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rdataframedplyrgpsdata-conversion

Conversion of Decimal Minutes Seconds into Decimal Degrees when cells within the Columns Contains the Factor 'Missed' in R

Issue

I have a data frame with 388 columns and two of these columns are labelled 'Longitude_E' and 'Latitude_N', containing GPS coordinates in degrees, minutes, and seconds (DMS).

I aim to create two empty columns, and label them as 'Decimal_Degrees_Longitude_E' and 'Degrees_Decimal_Latitude_N' because I want to insert GPS coordinates in decimal degrees (DD) into them, which have been converted from the DMS columns.

This data has been collected during fieldwork, and on some survey sheets, the GPS coordinates are missing, so some of the cells contain the factor 'Missed'

For Example:

[1] 33.53.270   33.85.093   33.52.7711  33.52.790   33.52.790   33.51.00    Missed      Missed     
  [9] 33.85.093   Missed      33.50.141   33.85.0925  33.50.20    33.80.14991 33.50.471   Missed     
 [17] 33.49.49.89 33.57.9389  33.57.939   Missed      Missed      33.49.755   33.48.452   33.85.093  
 [25] Missed      33.57.9389  33.48.7932  33.53.27    Missed      33.52.79    33.56.3312  33.55.2628 
 [33] 33.49.2552  33.49.2560  33.48.830   33.56.198   33.49.3460  Missed      33.5279     Missed     
 [41] 33.48.452   33.85.0925  33.51.199   33.51.199   33.52.479   Missed      33.49.2552  33.52.452  
 [49] Missed      33.50.106   33.50.106   Missed      33.85.0925  33.50.20?   33.50.6010  33.50.111  
 [57] 33.40.4042  Missed      33.52.479   33.51.103   33.52.284   38.52.144   33.50.549   33.48.8310 
 [65] 33.52,79    33.52.284   33.52.682   33.85.0925  33.51.493   33.51.007   33.47.078   33.85.0925 
 [73] Missed      Missed      33.850.925  33.53.27    33.850.925  33.850.925  33

I Created two Empty Columns to Insert the DD Values into

library(dplyr, warn = FALSE)

New_Df<- myDf |>
              mutate(
              Decimal_Degrees_Longitude_E = NA,
              Decimal_Degrees_Latitude_N = NA,
              .after = 14
              )

New_Df

I can't figure out how to modify the functions (below) so the factor 'Missed' contained within the cells of the columns doesn't interfere with the conversion of DMS to DD, and insert the DD values into the two empty-named columns.

A Section of my Data Frame:

New_Df<-structure(c("33°53'27.0", "33°85'09.3", "33°52'77.1", "33°52'79.0", 
"33°52'79.0", "33°51'00.", "Missed", "Missed", "33°85'09.3", 
"Missed", "33°50'14.1", "33°85'09.2", "33°50'20.", "33°80'14.9", 
"33°50'47.1", "Missed", "33°49'0.0", "33°57'93.8", "33°57'93.9", 
"Missed", "Missed", "33°49'75.5", "33°48'45.2", "33°85'09.3", 
"Missed", "33°57'93.8", "33°48'79.3", "33°53'27.", "Missed", 
"33°52'79.", "27°16'04.0", "27°40'93.2", "27°28'44.", "27°15'85.0", 
"27°15'85.0", "27°21'40.", "Missed", "Missed", "27°40'93.2", 
"Missed", "27°13'20.0", "27°40'93.1", "27°20'45.", "27°31'21.4", 
"27°13'94.9", "Missed", "27°11'44.6", "27°10'85.2", "23°10'85.2", 
"Missed", "Missed", "27°21'68.0", "27°18'19.0", "27°40'93.2", 
"Missed", "27°10'85.2", "27°17'79.2", "27°16'04.", "Missed", 
"27°15'85.", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA
), dim = c(30L, 4L), dimnames = list(NULL, c("Longitude_E_Corrected", 
"Latitude_N_Corrected", "Decimal_Degrees_Longitude_E", "Decimal_Degrees_Latitude_N"
)))
Solution

  • First replacing "Missing" with NA (using apply since class(mat) is [1] "matrix" "array"), then giving the data to mutate / across. Finally map_vec the strsplit values per variable to get the results.

    library(dplyr)

as_tibble(apply(mat, 2, \(x) replace(x, x == "Missed", NA))) %>% 
  mutate(across(matches("^Latitude_N|^Longitude_E"), \(cols) 
    purrr::map_vec(strsplit(cols, "°|'"), ~ 
      as.numeric(.x[1]) + as.numeric(.x[2]) / 60 + as.numeric(.x[3]) / 60 ^ 2), 
    .names="Decimal_Degrees_{col}"))

    output

    # A tibble: 30 × 4
   Longitude_E_Corrected Latitude_N_Corrected Decimal_Degrees_Longitude_E_Corr…¹
   <chr>                 <chr>                                             <dbl>
 1 33°53'27.0            27°16'04.0                                         33.9
 2 33°85'09.3            27°40'93.2                                         34.4
 3 33°52'77.1            27°28'44.                                          33.9
 4 33°52'79.0            27°15'85.0                                         33.9
 5 33°52'79.0            27°15'85.0                                         33.9
 6 33°51'00.             27°21'40.                                          33.8
 7 NA                    NA                                                 NA
 8 NA                    NA                                                 NA
 9 33°85'09.3            27°40'93.2                                         34.4
10 NA                    NA                                                 NA
# ℹ 20 more rows
# ℹ abbreviated name: ¹​Decimal_Degrees_Longitude_E_Corrected
# ℹ 1 more variable: Decimal_Degrees_Latitude_N_Corrected <dbl>
# ℹ Use `print(n = ...)` to see more rows
    Data
    mat <- structure(c("33°53'27.0", "33°85'09.3", "33°52'77.1", "33°52'79.0",
"33°52'79.0", "33°51'00.", "Missed", "Missed", "33°85'09.3",
"Missed", "33°50'14.1", "33°85'09.2", "33°50'20.", "33°80'14.9",
"33°50'47.1", "Missed", "33°49'0.0", "33°57'93.8", "33°57'93.9",
"Missed", "Missed", "33°49'75.5", "33°48'45.2", "33°85'09.3",
"Missed", "33°57'93.8", "33°48'79.3", "33°53'27.", "Missed",
"33°52'79.", "27°16'04.0", "27°40'93.2", "27°28'44.", "27°15'85.0",
"27°15'85.0", "27°21'40.", "Missed", "Missed", "27°40'93.2",
"Missed", "27°13'20.0", "27°40'93.1", "27°20'45.", "27°31'21.4",
"27°13'94.9", "Missed", "27°11'44.6", "27°10'85.2", "23°10'85.2",
"Missed", "Missed", "27°21'68.0", "27°18'19.0", "27°40'93.2",
"Missed", "27°10'85.2", "27°17'79.2", "27°16'04.", "Missed",
"27°15'85."), dim = c(30L, 2L), dimnames = list(NULL, c("Longitude_E_Corrected",
"Latitude_N_Corrected")))