knitr::opts_chunk$set(echo = TRUE, collapse = TRUE, fig.width = 7, fig.height = 4, fig.align = "center", message = FALSE, warning = FALSE)
The CRAN version can be loaded as follows:
library('mapping')
or the development version from GitHub:
remotes::install_github('serafinialessio/mapping')
The Italian geographical aggregates nomenclature are the following:
| Function argument | Aggregates | Level | ------------|------------| -------------| | "none" | country | level 0 | | "ripartizione" | Italian divisions | level 1 | | "regione" | Italian regions | level 2 | | "provincia" | Italian municipalities | level 3 | | "comune" | Italian districts | level 4 |
where level 0 is the largest unit (country), and level 4 the smallest unit.
DiagrammeR::grViz(" digraph graph2 { graph [layout = dot, rankdir = LR] # node definitions with substituted label text node [shape = oval] a [label = 'country'] b [label = 'ripartizione'] c [label = 'regione'] d [label = 'provincia'] e [label = 'comune'] e -> d -> c -> b -> a } ",height = 100)
The diagram show the hierarchy used in the IT()
to build the object to map. Smaller aggregate/levels have all the information of the bigger aggregates. For example, if we have "comune", we have also all the information until the first level, "ripartizione".
it_level0 <- loadCoordIT(unit = "none") mappingIT(it_level0)
it_level1 <- loadCoordIT(unit = "ripartizione") mappingIT(it_level1)
it_level2 <- loadCoordIT(unit = "regione") mappingIT(it_level2)
it_level3 <- loadCoordIT(unit = "provincia") mappingIT(it_level3)
it_level4 <- loadCoordIT(unit = "comune") mappingIT(it_level4)
Note that, given the government rule, the "provincia" and district may change over the year
.
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