This function extracts data from a table that are summarised by applying a schema description to it.
getData(schema = NULL, input = NULL)a table where columns and rows are summarised
input <- tabs2shift$clusters_nested
schema <- setCluster(id = "sublevel",
group = "territories", member = c(1, 1, 2),
left = 1, top = c(3, 8, 15)) %>%
setIDVar(name = "territories", columns = 1, rows = c(2, 14)) %>%
setIDVar(name = "sublevel", columns = 1, rows = c(3, 8, 15)) %>%
setIDVar(name = "year", columns = 7) %>%
setIDVar(name = "commodities", columns = 2) %>%
setObsVar(name = "harvested", columns = 5) %>%
setObsVar(name = "production", columns = 6)
validateSchema(schema = schema, input = input) %>%
getData(input = input)
#> # A tibble: 19 × 8
#> X1 X2 X3 X4 X5 X6 X7 X8
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 territory commodities NA other_observed harvested production year empty…
#> 2 group 1 NA NA NA NA NA NA NA
#> 3 unit 1 NA NA NA NA NA NA NA
#> 4 NA soybean NA xyz 1111 1112 year 1 NA
#> 5 NA maize NA xyz 1121 1122 year 1 NA
#> 6 NA soybean NA xyz 1211 1212 year 2 NA
#> 7 NA maize NA xyz 1221 1222 year 2 NA
#> 8 unit 2 NA NA NA NA NA NA NA
#> 9 NA soybean NA xyz 2111 2112 year 1 NA
#> 10 NA maize NA xyz 2121 2122 year 1 NA
#> 11 NA soybean NA xyz 2211 2212 year 2 NA
#> 12 NA maize NA xyz 2221 2222 year 2 NA
#> 13 NA NA NA NA NA NA NA NA
#> 14 group 2 NA NA NA NA NA NA NA
#> 15 unit 3 NA NA NA NA NA NA NA
#> 16 NA soybean NA xyz 3111 3112 year 1 NA
#> 17 NA maize NA xyz 3121 3122 year 1 NA
#> 18 NA soybean NA xyz 3211 3212 year 2 NA
#> 19 NA maize NA xyz 3221 3222 year 2 NA