robotoolbox
is an R client to access data from KoboToolbox.
Installation
This package is not on yet on CRAN and to install it, you will need the remotes
package. You can get robotoolbox
from Gitlab or Github (mirror)
## install.packages("remotes")
remotes::install_gitlab("dickoa/robotoolbox")
robotoolbox: A quick tutorial
The robotoolbox
package is a client to KoboToolbox API v2
. You will need to set your API token and specify the KoboToolbox
server URL. The easiest way to set up robotoolbox
is to store the token and the url in your .Renviron
which is automatically read by R
on startup.
Getting the API token
You can retrieve your API token
following the instruction in the official API documentation: https://support.kobotoolbox.org/api.html.
You can also get your token directly from R
using the kobo_token
function.
kobo_token(username = "xxxxxxxxx",
password = "xxxxxxxxx",
url = "https://kobo.unhcr.org")
Setup your session
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 the following two lines:
KOBOTOOLBOX_URL="https://kobo.unhcr.org/"
KOBOTOOLBOX_TOKEN=xxxxxxxxxxxxxxxxxxxxxxxxxx
Or use directly the kobo_setup
function
kobo_setup(url = "https://kobo.unhcr.org",
token = "xxxxxxxxxxxxxxxxxxxxxxxxxx")
Settings can be checked using kobo_settings
function.
library("robotoolbox")
kobo_settings()
## <robotoolbox settings>
## KoboToolbox URL: https://kobo.unhcr.org/
## KoboToolbox API Token: xxxxxxxxxxxxxxxxxxxxxxxxxx
With the settings done, it is possible to list all assets
(e.g form, project, etc) for the account associated to the token and url supplied.
Access data
library("dplyr")
<- kobo_asset_list()
l
l# A tibble: 24 x 7
uid name asset_type owner_username date_created<chr> <chr> <chr> <chr> <dttm>
1 b9kgvd… Proj_A1… survey xxxxxxxxxxxxx… 2020-04-27 20:34:23
2 aRFJMp… Proj_A2… survey xxxxxxxxxxxxx… 2020-04-27 21:21:12
3 a6qMG7… Proj_A3… survey xxxxxxxxxxxxx… 2021-05-25 16:59:08
4 azhrVs… Proj_A4… survey xxxxxxxxxxxxx… 2021-05-25 13:59:46
5 aReR58… Proj_A5… survey xxxxxxxxxxxxx… 2021-06-07 09:15:53
6 aWaoqy… Proj_A6… survey xxxxxxxxxxxxx… 2021-05-29 10:46:09
7 aABU3C… Proj_A7… survey xxxxxxxxxxxxx… 2020-11-28 15:00:10
8 aaznyX… Proj_A9… survey xxxxxxxxxxxxx… 2020-11-28 14:28:48
9 aCVr2Q… Proj_A9… survey xxxxxxxxxxxxx… 2021-05-25 13:30:24
10 aPxNao… Proj_A10… survey xxxxxxxxxxxxx… 2020-04-27 11:37:34
# … with 14 more rows, and 3 more variables:
# date_modified <dttm>, submissions <int>
glimpse(l)
$ uid <chr> "b9kgvd7AXQCmo5qyUOBEl", "aRfJMpTSGRLzZ…"
$ name <chr> "Proj_A1", "Proj_A2", "Proj_A3", "Proj_A…"
$ asset_type <chr> "survey", "survey", "survey", "survey", …
$ owner_username <chr> "xxxxxxxxxxxxxx", "xxxxxxxxxxxxxxx", "xx…"
$ date_created <dttm> 2020-04-27 20:34:23, 2020-04-27 21:21:1…
$ date_modified <dttm> 2021-06-17 01:52:57, 2021-06-17 01:52:5…
$ submissions <int> 2951, 2679, 2, 1, 0, 0, 287, 73, 0, 274,…
The list of assets
is a tibble
, you can filter it to select the form uuid
that uniquely identify the project you want to open. The function kobo_asset
can then be used to get the asset
from the uuid
.
uid <- l |>
filter(name == "proj_A1") |>
pull(uid) |>
first()
uid
## b9agvd9AXQCmo5qyUOBEl
asset <- kobo_asset(uid)
asset
## <robotoolbox asset> b9agvd9AXQCmo5qyUOBEl
## Asset Name: proj_A1
## Asset Type: survey
## Created: 2021-05-10 07:47:53
## Last modified: 2021-08-16 12:35:50
## Submissions: 941
Now with the selected asset
, we can extract the submissions
using the kobo_submissions
function. The kobo_data
can also be used instead, it’s an alias of kobo_submissions
.
df <- kobo_submissions(asset) ## or df <- kobo_data(asset)
glimpse(df)
## Rows: 941
## Columns: 17
## $ id <int> …
## $ start <dttm> …
## $ end <dttm> …
## $ today <date> …
## $ deviceid <chr> …
## $ test <chr+lbl> …
## $ round <date> …
## $ effective_date <date> …
## $ collect_type <chr+lbl> …
## $ covid_module <chr+lbl> …
## $ country <chr+lbl> …
## $ interviewer_id <chr> …
## $ respondent_is_major <chr+lbl> …
## $ consent <chr+lbl> …
## $ admin_level_1 <chr+lbl> …
## $ admin_level_2 <chr+lbl> …
## $ admin_level_3 <chr+lbl> …
Languages
robotoolbox
uses the R package labelled
to provide tools to manipulate variable labels and value labels. You can learn more about this here:
https://dickoa.gitlab.io/robotoolbox/articles/language-labelled.html
Repeating groups
Repeating groups associate multiple records to a single record in the main
table. It’s used to group questions that need to be answered repeatedly. The package dm
is used to model such relationship and allow you to safely query and join such linked data for your analysis.
https://dickoa.gitlab.io/robotoolbox/articles/repeat-group-data.html
Caveats and limitations
robotoolbox
uses the labelled
package to manipulate labels
for select_one
question. For select_multiple
questions, dummy columns are used. They are based on values not labels. Please feel free to submit an issue, if you want to have labels
for select_multiple
.
robotoolbox
uses the Kobotoolbox
API v2. Using the API, if you don’t own the project, it is not currently possible to access all versions of the form used to collect the data. You can just access the latest version of the form. It has an impact on how robotoolbox
can map the raw data and the information from the associated form (labels, languages, etc.).
Meta
- Please report any issues or bugs.
- License: MIT
- Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.