Removing blank rows in the two data frames and combine them - r

Question

I have a dataset which contains two groups. First 3 columns are 1st group and next 3 columns are 2nd group. They contains missing values at random manner.
I have to delete the rows containing complete missing values in any one group. And both group contains at least one value in the row.
At last I have to combine both the groups.
I have tried many R codes. Please suggest some useful R function for this issue.
example data structure

Answer 1

If your data is properly named, this can be done using starts_with and if_any (otherwise you might rename your columns first as you see fit)
library(tidyverse)
df <- tribble(
~x1, ~x2, ~x3, ~y1, ~y2, ~y3,
26.4, 26.5, 26.6, 26.7, 26.4, 26.5,
NA, NA, NA, 23.7, NA, NA,
27.2, 28.0, 27.9, 27.6, 27.8, 27.7,
NA, 24.2, 24.9, 23.9, 24.9, 24.0,
24.3, NA, 24.3, 24.0, 24.1, 24.5,
26.9, 26.7, 27.0, 26.9, 26.8, 26.8,
24.4, 24.4, 24.5, 24.8, 24.3, 24.3,
NA, NA, NA, 23.9, NA, NA,
NA, NA, NA, 23.9, NA, NA,
24.9, NA, NA, 24.9, NA, NA,
NA, NA, NA, 24.5, NA, NA,
28.3, 28.2, 28.3, 28.2, 28.4, 28.3,
28.3, 28.4, 28.1, 28.3, 28.3, 28.2
)
df %>% filter(!if_all(starts_with("x"), is.na) & !if_all(starts_with("y"), is.na))
#> # A tibble: 9 × 6
#> x1 x2 x3 y1 y2 y3
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 26.4 26.5 26.6 26.7 26.4 26.5
#> 2 27.2 28 27.9 27.6 27.8 27.7
#> 3 NA 24.2 24.9 23.9 24.9 24
#> 4 24.3 NA 24.3 24 24.1 24.5
#> 5 26.9 26.7 27 26.9 26.8 26.8
#> 6 24.4 24.4 24.5 24.8 24.3 24.3
#> 7 24.9 NA NA 24.9 NA NA
#> 8 28.3 28.2 28.3 28.2 28.4 28.3
#> 9 28.3 28.4 28.1 28.3 28.3 28.2
Created on 2022-06-18 by the reprex package (v2.0.1)

Answer 2

I am not sure I understand your question, but here is a demonstration using dplyr::if_all() , dplyr::if_any()
library(tidyverse)
# Example data
# have to delete the rows containing complete missing values in any one group.
# And both group contains at least one value in the row. (Not sure what that means)
# At last I have to combine both the groups.
d <- tibble::tribble(
~gr1_col1, ~gr1_col2, ~gr1_col3, ~gr2_col1, ~gr2_col2, ~gr2_col3,
1, 2, NA, 1, 1, 1,
NA, NA, NA, NA, 1, 1,
NA, 1, 1, NA, NA, 1,
1, NA, 2, NA, NA, NA,
)
d
#> # A tibble: 4 x 6
#> gr1_col1 gr1_col2 gr1_col3 gr2_col1 gr2_col2 gr2_col3
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 2 NA 1 1 1
#> 2 NA NA NA NA 1 1
#> 3 NA 1 1 NA NA 1
#> 4 1 NA 2 NA NA NA
d %>%
dplyr::filter(
# First group
!dplyr::if_all(.cols = c(1, 2, 3), .fns = is.na), # removing rows if all columns 1, 2 and 3 are NA
# second group
!if_all(.cols = c(4, 5, 6), .fns = is.na) # removing rows if all columns 1, 2 and 3 are NA
)
#> # A tibble: 2 x 6
#> gr1_col1 gr1_col2 gr1_col3 gr2_col1 gr2_col2 gr2_col3
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 2 NA 1 1 1
#> 2 NA 1 1 NA NA 1
# Not sure what you mean with how you want to combine groups
Created on 2022-06-17 by the reprex package (v2.0.1)