Calculate distance between points using gdist() for grouped subsets

Question

A subset of my data for 2 individuals ( squirrelID ) can be found here .

My data looks as follows (only showing the relevant columns):

lat                  lon                NatalMidden   squirrelID    type
60.9577819984406    -138.0347849708050  -27           NA            Nest2017
60.9574120212346    -138.0345689691600  -27           NA            NatalMidden
60.9578209742904    -138.0346520338210  -27           23054         Foray
60.9575380012393    -138.0348329991100  -27           23054         Foray
60.9576250053942    -138.0339069664480  -27           23054         Foray
60.957643026486     -138.0338829942050  -27           23054         Foray
60.9575670026243    -138.0348739866170  -27           23054         Foray

For example, for squirrelID 23054, it was located ( Foray ) multiple times ( type column) and I have a corresponding latitude ( lat ) and longitude ( lon ) for each Foray . I am trying to calculate the distance between each Foray ( type column) and Nest2017 ( type column) for each individual ( squirrelID ) separately.

The below code works (and gives me a value of 15.11501 m), but it requires that I manually enter each point. This is not problematic, per say, but I am working with +2000 observations with more than 2 options per grid , NatalMidden , and squirrelID columns.

library(Imap)

gdist(60.9578209742904,-138.0346520338210, 60.9577819984406, -138.0347849708050, units="m", verbose=FALSE)

Is there a way I could work within the dplyr framework to group_by(squirrelID) and then calculate the distances between each Foray and its corresponding Nest2017 (which has the same NatalMidden for both the Foray and Nest2017 )?

My ultimate goal is to create a new column for the distance between the Foray and Nest2017 for each squirrelID .

UPDATE:

I have tried the following:

nests<-df %>% #creating a new data frame for Nest2017 points only
    filter(type %in% "Nest2017") %>%
    select(ID,lat,lon,ele,grid,NatalMidden,type)

foray<-df %>% #creating a new data frame for Foray points only
    filter(type %in% "Foray") %>%
    mutate(sq_id=as.factor(sq_id)) %>%
    group_by(sq_id)

But these subsets do not work in the gdist function (I get this error):

gdist(nests$lat, nests$lon, foray$lat, foray$lon, units="m", verbose=FALSE)

Error in while (abs(lamda - lamda.old) > 1e-11) { : 
  missing value where TRUE/FALSE needed
In addition: Warning messages:
1: In Ops.factor(lon.1, rad) : ‘*’ not meaningful for factors
2: In Ops.factor(lat.1, rad) : ‘*’ not meaningful for factors
3: In Ops.factor(lon.2, rad) : ‘*’ not meaningful for factors
4: In Ops.factor(lat.2, rad) : ‘*’ not meaningful for factors
5: In lon.1 - lon.2 :
  longer object length is not a multiple of shorter object length
6: In while (abs(lamda - lamda.old) > 1e-11) { :
  the condition has length > 1 and only the first element will be used

Answer 1

I am not very familiar with dplyr package but I think this would do what you are interested in:

# read data from the FigShare linked file
squirrel_data <- read.table("figshare.txt", header=T)

# split into 'Forays' and 'Nests'
nests <- squirrel_data %>%
  filter(type %in% "Nest2017")
foray <- squirrel_data %>%
  filter(type %in% "Foray")

# merge 'Forays' and 'Nests' by 'NatalMidden'
nests_foray <- inner_join(
  nests, foray, by = "NatalMidden", suffix = c(".nest", ".foray"))

# calculate the distance for each row, keep 'SquirrelID' and 'Dist'
results <- nests_foray %>%
  rowwise() %>%
  mutate(dist = gdist(lat.nest, lon.nest,
                      lat.foray, lon.foray, units = "m")) %>%
  select(squirrelID.foray, dist)
head(results, n = 3)
## A tibble: 3 x 2
#  squirrelID.foray     dist
#             <int>    <dbl>
#1            22684 14.03843
#2            22684 59.06996
#3            22684 13.40567

This is basically what I have proposed in my first comment, but using dplyr functions instead of base . The idea is simply to create inner join between "Foray" rows and "Nest2017" rows by "NatalMidded", then simply calculate the distance for each row and report it with "SquirrelID". I hope this helps.