How to work on dataframes with different lengths

General
2

Hi, what you want to do is done with joins. Here is an example that should put you on a right track:

suppressPackageStartupMessages(library(tidyverse))

tibble1 <- tibble(year = as.character(1981:1989), value = rnorm(9))
tibble2 <- tibble(year = sample(as.character(1981:1989), size = 6), value = rnorm(6))

tibble1
#> # A tibble: 9 x 2
#>   year    value
#>   <chr>   <dbl>
#> 1 1981  -0.580 
#> 2 1982  -0.0376
#> 3 1983   0.913 
#> 4 1984  -0.737 
#> 5 1985  -0.387 
#> 6 1986   0.0912
#> 7 1987   3.76  
#> 8 1988   1.10  
#> 9 1989  -0.940
tibble2
#> # A tibble: 6 x 2
#>   year   value
#>   <chr>  <dbl>
#> 1 1987   0.874
#> 2 1989  -0.282
#> 3 1984  -0.100
#> 4 1982   1.01 
#> 5 1983   0.672
#> 6 1986   1.34

tibble1$value - tibble2$value
#> Warning in tibble1$value - tibble2$value: longer object length is not a
#> multiple of shorter object length
#> [1] -1.4531519  0.2439863  1.0131162 -1.7449109 -1.0591744 -1.2475435
#> [7]  2.8834482  1.3785701 -0.8390908

dplyr::full_join(tibble1, tibble2, by = "year") %>%
  dplyr::mutate(diff = value.x - value.y)
#> # A tibble: 9 x 4
#>   year  value.x value.y    diff
#>   <chr>   <dbl>   <dbl>   <dbl>
#> 1 1981  -0.580   NA      NA    
#> 2 1982  -0.0376   1.01   -1.05 
#> 3 1983   0.913    0.672   0.241
#> 4 1984  -0.737   -0.100  -0.637
#> 5 1985  -0.387   NA      NA    
#> 6 1986   0.0912   1.34   -1.25 
#> 7 1987   3.76     0.874   2.88 
#> 8 1988   1.10    NA      NA    
#> 9 1989  -0.940   -0.282  -0.658

Created on 2018-10-23 by the reprex package (v0.2.1)

In the future, it is always helpful to try to put your question in a reprex (similar to what I did above). There is more info about how to do it here:

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