Package: vizsurvey 0.4.3

Thomas Delclite

vizsurvey: Visualisation And Analysis During a Survey Field

vizsurvey is an R package designed to streamline the quality assessment of survey data by providing intuitive visual diagnostics through an interactive dashboard. vizsurvey is especially useful for institutions or researchers conducting large-scale surveys with multiple interviewers, enabling a fast and systematic overview of data quality over time.

Authors:Thomas Delclite [aut, cre], Adrien Mierop [aut]

vizsurvey_0.4.3.tar.gz
vizsurvey_0.4.3.zip(r-4.7-any)vizsurvey_0.4.3.zip(r-4.6-any)vizsurvey_0.4.3.zip(r-4.5-any)
vizsurvey_0.4.3.tgz(r-4.6-any)vizsurvey_0.4.3.tgz(r-4.5-any)
vizsurvey_0.4.3.tar.gz(r-4.7-any)vizsurvey_0.4.3.tar.gz(r-4.6-any)
vizsurvey_0.4.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
vizsurvey/json (API)

# Install 'vizsurvey' in R:
install.packages('vizsurvey', repos = c('https://tdelc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/tdelc/vizsurvey/issues

Pkgdown/docs site:https://tdelc.github.io

On CRAN:

Conda:

4.18 score 1 stars 6 scripts 33 exports 81 dependencies

Last updated from:8e4424f32a. Checks:7 ERROR, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develERROR163
source / vignettesOK208
linux-releaseERROR162
macos-releaseERROR165
macos-oldrelERROR162
windows-develERROR101
windows-releaseERROR107
windows-oldrelERROR116
wasm-releaseOK130

Exports:build_df_timer_intvwrclassify_dfcombine_varscreate_configcreate_eusilc_simcreate_fake_silccut_safedescribe_variabledescribe_variable_dtempty_as_nafind_timer_rdsfolder_to_dfgroup_vs_othersheatmap_groupindex_homogeneityis.integer64key_level1key_level2keys_varslist_distlist_dist_dtmatch_keysmy_chisq_testprepa_statsprepa_stats_dtprepa_surveyprepa_surveysrunVizsurveyrunVizsurvey_from_folderrunVizsurvey_from_rscale_IQRscore_isoforestvars_levels

Dependencies:askpassbase64encbootbsiconsbslibcachemclicommonmarkcpp11crosstalkcurldata.tabledigestdplyrDTevaluatefarverfastmapfontawesomefsgenericsggplot2gluegtablehighrhtmltoolshtmlwidgetshttpuvhttrisobandisotreejquerylibjsonliteknitrlabelinglaekenlaterlazyevallifecyclelubridatemagrittrMASSmemoisemimeopensslotelpillarpkgconfigplotlypromisespurrrR6rappdirsRColorBrewerRcppRhpcBLASctlrlangrmarkdownrstudioapiS7sassscalesshinyshiny.i18nshinybusysourcetoolsstringistringrsystibbletidyrtidyselecttimechangetinytexutf8vctrsviridisLitewithrxfunxtableyaml

Preparing the data
Introduction | Example data | Configuring a survey | Survey configuration file | Two levels for the wave or the filter | Optional: interviewer summary file | Preparing the survey | Simple structure: a single directory | Double structure: several directories | Triple structure: several directory levels | Conclusion
Rendered fromdata-preparation.Rmdusingknitr::rmarkdown

Last update: 2026-08-10
Started: 2025-11-01

Methodology and use of the functions
Introduction | classify_df(): classify the variables | prepa_stats(): extract the aggregates | Description of the output | Computing the $\chi^2$ | Standardising the indicators | heatmap_group(): customise the visualisation | score_isoforest(): rank the atypical profiles | Conclusion
Rendered frommethods.Rmdusingknitr::rmarkdown

Last update: 2026-06-24
Started: 2025-11-03

Step-by-step guide to explore and detect anomalies
Introduction | Why vizsurvey? | Interviewer consistency | Survey wave consistency | Launching vizsurvey | From an R object | Optional: an interviewer summary file | From a directory of databases | Interviewer consistency analysis | Example data | Reading the heatmap | Analysing a categorical variable | Analysing a continuous variable | Anomaly summary | Summary: step-by-step analysis | Survey wave consistency analysis | Analysing changes in variables | Graphical analysis | Conclusion
Rendered fromvizsurvey.Rmdusingknitr::rmarkdown

Last update: 2026-06-24
Started: 2025-11-01

Readme and manuals

Help Manual

Help pageTopics
Build the df_timer of interviewerbuild_df_timer_intvwr
Classify all variable of a data.frameclassify_df
Combine several variables in one key (multi-level wave or filter)combine_vars
corrections of each df of a listcorrect_list_df
Create a template of configuration filecreate_config
Create statistics from databasecreate_df_stats
Simulate EU-SILC dataset with injected errorscreate_eusilc_sim
Use PUF files for SILC examplecreate_fake_silc
Cut a continuous variable in n categories.cut_safe
Description d'une variable, globale ou par groupedescribe_variable
Description d'une variable rendue en DTdescribe_variable_dt
Replace empty by naempty_as_na
extract a config from key (config from load_config)extract_config
Extract timer rds files from folderfind_timer_rds
tranform data from folder to config and dffolder_to_df
Vecteur de groupe "VAR = valeur" / "VAR != valeur" pour les comparaisonsgroup_vs_others
Create a heatmapheatmap_group
index_homogeneityindex_homogeneity
Check if value is integer64is.integer64
First level of a multi-level keykey_level1
Other levels of a multi-level key (used as label in the interface)key_level2
Keys (modalities) of a wave or filter variablekeys_vars
List distribution of discrete variableslist_dist
List of proportions for categorical variableslist_dist_dt
load a config file for prepare dataload_config
Loop of stats creation by filterloop_stats
Rows of a data.frame matching one or several keysmatch_keys
Specific chisq test to NA and Other modalitymy_chisq_test
Create a summarise of all the differenceprepa_stats
prepa_stats_dtprepa_stats_dt
Preparation of a surveyprepa_survey
Preparation of all surveys from a folderprepa_surveys
Shiny vizsurveyrunVizsurvey
Shiny vizsurvey with already prepared datarunVizsurvey_from_folder
Shiny vizsurvey from a R data.framerunVizsurvey_from_r
Robust Scale of a varible with IQRscale_IQR
calculate isoforest score from dfscore_isoforest
Variables of each level of the wave or of the filtervars_levels