This function allows to specify additional rules to filter certain rows

setFilter(schema = NULL, rows = NULL, columns = NULL, operator = NULL)

Arguments

schema

[schema(1)]
In case this information is added to an already existing schema, provide that schema here (overwrites previous information).

rows

[integerish(.)]
rows that are mentioned here are kept.

columns

[integerish(.)]
columns that are mentioned here are kept.

operator

[function(1)]
Logic operators by which the current filter should be combined with the directly preceeding filter; hence this argument is not used in case no other filter was defined before it.

Value

An object of class schema.

See also

Other functions to describe table arrangement: setCluster(), setFormat(), setGroups(), setIDVar(), setObsVar()

Examples

(input <- tabs2shift$messy_rows)
#> # A tibble: 16 × 7
#>    X1          X2     X3          X4             X5        X6         X7       
#>    <chr>       <chr>  <chr>       <chr>          <chr>     <chr>      <chr>    
#>  1 territories period commodities other_observed harvested production empty_col
#>  2 1           -      all         xyz            999       999        NA       
#>  3 2           -      none        xyz            999       999        NA       
#>  4 NA          NA     NA          NA             NA        NA         NA       
#>  5 3           -      xyz         xyz            999       999        NA       
#>  6 4           -      5           xyz            999       999        NA       
#>  7 unit 1      year 1 soybean     xyz            1111      1112       NA       
#>  8 unit 1      year 1 maize       xyz            1121      1122       NA       
#>  9 unit 1      year 2 soybean     xyz            1211      1212       NA       
#> 10 unit 1      year 2 maize       xyz            1221      1222       NA       
#> 11 5           -      all         NA             999       999        NA       
#> 12 6           -      none        NA             999       999        NA       
#> 13 unit 2      year 1 soybean     xyz            2111      2112       NA       
#> 14 unit 2      year 1 maize       xyz            2121      2122       NA       
#> 15 unit 2      year 2 soybean     xyz            2211      2212       NA       
#> 16 unit 2      year 2 maize       xyz            2221      2222       NA       

# select rows where there is 'unit 2' in column 1 or 'year 2' in column 2
schema <-
  setFilter(rows = .find(pattern = "unit 2", col = 1)) %>%
  setFilter(rows = .find(pattern = "year 2", col = 2), operator = `|`) %>%
  setIDVar(name = "territories", columns = 1) %>%
  setIDVar(name = "year", columns = 2) %>%
  setIDVar(name = "commodities", columns = 3) %>%
  setObsVar(name = "harvested", columns = 5) %>%
  setObsVar(name = "production", columns = 6)

reorganise(schema = schema, input = input)
#> # A tibble: 6 × 5
#>   territories year   commodities harvested production
#>   <chr>       <chr>  <chr>           <dbl>      <dbl>
#> 1 unit 1      year 2 soybean          1211       1212
#> 2 unit 1      year 2 maize            1221       1222
#> 3 unit 2      year 1 soybean          2111       2112
#> 4 unit 2      year 1 maize            2121       2122
#> 5 unit 2      year 2 soybean          2211       2212
#> 6 unit 2      year 2 maize            2221       2222