Gesis
Introduction
The GESIS Data Catalogue offers a repository of approximately 5,000 datasets.
To install the package from github:
# install.packages("devtools")
devtools::install_github("expersso/gesis")library(gesis)A simple example
We start by listing all available groups of studies:
groups <- get_study_groups()
head(groups, 10)## group_no value
## 1 0001 International Social Survey Programme (ISSP)
## 2 0002 EB - Flash Eurobarometer
## 3 0003 Travel Surveys
## 4 0004 Time Budget Study
## 5 0005 EB - Central and Eastern Eurobarometer
## 6 0006 EB - Candidate Countries Eurobarometer
## 7 0007 ALLBUS
## 8 0008 EB - Standard and Special Eurobarometer
## 9 0009 European Values Study (EVS)
## 10 0010 Politbarometer
We see that the Eurobarometer has study group number 0008 Let's looks at all available Eurobarometer waves:
eurobars <- get_datasets("0008")
head(eurobars)## doi title
## 1 0078 Attitudes towards Europe (1962)
## 2 0626 European Communities Study 1970
## 3 0627 European Communities Study 1971
## 4 0628 European Communities Study 1973
## 5 0986 Eurobarometer 2 (Oct-Nov 1974)
## 6 0987 Eurobarometer 3 (May 1975)
We would now like to download the first three studies. We first need to log in to the Gesis website and then pass the DOIs (unique data set identifiers) to download_dataset:
# username and password stored as environment
# variables "GESIS_USER" and "GESIS_PASS"
gesis_session <- login()if(!dir.exists("downloads")) dir.create("downloads")
download_dataset(s = gesis_session, doi = eurobars$doi[1:3],
path = "downloads", filetype = ".dta")## Downloading DOI: 0078
## Downloading DOI: 0626
## Downloading DOI: 0627
(files <- list.files("downloads", full.names = TRUE))## [1] "downloads/ZA0078_v1-0-1.dta" "downloads/ZA0626_v1-0-1.dta"
## [3] "downloads/ZA0627_v1-0-1.dta"
We can also download the codebooks for the same studies:
download_codebook(eurobars$doi[1:3], path = "downloads")## Downloading codebook for DOI: 0078
## Downloading codebook for DOI: 0626
## Downloading codebook for DOI: 0627
Using the haven package we can now read the data sets:
library(haven)
df <- read_dta(files[1])
dim(df)## [1] 4774 175
Disclaimer: the gesis package is neither affiliated with, nor endorsed by, the Leibniz Institute for the Social Sciences. I have been unable to find any indication that programmatic access to the website is disallowed under its terms of use (indeed, its guidelines appear to encourage it). That said, I would discourage users from using the gesis package to put undue pressure on their servers by initiating unnecessary (or unnecessarily large) batch downloads.