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hmeleiro committed Nov 17, 2023
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.RData
.Ruserdata
docs
inst/doc
4 changes: 4 additions & 0 deletions DESCRIPTION
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Expand Up @@ -22,3 +22,7 @@ Imports:
rlang (>= 1.1.1),
haven (>= 2.5.3)
URL: https://hmeleiro.github.io/opencis/
Suggests:
knitr,
rmarkdown
VignetteBuilder: knitr
2 changes: 0 additions & 2 deletions R/internal.R
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Expand Up @@ -52,8 +52,6 @@ parse_response_series <- function(res) {
response_metadata_categories <- response_categories[i]
response_categories <- gsub(" $|^ ", "", response_categories[-i])

x <- res_content$ficha$serie_temporal[[1]]

question_data <- map_df(res_content$ficha$serie_temporal, function(x) {
response_values <- unlist(x$datos)
response_values <- as.numeric(gsub("[()]", "", response_values))
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174 changes: 173 additions & 1 deletion README.md
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<!-- badges: start -->
[![CRAN status](https://www.r-pkg.org/badges/version/opencis)](https://CRAN.R-project.org/package=opencis)
[![R-CMD-check](https://github.com/hmeleiro/opencis/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/hmeleiro/opencis/actions/workflows/R-CMD-check.yaml)
[![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)
<!-- badges: end -->

Search and import data directly to R from the Spanish Sociological Research Center (CIS). The CIS is a public institution that conducts electoral and sociological research studies on the Spanish society. The CIS has a large database of surveys that can be accessed through its website. The package includes functions to search for surveys, survey questions and timeseries, and import the data directly to R.

## Installation

You can install `opencis` using the `devtools` package:
You can install `opencis` from Github using the `devtools` package:

``` r
devtools::install_github("hmeleiro/opencis")
```


## Usage

The package includes three group of functions.

The first group is used to search for surveys, survey questions and timeseries.

``` r
# Search for survey studies
search_studies(search_terms = "preelectoral",
since_date = "01-01-2020",
until_date = "17-11-2023")
#> # A tibble: 456 × 4
#> id codigo titulo fecha
#> <int> <chr> <chr> <date>
#> 1 14724 3411 PREELECTORAL ELECCIONES GENERALES 2023 2023-06-08
#> 2 14718 3402 PREELECTORAL ELECCIONES MUNICIPALES Y AUTONÓMICAS… 2023-04-10
#> 3 14629 3365 PREELECTORAL ELECCIONES AUTONÓMICAS 2022. COMUNID… 2022-05-17
#> 4 14605 3348 PREELECTORAL ELECCIONES AUTONÓMICAS 2022. COMUNID… 2022-01-07
#> 5 14558 3317 PREELECTORAL ELECCIONES AUTONÓMICAS 2021. COMUNID… 2021-03-19
#> 6 14541 3306 PREELECTORAL DE CATALUÑA. ELECCIONES AUTONÓMICAS … 2021-01-02
#> 7 14513 3286 PREELECTORAL DEL PAÍS VASCO. ELECCIONES AUTONÓMIC… 2020-06-10
#> 8 14514 3287 PREELECTORAL DE GALICIA. ELECCIONES AUTONÓMICAS J… 2020-06-10
#> 9 14491 3275 PREELECTORAL DEL PAÍS VASCO. ELECCIONES AUTONÓMIC… 2020-02-17
#> 10 14492 3276 PREELECTORAL DE GALICIA. ELECCIONES AUTONÓMICAS A… 2020-02-17
#> # ℹ 446 more rows
#> # ℹ Use `print(n = ...)` to see more rows


# Search for survey questions
search_questions(search_terms = "feminismo")
#> # A tibble: 6 × 7
#> id id_estudio codigo titulo fecha_estudio titulo_cuestionario series
#> <int> <int> <chr> <chr> <date> <chr> <list>
#> 1 491141 10002 2828/0 0… Rasgo… 2010-01-09 BARÓMETRO DE ENERO… <NULL>
#> 2 485492 1384 2401/0 0… Rasgo… 2000-12-09 25 AÑOS DESPUÉS <NULL>
#> 3 493678 1202 2212/0 0… Senti… 1996-04-13 BARÓMETRO DE ABRIL… <NULL>
#> 4 479219 1144 2154/0 0… Rasgo… 1995-04-04 CULTURA POLÍTICA (… <NULL>
#> 5 449988 1008 2016/0 0… Rasgo… 1992-07-09 BARÓMETRO DE JULIO… <NULL>
#> 6 452793 985 1993/0 0… Senti… 1992-02-27 BARÓMETRO DE FEBRE… <NULL>

# Search for timeseries
search_series(search_terms = "situación económica")
#> # A tibble: 85 × 6
#> id variable titulo puntos fecha_minima fecha_maxima
#> <int> <chr> <chr> <int> <chr> <chr>
#> 1 2092 K.1.02.02.002 VALORACIÓN RETROSPECTIVA … 223 10-1978 03-2020
#> 2 2295 K.1.02.01.003 VALORACIÓN DE LA SITUACIÓ… 21 05-1986 10-2019
#> 3 2460 K.1.03.02.001 VALORACIÓN PROSPECTIVA DE… 106 04-1995 03-2020
#> 4 2462 K.1.03.02.003 VALORACIÓN PROSPECTIVA DE… 10 12-1986 02-1999
#> 5 2463 K.1.03.02.004 VALORACIÓN RETROSPECTIVA … 15 04-1992 01-2011
#> 6 2464 K.1.03.01.001 VALORACIÓN DE LA SITUACIÓ… 118 04-1992 03-2020
#> 7 2467 K.1.03.02.005 VALORACIÓN RETROSPECTIVA … 11 02-1992 02-1999
#> 8 2469 K.1.03.02.008 VALORACIÓN PROSPECTIVA DE… 6 05-2001 11-2017
#> 9 3075 K.1.02.01.001 VALORACIÓN DE LA SITUACIÓ… 364 06-1979 03-2020
#> 10 3076 K.1.02.02.001 VALORACIÓN PROSPECTIVA DE… 344 10-1978 03-2020
#> # ℹ 75 more rows
#> # ℹ Use `print(n = ...)` to see more rows
```

The second group of functions retrieves the valid category codes to narrow search queries. [Read the documentation](https://hmeleiro.github.io/opencis/reference/index.html#retrieve-categories) to understand how to use the category codes in the search functions.

``` r
get_study_categories()
#> # A tibble: 213 × 4
#> id conteo codigo titulo
#> <int> <int> <chr> <chr>
#> 1 1 1356 001 POLÍTICA
#> 2 1 24 001_000 Política
#> 3 2 222 001_001 Estado, Constitución e instituciones
#> 4 2 94 001_001_000 Estado, constitución e instituciones
#> 5 210 56 001_001_001 Constitución
#> 6 4 29 001_001_002 Fuerzas Armadas y defensa
#> 7 3 66 001_001_003 Gobierno
#> 8 551 22 001_001_004 Monarquía
#> 9 5 197 001_002 Administración y servicios públicos
#> 10 6 301 001_003 Cultura política
#> # ℹ 203 more rows
#> # ℹ Use `print(n = ...)` to see more rows

get_question_categories()
#> # A tibble: 5,257 × 4
#> id conteo codigo titulo
#> <int> <int> <chr> <chr>
#> 1 1637 154084 003 DESCRIPTORES
#> 2 1 1699 003_001 Ciencia
#> 3 1 92 003_001_000 Ciencia
#> 4 2 16 003_001_001 Ciencia espacial
#> 5 3 117 003_001_002 Desarrollo científico
#> 6 4 599 003_001_003 Investigación científica
#> 7 4 122 003_001_003_000 Investigación científica
#> 8 5 402 003_001_003_001 Métodos de investigación
#> 9 6 402 003_001_003_001_001 Encuestas
#> 10 7 23 003_001_003_001_002 Trabajo de campo
#> # ℹ 5,247 more rows
#> # ℹ Use `print(n = ...)` to see more rows

get_series_category()
#> # A tibble: 4,433 × 6
#> dmid conteo dmvariable dmtitulo dmprquestion dmindex
#> <int> <int> <chr> <chr> <chr> <chr>
#> 1 235 1190 A ESTADO, SISTEMA POLÍTICO "" 001
#> 2 221 92 A.1 CONSTITUCIÓN E INSTITUCIONES "" 001_001
#> 3 222 24 A.1.01 CONSTITUCIÓN "" 001_00…
#> 4 223 6 A.1.01.01 CONOCIMIENTO DE LA CONSTITUCIÓN "" 001_00…
#> 5 2535 1 A.1.01.01.001 GRADO DE CONOCIMIENTO DE LA CO… "<p style=\… 001_00…
#> 6 2977 1 A.1.01.01.002 GRADO DE CONOCIMIENTO DE LA CO… "<p style=\… 001_00…
#> 7 2978 1 A.1.01.01.004 GRADO DE ESFUERZO DE LOS GOBIE… "<p style=\… 001_00…
#> 8 16109 1 A.1.01.01.009 ACUERDO CON DISTINTOS MEDIOS D… "<p style=\… 001_00…
#> 9 16110 1 A.1.01.01.010 ACUERDO CON DISTINTOS MEDIOS D… "<p style=\… 001_00…
#> 10 16112 1 A.1.01.01.011 ACUERDO CON DISTINTOS MEDIOS D… "<p style=\… 001_00…
#> # ℹ 4,423 more rows
#> # ℹ Use `print(n = ...)` to see more rows

```


The third group of functions are used to import the data directly into R.

``` r
# Read a survey study
df <- read_cis("3411")
#> probando la URL 'https://www.cis.es/documents/d/cis/MD3411'
#> Content type 'application/zip' length 14194752 bytes (13.5 MB)
#> downloaded 13.5 MB
print(df)
#> Invalid date string (length=9): 11 042 23
#> # A tibble: 29,201 × 216
#> ESTUDIO REGISTRO CUES CCAA PROV MUN CAPITAL TAMUNI ENTREV
#> <dbl+lbl> <dbl> <dbl> <dbl+lbl> <dbl+l> <dbl+l> <dbl+l> <dbl+l> <dbl+l>
#> 1 3411 [3411] 492777 29043 1 [Andalucí… 4 [Alm… 0 [Mun… 3 [Otr… 1 [Men… 0 [Ano…
#> 2 3411 [3411] 70655 5848 1 [Andalucí… 4 [Alm… 0 [Mun… 3 [Otr… 1 [Men… 0 [Ano…
#> 3 3411 [3411] 46423 3893 1 [Andalucí… 4 [Alm… 0 [Mun… 3 [Otr… 3 [10.… 0 [Ano…
#> 4 3411 [3411] 103464 8711 1 [Andalucí… 4 [Alm… 0 [Mun… 3 [Otr… 3 [10.… 0 [Ano…
#> 5 3411 [3411] 112810 9517 1 [Andalucí… 4 [Alm… 0 [Mun… 3 [Otr… 3 [10.… 0 [Ano…
#> 6 3411 [3411] 126567 10736 1 [Andalucí… 4 [Alm… 0 [Mun… 3 [Otr… 3 [10.… 0 [Ano…
#> 7 3411 [3411] 137692 11573 1 [Andalucí… 4 [Alm… 0 [Mun… 3 [Otr… 3 [10.… 0 [Ano…
#> 8 3411 [3411] 182178 14839 1 [Andalucí… 4 [Alm… 0 [Mun… 3 [Otr… 3 [10.… 0 [Ano…
#> 9 3411 [3411] 216764 16793 1 [Andalucí… 4 [Alm… 0 [Mun… 3 [Otr… 3 [10.… 0 [Ano…
#> 10 3411 [3411] 237655 17918 1 [Andalucí… 4 [Alm… 0 [Mun… 3 [Otr… 3 [10.… 0 [Ano…
#> # ℹ 29,191 more rows
#> # ℹ 207 more variables: TIPO_TEL <dbl+lbl>, SEXO <dbl+lbl>, EDAD <dbl+lbl>,
#> # P0A <dbl+lbl>, ECOPER <dbl+lbl>, ECOESP <dbl+lbl>, MEDIO_1 <dbl+lbl>,
#> # MEDIO_2 <dbl+lbl>, LEEPRENSA <dbl+lbl>, VETELE <dbl+lbl>, OYERADIO <dbl+lbl>,
#> # PRENSA <dbl+lbl>, P3AR <dbl+lbl>, TELEVISION <dbl+lbl>, P3BR <dbl+lbl>,
#> # RADIO <dbl+lbl>, P3CR <dbl+lbl>, GESTIONGOB <dbl+lbl>, GESTIONOPO <dbl+lbl>,
#> # PROBVOTO <dbl+lbl>, VOTOCORREO <dbl+lbl>, PROBPARTIDOS_1 <dbl+lbl>, …
#> # ℹ Use `print(n = ...)` to see more rows, and `colnames()` to see all variable names

# Read a timeseries
df_series <- read_series("2092")
print(df_series)
#> # A tibble: 1,115 × 16
#> id codigo_serie titulo pregunta muestra notas multiVariable estudio fecha
#> <int> <chr> <chr> <chr> <chr> <chr> <lgl> <chr> <chr>
#> 1 2092 K.1.02.02.002 VALORAC… "<p sty… Nacion… "" FALSE 1169/1 10-1…
#> 2 2092 K.1.02.02.002 VALORAC… "<p sty… Nacion… "" FALSE 1169/1 10-1…
#> 3 2092 K.1.02.02.002 VALORAC… "<p sty… Nacion… "" FALSE 1169/1 10-1…
#> 4 2092 K.1.02.02.002 VALORAC… "<p sty… Nacion… "" FALSE 1169/1 10-1…
#> 5 2092 K.1.02.02.002 VALORAC… "<p sty… Nacion… "" FALSE 1169/1 10-1…
#> 6 2092 K.1.02.02.002 VALORAC… "<p sty… Nacion… "" FALSE 1189/0 06-1…
#> 7 2092 K.1.02.02.002 VALORAC… "<p sty… Nacion… "" FALSE 1189/0 06-1…
#> 8 2092 K.1.02.02.002 VALORAC… "<p sty… Nacion… "" FALSE 1189/0 06-1…
#> 9 2092 K.1.02.02.002 VALORAC… "<p sty… Nacion… "" FALSE 1189/0 06-1…
#> 10 2092 K.1.02.02.002 VALORAC… "<p sty… Nacion… "" FALSE 1189/0 06-1…
#> # ℹ 1,105 more rows
#> # ℹ 7 more variables: codigo_variable <chr>, idEstudio <chr>, idPregunta <chr>,
#> # idVariable <chr>, response_categories <chr>, response_values <dbl>,
#> # X.N. <dbl>
#> # ℹ Use `print(n = ...)` to see more rows
```
29 changes: 28 additions & 1 deletion _pkgdown.yml
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url: https://hmeleiro.github.io/opencis/
url: https://hmeleiro.github.io/opencis
template:
package: preferably
bootstrap: 5
lang: en
navbar:
structure:
left: [intro, reference, articles]
right: [github, twitter, search]
components:
github:
icon: fa-github
href: https://github.com/hmeleiro/opencis
aria-label: Github
twitter:
icon: fa-twitter
href: http://twitter.com/hmeleiros
aria-label: Twitter
repo:
url:
home: https://github.com/hmeleiro/opencis
issue: https://github.com/hmeleiro/opencis/issues
user: https://github.com/hmeleiro

home:
links:
- text: Report a bug
href: https://github.com/hmeleiro/opencis/issues
sidebar:
structure: [links, license, authors, citation, dev]

reference:
- title: Import data
desc: Functions to import data from the CIS archive.
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*.html
*.R
68 changes: 68 additions & 0 deletions vignettes/usage.Rmd
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---
title: "How to use opencis"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{How to use opencis}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
```

## Installation

You can install `opencis` from Github using the `devtools` package:

``` {r, eval=FALSE}
devtools::install_github("hmeleiro/opencis")
```


## Usage

The package includes three group of functions.

The first group is used to search for surveys, survey questions and timeseries.

``` {r}
library(opencis)
# Search for survey studies
search_studies(search_terms = "preelectoral", since_date = "01-01-2020", until_date = "17-11-2023")
# Search for survey questions
search_questions(search_terms = "feminismo")
# Search for timeseries
search_series(search_terms = "situación económica")
```

The second group of functions retrieves the valid category codes to narrow search queries. [Read the documentation](https://hmeleiro.github.io/opencis/reference/index.html#retrieve-categories) to understand how to use the category codes in the search functions.

``` {r}
get_study_categories()
get_question_categories()
get_series_category()
```


The third group of functions are used to import the data directly into R.

```{undefined warning=FALSE}
# Read a survey study
df <- read_cis("3411")
print(df)
# Read a timeseries
df_series <- read_series("2092")
print(df_series)
```

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