How put value when exist in other rows?

[M_AcostaCH]

Hi community

I want to correct the coordinates of a database. I have only in some cases a new correction for latitude or longitude but in somes cases both changes.
So, when I graph in leaflet I get an error for those blank data.
The idea is that when the blank space is filled with the data from the first rows of the A-D
The Acces column is an identifier

dat <- data.frame(Acces=c('A','B','C','D','E',
                          'A','B','C','D','E'),
                  latitud=c( -24.12,-26.33,-27.32,-29.48,-27.43,
                             '',-26.80,-27.3206, '', -27.4334),
                  longitud=c(-65.40,-58.75,-58.58,-56.48,	-58.82,
                             -65.4027,-58.9666,'', -56.9833, -58.8337))

Hope obtain this:

Tnks!

[scottyd22]

This can be accomplished with the na.locf() function from the zoo package by first converting empty character strings "" to NA. The only caveat is the first row in the group needs to have a non-NA value.

library(tidyverse)
library(zoo)

dat %>%
  mutate_at(2:3, ~ifelse(. == '', NA, .)) %>%
  group_by(Acces) %>%
  mutate(latitud = na.locf(latitud),
         longitud = na.locf(longitud)
         ) %>%
  ungroup()
#> # A tibble: 10 × 3
#>    Acces latitud  longitud
#>    <chr> <chr>    <chr>   
#>  1 A     -24.12   -65.4   
#>  2 B     -26.33   -58.75  
#>  3 C     -27.32   -58.58  
#>  4 D     -29.48   -56.48  
#>  5 E     -27.43   -58.82  
#>  6 A     -24.12   -65.4027
#>  7 B     -26.8    -58.9666
#>  8 C     -27.3206 -58.58  
#>  9 D     -29.48   -56.9833
#> 10 E     -27.4334 -58.8337

Created on 2022-12-09 with reprex v2.0.2.9000

[andresrcs]

Another option assuming they are in the desired order

library(dplyr)
library(tidyr)

dat <- data.frame(Acces=c('A','B','C','D','E',
                          'A','B','C','D','E'),
                  latitud=c( -24.12,-26.33,-27.32,-29.48,-27.43,
                             '',-26.80,-27.3206, '', -27.4334),
                  longitud=c(-65.40,-58.75,-58.58,-56.48,   -58.82,
                             -65.4027,-58.9666,'', -56.9833, -58.8337))

dat %>% 
    mutate(across(c(latitud, longitud), na_if, y = "")) %>% 
    group_by(Acces) %>% 
    fill(latitud, longitud, .direction = "down") %>% 
    ungroup()
#> # A tibble: 10 × 3
#>    Acces latitud  longitud
#>    <chr> <chr>    <chr>   
#>  1 A     -24.12   -65.4   
#>  2 B     -26.33   -58.75  
#>  3 C     -27.32   -58.58  
#>  4 D     -29.48   -56.48  
#>  5 E     -27.43   -58.82  
#>  6 A     -24.12   -65.4027
#>  7 B     -26.8    -58.9666
#>  8 C     -27.3206 -58.58  
#>  9 D     -29.48   -56.9833
#> 10 E     -27.4334 -58.8337

^{Created on 2022-12-09 with reprex v2.0.2}

[M_AcostaCH]

The both solutions are excellent.
Tnks guys!