cp2sc {sc2sc}

Implements the geometric spatial transfer of statistics from Spanish postal code areas to census sections

Description

Transfers the statistics available in a set of Spanish postal codes to the corresponding spatial set of Spanish official census sections into force in a given year.

Usage

cp2sc(x, year, data.type = "counts", all.units = FALSE, ...)

Arguments

x

A data frame of order N x K (with K > 1) with the statistics to be spatially transferred/imputed. The first column must contains the codes of the postal code areas to which the statistics belong to. The statistical nature of the data columns must be of the same type. See the argument ⁠data.type'. ⁠

year

An integer number. Reference year of the census sections to which the statistics are going to be transferred. Only 2001 and 2003 to 2023 are allowed.

data.type

A character string indicating the type of data to be transferred, either "counts" (aggregate statistics) or "averages" (mean, proportion or rate statistics). Default "counts".

all.units

A TRUE/FALSE value indicating the census section units of the destination division to be included in the output data frame. If TRUE all the units of the destination division are included. If FALSE only those units for which a value is imputed are included. Default, FALSE.

...

Other arguments to be passed to the function. Not currently used.

Value

A list with the following components

df

A data frame with the statistics spatially transferred to the census sections corresponding to the year.sscc.dest division.

missing

A vector with the codes of the postal code areas included in x that are not available in the shp file of postal code area division.

Note

The data that allows to transfer throughout time statistics among census sections and/or postal code areas has been own elaboration by the authors using (i) the Spanish Digital Cartography Files available in http://www.ine.es that contain the digitalisation of the georeferenced polygons of the census sections, according to UTM coordinates 28, 29, 30 and 31, and (ii) the Cartography File of postal code areas developed by Goerlich (2022).

Neither The Spanish Statistical Office (Instituto Nacional de Estadística) nor Professor Goerlich had any involvement in preparing this package. They bear no responsibility on the results derived from using this package.

Postal code areas have 2019 as reference year. It must be noted, however, that they can be considered as almost time stationary. Spanish postal code areas are quite stable over time.

Author(s)

Jose M. Pavia, [e-mail]

Virgilio Perez [e-mail]

References

Goerlich, FJ (2022). Elaboracion de un mapa de codigos postales de Espana con recursos libres. Como evitar pagar a Correos 6000 euros por informacion de referencia. Working Papers Ivie n. 2022-3. Valencia: Ivie. doi:10.12842/WPIVIE_0322

Pavia, JM and Cantarino, I (2017a). Can dasymetric mapping significantly improve population data reallocation in a dense urban area? Geographical Analysis, 49(2), 155-174. doi:10.1111/gean.12112

Pavia, JM and Cantarino, I (2017b). Dasymetric distribution of votes in a dense city. Applied Geography, 86, 22-31. doi:10.1016/j.apgeog.2017.06.021

See Also

sc2cp sc2sc

Examples

data <- structure(list(CCPP = c(1120L, 1160L, 1250L, 1212L, 1213L),
                       income = c(15000L, 12000L, 11500L,
                       13000L, 12500L)),
                  class = "data.frame", row.names = c(NA, -5L))
example <- cp2sc(x = data, year = 2014, data.type = "averages")