Add blank rows in between existing rows

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I have a dataset of 240 cases, in which I want to create a blank row after each existing row. Leaving me with 480 rows, of which half is filled and the other half is empty (

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忘了有多久

2021-01-06 06:21

We can duplicate each row and then set the row with even row numbers to be NA.

dt2 <- dt[rep(1:nrow(dt), each = 2), ]
dt2[1:nrow(dt2) %% 2 == 0, ] <- NA

head(dt2)
    id groep_MNC zkhs fbeh    pgebdat    p_age pgesl
1    3         1    1    1 1955-12-01 42.50000     1
1.1 NA        NA   NA   NA       <NA>       NA    NA
2    5         1    1    1 1943-04-09 55.16667     1
2.1 NA        NA   NA   NA       <NA>       NA    NA
3    7         1    1    1 1958-04-10 40.25000     1
3.1 NA        NA   NA   NA       <NA>       NA    NA

DATA

dt <- read.table(text = "  id groep_MNC zkhs fbeh    pgebdat    p_age pgesl
1  3         1    1    1 1955-12-01 42.50000     1
2  5         1    1    1 1943-04-09 55.16667     1
3  7         1    1    1 1958-04-10 40.25000     1
4 10         1    1    1 1958-04-17 40.25000     1
5 12         1    1    2 1947-11-01 50.66667     1
6 14         1    1    2 1952-02-02 46.41667     1",
                 header = TRUE, stringsAsFactors = FALSE)

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星月不相逢

2021-01-06 06:29

Try this:

require(dplyr)

df %>% 
  group_by(id) %>% 
  do(rbind(.,c(.$id,rep(NA,NCOL(df)-1)))) %>%
  ungroup() %>% data.frame()

Output:

   id groep_MNC zkhs fbeh    pgebdat    p_age pgesl
1   3         1    1    1 1955-12-01 42.50000     1
2   3        NA   NA   NA       <NA>       NA    NA
3   5         1    1    1 1943-04-09 55.16667     1
4   5        NA   NA   NA       <NA>       NA    NA
5   7         1    1    1 1958-04-10 40.25000     1
6   7        NA   NA   NA       <NA>       NA    NA
7  10         1    1    1 1958-04-17 40.25000     1
8  10        NA   NA   NA       <NA>       NA    NA
9  12         1    1    2 1947-11-01 50.66667     1
10 12        NA   NA   NA       <NA>       NA    NA
11 14         1    1    2 1952-02-02 46.41667     1
12 14        NA   NA   NA       <NA>       NA    NA

Sample data:

require(data.table)
df <- fread("id groep_MNC zkhs fbeh    pgebdat    p_age pgesl
              3         1    1    1 1955-12-01 42.50000     1
              5         1    1    1 1943-04-09 55.16667     1
              7         1    1    1 1958-04-10 40.25000     1
             10         1    1    1 1958-04-17 40.25000     1
             12         1    1    2 1947-11-01 50.66667     1
             14         1    1    2 1952-02-02 46.41667     1")

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死守一世寂寞

2021-01-06 06:29

Another option using dplyr:

library(dplyr)
df %>%
  split(df$id) %>%
  Map(rbind, ., NA) %>%
  do.call(rbind, .) %>%
  mutate(id = rep(df$id, each = 2))

Or you can use map_dfr from purrr:

library(purrr)
df %>%
  group_by(id) %>%
  map_dfr(rbind, NA) %>%
  mutate(id = rep(df$id, each = 2))

Result:

# A tibble: 12 x 7
      id groep_MNC  zkhs  fbeh    pgebdat    p_age pgesl
   <int>     <int> <int> <int>      <chr>    <dbl> <int>
 1     3         1     1     1 1955-12-01 42.50000     1
 2     3        NA    NA    NA       <NA>       NA    NA
 3     5         1     1     1 1943-04-09 55.16667     1
 4     5        NA    NA    NA       <NA>       NA    NA
 5     7         1     1     1 1958-04-10 40.25000     1
 6     7        NA    NA    NA       <NA>       NA    NA
 7    10         1     1     1 1958-04-17 40.25000     1
 8    10        NA    NA    NA       <NA>       NA    NA
 9    12         1     1     2 1947-11-01 50.66667     1
10    12        NA    NA    NA       <NA>       NA    NA
11    14         1     1     2 1952-02-02 46.41667     1
12    14        NA    NA    NA       <NA>       NA    NA

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