How to calculate percentage variation with 3 variables in R

One way to do this with a few lines of code is through the dplyr package. I even recommend that you study it and tidyverse if you want to learn how to effectively manipulate data in R .

I think the following code will solve your problems:

Tab1612SojaQde %>%
  select('Unidade da Federação', Ano, Valor) %>%
  group_by('Unidade da Federação') %>%
  mutate(Difference = Valor - lag(Valor))

I'll describe in items what each command above does:

• %>% is a command of R called pipe . It is present in the dplyr package. What it does is take the output of a line and use it with input of the next line

• select is another function of dplyr . With it, I'm only selecting columns Unidade da Federação , Ano and Valor , as it seems to me that the other information present in this dataset is not important at this point. This step is optional. I put it here because, with fewer columns, we can see better the result.

• group_by is another function of dplyr . With it, I am informing R that it should group the data according to a column of the dataset. This grouping will allow us to apply the same function k times, where k is the number of levels of the grouped variable. In this case, it will be the federation units.

• Finally, the mutate function, also dplyr , is used together with the lag function to calculate the year-to-year variation. With mutate , I create a new column in my dataset, called Difference (could be any other name). The function lag takes the result of Valor[n]-Valor[n-1] . Note that in the result below there is no change for the year 1996. Of course, there is no value for 1995, so it is not possible to know what the change was from 1995 to 1996.

  # A tibble: 594 x 4
  # Groups:   Unidade da Federação [27]
     'Unidade da Federação' Ano    Valor Difference
     <chr>                  <chr>  <dbl>      <dbl>
   1 Rondônia               1996    1090         NA
   2 Rondônia               1997    1296        206
   3 Rondônia               1998   15790      14494
   4 Rondônia               1999   16100        310
   5 Rondônia               2000   36222      20122
   6 Rondônia               2001   68687      32465
   7 Rondônia               2002   83782      15095
   8 Rondônia               2003  126396      42614
   9 Rondônia               2004  163029      36633
  10 Rondônia               2005  233281      70252
  # ... with 584 more rows
  

With this gross difference result, you can calculate the percentage difference. Just change a little bit of the code above, adapting the formula of difference:

Tab1612SojaQde %>%
  select('Unidade da Federação', Ano, Valor) %>%
  group_by('Unidade da Federação') %>%
  mutate(Difference = 100*(Valor - lag(Valor))/lag(Valor))

    # A tibble: 594 x 4
    # Groups:   Unidade da Federação [27]
       'Unidade da Federação' Ano    Valor Difference
       <chr>                  <chr>  <dbl>      <dbl>
     1 Rondônia               1996    1090      NA   
     2 Rondônia               1997    1296      18.9 
     3 Rondônia               1998   15790    1118.  
     4 Rondônia               1999   16100       1.96
     5 Rondônia               2000   36222     125.  
     6 Rondônia               2001   68687      89.6 
     7 Rondônia               2002   83782      22.0 
     8 Rondônia               2003  126396      50.9 
     9 Rondônia               2004  163029      29.0 
    10 Rondônia               2005  233281      43.1 
    # ... with 584 more rows