(met_test)
[1] "07227500" "07308500" "07311700"
>
To merge the site identifiers, we modify the do.call() function from the original post to include lapply() with an anonymous function that assigns the correct name from the list to a column we name site_id. Note that in order to loop through the list of data frames and access their names, we use a vector, 1:length(met_test) to drive the lapply() function, and include met_test as a second argument so we can use the index number x to access both the correct list element and its name.
met_test_df<-do.call(rbind, lapply(1:length(met_test),function(x,y){
data <- as.data.frame(y[[x]])
# note individual data frames already have an ID variable
data$site_id <- names(y)[x]
data
},met_test))
met_test_df
...and the output:
> met_test_df
id name latitude longitude distance site_id
1 CHM00052955 GUINAN 35.5830 100.7500 102.990626 07227500
2 CHM00056080 HEZUO 35.0000 102.9000 106.410602 07227500
3 CHM00052957 TONGDE 35.2700 100.6500 113.695195 07227500
4 CHM00056033 MADOI 34.9170 98.2170 94.243943 07308500
5 CHM00056046 DARLAG 33.7500 99.6500 110.669503 07308500
6 CHM00056029 YUSHU 33.0000 96.9670 190.415441 07308500
7 USC00419163 TRUSCOTT 3 W 33.7569 -99.8617 9.927467 07311700
8 USC00411995 COPPER BREAKS SP 34.1122 -99.7430 32.667020 07311700
9 USC00417572 RHINELAND 33.5333 -99.6500 34.356103 07311700
>
At this point we can extract the individual monitor data, and merge the site_id numbers by monitor id. First, we extract the monitor data.
met_id<-as.vector(met_test_df$id)
met_data<-meteo_pull_monitors(met_id, var = c("date","TMAX","TMIN"), date_min = "2020-01-01", date_max = "2020-06-01")
Then, we merge the site identifier data.
sites <- met_test_df[,c("id","site_id")]
mergedData <- merge(met_data,sites)
Finally, we print the first few rows of the result data frame.
head(mergedData)
id date tmax tmin site_id
1 CHM00052955 2020-01-01 81 -193 07227500
2 CHM00052955 2020-01-02 81 -163 07227500
3 CHM00052955 2020-01-03 54 -155 07227500
4 CHM00052955 2020-01-04 62 -127 07227500
5 CHM00052955 2020-01-05 62 -149 07227500
6 CHM00052955 2020-01-06 3 -216 07227500
>