An RStudio addin that wraps access to UNHCR data behind a uniform interface.
It can be installed from github with devtools::install_github("UNHCR-WEB/hcrdata").
Currently supported data sources:
- kobo:UNHCR corporate server for survey data collection based on Kobotoolbox: http://kobo.unhcr.org
- ridl: Raw Internal Data Library, UNHCR internal instance of CKAN data portal for data documentation: http://ridl.unhcr.org
- mdl: Microdata Library, UNHCR instance of NADA for the publication of anonymized microdata: http://microdata.unhcr.org
With more to come (popstats, rsq, etc...).
Using API calls in your analysis scripts can be quite convenient in multiple situations:
-
During data collection, it is important to perform High frequency Check in order to monitor the quality of the data collection process. Using the API call, you can further automate those checks;
-
Once the survey is completed in KoboToolbox, data shall be extracted and then documented and uploaded in RIDL. Performing those tasks through scripts can be a lot quicker, specifically when a dataset with similar metadata shall be split between different data containers;
-
When writing an analytic piece with Rmd, being able to include in the Rmd the exact location of the RIDL data container or Microdata catalog allows to increase reproducibility.
The package expects to find your API keys / access credentials in environment variables. The easiest way to get them there and persist your settings is to store them in your .Renviron file which is automatically read by R on startup.
You can retrieve your API key for UNHCR kobo server in the account setting page and in RIDL in your own user page.
You can either edit directly the .Renviron file or access it by calling usethis::edit_r_environ() (assuming you have the usethis package installed) and entering:
KOBO_API_KEY=xxxxxxxxx
RIDL_API_KEY=xxxxxxxxx
MDL_ACCESS_CREDS=user:password
Once that's done, restart your R session to make sure that the variables are loaded.
Then open a new R script within a new RStudio project.
You should then be able to launch the "data browser" within Rstudio addins menu:
- select the source
- go to the dataset tab and select the project you want to pull data from
- go to the files tab and select the specific file you want to retrieve from the project.
- press the load data button and the R statement to pull this file from your project will be automatically inserted in your blank R script tab
Note that data pulled live from Kobo server (rather than exported to csv or excel at point in time) is served as json file. In order to get transformed to a more convenient data frame, you can use the following script:
data <-
hcrdata::hcrfetch(
src = "kobo",
dataset = "My kobo project",
file = "data.json") %>%
jsonlite::fromJSON() %>%
purrr::pluck("results") %>%
tibble::as_tibble() %>%
purrr::set_names(~stringr::str_replace_all(., "(\\/)", "."))This package is part of
unhcrverse, a set of packages to ease the production of statistical evidence and data stories. You can install them all with the following:
## Use UNHCR Open data - https://unhcr.github.io/unhcrdatapackage/docs/
remotes::install_github('unhcr/unhcrdatapackage’)
## API to connect to internal data source - https://unhcr-web.github.io/hcrdata/docs/
remotes::install_github('unhcr-web/hcrdata’)
## Perform High Frequency Check https://unhcr.github.io/HighFrequencyChecks/docs/
remotes::install_github('unhcr-web/HighFrequencyChecks’)
## Process data crunching for survey dataset - https://unhcr.github.io/koboloadeR/docs/
remotes::install_github('unhcr/koboloadeR’)
## Use UNHCR graphical template- https://unhcr-web.github.io/unhcRstyle/docs/
remotes::install_github('unhcr-web/unhcRstyle')