I've tried to find the answer to this simple question without anyluck.

Let's say I have:

A <- c(1101,1102,1103)

and a dataframe that looks like this:

t    m    com   x
1    1    1101  10
1    1    1102  15
1    1    1103  20
1    2    NA    NA
1    3    1101  20
1    3    1102  25
1    3    1103  30
1    4    NA    NA
1    5    1101  25
1    5    1102  30
1    5    1103  35

and since what I want to do is a linear interpolation of X with na.approx (actual dataframe and object are way bigger), I need the dataframe to look like this:

t    m    com   x
1    1    1101  10
1    1    1102  15
1    1    1103  20
1    2    1101  NA
1    2    1102  NA
1    2    1103  NA
1    3    1101  20
1    3    1102  25
1    3    1103  30
1    4    1101  NA
1    4    1102  NA
1    4    1103  NA
1    5    1101  25
1    5    1102  30
1    5    1103  35

I haven't tried any code for this because I don't know where to start.

Any help and/or r material that you consider usefull would be great.

Thanks,

CodePudding user response：

The function you need is tidyr::complete().

1. Since you would like to "expand" column com within group of m, you need to group_by(m) first,
2. then use the vector A to complete the com column.
3. In this case, the t column will be filled with NA by default, we can fill() up column t using the value in the previous row (since you said you have a large dataset, this should work better than setting the fill parameter in complete()).
4. Then drop any NA in the com column (these are the original NA in your data set).
5. Finally, reorder the columns back to their original position.

library(tidyverse)

A <- c(1101,1102,1103)

df %>% 
  group_by(m) %>% 
  complete(com = A) %>% 
  fill(t, .direction = "up") %>% 
  drop_na(com) %>% 
  select(t, m, com, x)

# A tibble: 15 x 4
# Groups:   m [5]
       t     m   com     x
   <int> <int> <dbl> <int>
 1     1     1  1101    10
 2     1     1  1102    15
 3     1     1  1103    20
 4     1     2  1101    NA
 5     1     2  1102    NA
 6     1     2  1103    NA
 7     1     3  1101    20
 8     1     3  1102    25
 9     1     3  1103    30
10     1     4  1101    NA
11     1     4  1102    NA
12     1     4  1103    NA
13     1     5  1101    25
14     1     5  1102    30
15     1     5  1103    35