3

I am using the Googleway package to get the elevation information for a bunch of lat long coordinates of which there are 954 in total.

I've broken the calls into 3 separate files but they're in list format and when I convert them to a dataframe they are in nested dataframe formats. I've been trying to flatten the files and unlist them but I am having no success.

DF <- read.csv("Site Coor R.csv", header = T, colClasses = c("numeric","numeric"))

result1 <- google_elevation(df_locations = DF[1:350,], key = "KEY")
result2 <- google_elevation(df_locations = DF[351:700,], key = "KEY")
result3 <- google_elevation(df_locations = DF[701:954,], key = "KEY")

> str(result1)
List of 2
 $ results:'data.frame':    350 obs. of  3 variables:
  ..$ elevation : num [1:350] 14.15 2.14 2.66 6.78 23.27 ...
  ..$ location  :'data.frame':  350 obs. of  2 variables:
  .. ..$ lat: num [1:350] 52.7 52.7 52.7 52.9 52.7 ...
  .. ..$ lng: num [1:350] -8.61 -8.83 -8.92 -8.98 -8.91 ...
  ..$ resolution: num [1:350] 611 611 611 611 611 ...
 $ status : chr "OK"


do.call("c", result1[["location"]])

or

result1 <- unlist(result1, recursive = TRUE, use.names = TRUE)

or 

write.table(data.frame(subset(result1DF,select=-c(results.location)),unclass(result1DF$results.location)))

Since result1, result2 and result3 are of the same structure is there a simple way to merge them, flatten the conjoined table and then export as CSV?

TheGoat
  • 2,587
  • 3
  • 25
  • 58
  • 2
    Try `do.call(data.frame, result1$results)` – akrun Mar 17 '17 at 12:31
  • 1
    For each result call `function(r) cbind(r$results$elevation, r$results$location, r$results$resolution)` to get a flat dataframe from the result. After that you have to `rbind()` the datarames for `result1`, `result2`, `result3` – jogo Mar 17 '17 at 12:35

1 Answers1

6

We can get all the objects in a list and create data.frame in a single call

lst <- lapply(mget(paste0("result", 1:3)), function(x) do.call(data.frame, x$results))
str(lst[[1]])
#'data.frame':   12 obs. of  3 variables:
#$ elevation   : num  -0.546 0.537 0.42 -0.584 0.847 ...
#$ location.lat: int  61 85 53 80 82 52 66 62 68 57 ...
#$ location.lng: int  11 7 10 19 1 -2 -6 -8 -14 -13 ...

If we need a single table, then rbind them together

library(data.table)
dt <- rbindlist(lst)
fwrite(dt, file = "yourfile.csv")

data

f1 <- function(seed){
     set.seed(seed)
     results <- data.frame(elevation = rnorm(12))
     results$location <- data.frame(lat = sample(50:100, 12, replace=TRUE), 
           lng = sample(-15:20, 12, replace=TRUE))
      results
  }

result1 <- list(results = f1(24), status = "OK")
result2 <- list(results = f1(42), status = "OK")
result3 <- list(results = f1(343), status = "OK")
akrun
  • 874,273
  • 37
  • 540
  • 662