censo2017

Una Base de Datos de Alto Rendimiento del Censo 2017 de Chile.

https://github.com/ropensci/censo2017

Science Score: 49.0%

This score indicates how likely this project is to be science-related based on various indicators:

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CITATION.cff file
✓
codemeta.json file
Found codemeta.json file
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.zenodo.json file
Found .zenodo.json file
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DOI references
Found 4 DOI reference(s) in README
✓
Academic publication links
Links to: zenodo.org
○
Academic email domains
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Institutional organization owner
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JOSS paper metadata
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Scientific vocabulary similarity
Low similarity (12.2%) to scientific vocabulary

Keywords

censo census chile demografia demographics duckdb redatam rstats

Last synced: 6 months ago · JSON representation

Repository

Una Base de Datos de Alto Rendimiento del Censo 2017 de Chile.

Basic Info

Host: GitHub
Owner: ropensci
License: cc0-1.0
Language: R
Default Branch: main
Homepage: https://docs.ropensci.org/censo2017/
Size: 1.21 MB

Statistics

Stars: 28
Watchers: 2
Forks: 9
Open Issues: 0
Releases: 1

Topics

censo census chile demografia demographics duckdb redatam rstats

Created over 5 years ago · Last pushed over 1 year ago

Metadata Files

Readme Changelog Funding License Codemeta

README.Rmd

---
output: github_document
---



```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# Censo 2017 (Paquete R)


[![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](https://lifecycle.r-lib.org/articles/figures/lifecycle-stable.svg)](https://lifecycle.r-lib.org/articles/stages.html#stable-1)
[![Lifecycle: stable](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://www.tidyverse.org/lifecycle/#stable)
[![GH-actions](https://github.com/ropensci/censo2017/workflows/R-CMD-check/badge.svg)](https://github.com/ropensci/censo2017/actions)
[![codecov](https://codecov.io/gh/ropensci/censo2017/branch/main/graph/badge.svg?token=XI59cmGd15)](https://codecov.io/gh/ropensci/censo2017)
[![CRAN status](https://www.r-pkg.org/badges/version/censo2017)](https://CRAN.R-project.org/package=censo2017)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4277761.svg)](https://doi.org/10.5281/zenodo.4277761)
[![Buy Me a Coffee](https://img.shields.io/badge/buymeacoffee-pacha-yellow)](https://www.buymeacoffee.com/pacha?via=github)
[![Status at rOpenSci Software Peer Review](https://badges.ropensci.org/414_status.svg)](https://github.com/ropensci/software-review/issues/414)


# Acerca de

Provee un acceso conveniente a mas de 17 millones de registros de la base de datos del Censo 2017. Los datos fueron importados desde el DVD oficial del INE usando el [Convertidor REDATAM](https://github.com/discontinuos/redatam-converter/) creado por Pablo De Grande y ademas se proporcionan los mapas que acompanian a estos datos. Estos mismos datos en DVD posteriormente quedaron disponibles en las [Bases de Datos del INE](https://www.ine.cl/estadisticas/sociales/censos-de-poblacion-y-vivienda/poblacion-y-vivienda).

Despues de la primera llamada a `library(censo2017)` se le pedira al usuario que descargue la base usando `censo_descargar_base()` y se puede modificar la ruta de descarga con la variable de entorno `CENSO2017_DIR`. La variable de entorno se puede crear con `usethis::edit_r_environ()`.

La documentacion esta disponible en https://docs.ropensci.org/censo2017/.

# Publico objetivo

Estudiantes, academicos e investigadores que necesiten un acceso conveniente a datos censales directamente en R o RStudio.

# Requerimientos de instalacion

Este paquete necesita 3.5 GB libres para la crear la base de datos localmente.

# Instalacion

Version estable
```
install.packages("censo2017")
```

Version de desarrollo
```
# install.packages("remotes")
remotes::install_github("ropensci/censo2017")
```

# Valor agregado sobre los archivos SHP y REDATAM del INE

Esta version de la base de datos del Censo 2017 presenta algunas diferencias respecto de la original que se obtiene en DVD y corresponde a una version DuckDB derivada a partir de los Microdatos del Censo 2017 en formato DVD. 

La modificacion sobre los archivos originales, que incluyen geometrias detalladas disponibles en [Cartografias Censo2017](https://github.com/ropensci/censo2017-cartografias), consistio en unir todos los archivos SHP regionales en una unica tabla por nivel (e.g en lugar de proveer `R01_mapa_comunas`, ..., `R15_mapa_comunas` combine las 15 regiones en una unica tabla `mapa_comunas`).

Los cambios concretos respecto de la base original son los siguientes:

* Nombres de columna en formato "tidy" (e.g. `comuna_ref_id` en lugar de `COMUNA_REF_ID`).
* Agregue los nombres de las unidades geograficas (e.g. se incluye `nom_comuna` en la tabla `comunas` para facilitar los filtros).
* Aniadi la variable `geocodigo` a la tabla de `zonas`. Esto facilita mucho las uniones con las tablas de mapas en SQL.
* Tambien inclui las observaciones 16054 to 16060 en la variable `zonaloc_ref_id`. Esto se debio a que era necesario para crear una llave foranea desde la tabla `mapa_zonas` (ver repositorio [Cartografias Censo2017](https://github.com/ropensci/censo2017-cartografias)) y vincular el `geocodigo` (no todas las zonas del mapa estan presentes en los datos del Censo).

Ademas de los datos del Censo, inclui la descripcion de las variables en formato tabla (y no en XML como se obtiene del DVD). La ventaja de esto es poder consultar rapidamente lo que significan los codigos de variables y su etiquetado, por ejemplo:
```{r message=FALSE, warning=FALSE}
# con la bbdd instalada
library(censo2017)
library(dplyr)

censo_tabla("variables") %>% 
  filter(variable == "p01")

censo_tabla("variables_codificacion") %>% 
  filter(variable == "p01")
```

# Relacion de Censo 2017 con Chilemapas

Todos los datos de estos repositorios contemplan 15 regiones pues los archivos del Censo se entregan de esta forma y este paquete esta 100% orientado a facilitar el acceso a datos.

Por su parte, [chilemapas](https://docs.ropensci.org/censo2017) se centra unicamente en los mapas y tambien usa las cartografias del DVD del Censo para entregar mapas simplificados (de menor detalle y mas livianos). Chilemapas cuenta con una transformacion de codigos para dar cuenta de la creacion de la Region de Niuble.

En resumen, censo2017 permite construir estadisticas demograficas y chilemapas ayuda a mostrarlas en un mapa usando ggplot2 (u otro paquete como tmap).

# Cita este trabajo

Si usas `censo2017` en trabajos academicos u otro tipo de publicacion por favor usa la siguiente cita:

```
Mauricio Vargas (2020). censo2017: Base de Datos de Facil Acceso del Censo
  2017 de Chile (2017 Chilean Census Easy Access Database). R package version
  0.1. https://docs.ropensci.org/censo2017/
```

Entrada para BibTeX:

```
@Manual{,
  title = {censo2017: Base de Datos de F\'acil Acceso del Censo 2017 de Chile
(2017 Chilean Census Easy Access Database)},
  author = {Mauricio Vargas},
  year = {2020},
  note = {R package version 0.1},
  url = {https://docs.ropensci.org/censo2017/},
  doi = {10.5281/zenodo.4277761}
}
```

# Contribuciones

Para contribuir a este proyecto debes estar de acuerdo con el [Codigo de Conducta de rOpenSci](https://ropensci.org/code-of-conduct/). Me es util contar con mas ejemplos, mejoras a las funciones y todo lo que ayude a la comunidad. Si tienes algo que aportar me puedes dejar un issue o pull request.

# Agradecimientos

Muchas gracias a Juan Correa por su asesoria como geografo experto.

# Aportes

Si quieres donar para aportar al desarrollo de este y mas paquetes Open Source, puedes hacerlo en [Buy Me a Coffee](https://www.buymeacoffee.com/pacha/).

Owner

Name: rOpenSci
Login: ropensci
Kind: organization
Email: info@ropensci.org
Location: Berkeley, CA

Website: https://ropensci.org/
Twitter: rOpenSci
Repositories: 307
Profile: https://github.com/ropensci

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