Tools for Analysing and Visualising Viva Insights Data
Overview
Opinionated functions that enable easier and faster analysis of Viva Insights data. There are three main types of functions in 'wpa': (i) Standard functions create a 'ggplot' visual or a summary table based on a specific Viva Insights metric; (2) Report Generation functions generate HTML reports on a specific analysis area, e.g. Collaboration; (3) Other miscellaneous functions cover more specific applications (e.g. Subject Line text mining) of Viva Insights data. This package adheres to 'tidyverse' principles and works well with the pipe syntax. 'wpa' is built with the beginner-to-intermediate R users in mind, and is optimised for simplicity.
- Minor update to globals to support dplyr update.
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-04
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- ERROR12 OK, 1 ERROR2026-06-08
- WARNING12 OK, 1 WARNING2026-06-07
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- OK14 OK2026-03-10
Documentation
- Help pages
- 178 (1 internal)
- Examples that run
- 87%110 run in a plain check · 16 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 75%
- Documented parameters
- 98%
- Return-value docs
- 95%
- Help pages citing references
- 1%
Downloads
Repository
- PRs merged (all time)
- 97%
- Median days to close, 50 most recently updated closed issues
- 61
- Median days to close, 50 most recently updated closed PRs
- 4
Stars over time
Forks over time
PRs over time
Commits over time
Commit identities over time
14 development-tooling and community-health practices detected across 6 families in the upstream repository
Checks run against github.com/microsoft/wpa on 2026-10-22.
The R CMD check workflow runs on macOS
GitHub Pages site last deployed 2026-10-11 · The repository has a site deploy workflow
pkgdown site last built 2026-10-11
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This repository shows signs of AI coding tools.
- GitHub Copilotfirst seen 2025-05-23Pull request: opened by its own accountCommits: 19 by its own account · at least 1 crediting it in the message
Dependencies
Installing wpa adds 90 packages (54 with compiled code, 87 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, data.table 5.7 MB.
Code & Tests
Datasets
People & History
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- RR 4.6.0 released · 2026-04-24
- 1.10.1Latest
- 1.10.02025-08-26 · diff ↗
- 1.9.22025-05-28 · diff ↗
- RR 4.5.0 released · 2025-04-11
- 1.9.12024-06-06 · diff ↗
- RR 4.4.0 released · 2024-04-24
- 1.9.0
- RR 4.3.0 released · 2023-04-21
- 1.8.12023-01-30 · diff ↗
- 1.8.02022-07-05 · diff ↗ ·
added 9 exports
external_dist, external_fizz, external_line, external_rank, external_sum, external_summary, identify_datefreq, pad2, plot_hourly_pat - unarchivedReturned to CRAN2022-06-09
- 1.7.02022-06-09 · diff ↗ ·
added 6 exports
GetResiduals, LjungBox, create_density, keymetrics_scan_asis, network_summary, wrap_text - archivedRemoved from CRAN2022-06-06check problems were not corrected in time
- RR 4.2.0 released · 2022-04-22
- 1.6.42022-01-19 · diff ↗
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Package metadata
- First published
- 2021-04-06
- Total releases
- 15 / 5 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 3.1.2
- Bundled data
- 880 KB / 5 files
- Download size
- 1.2 MB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("wpa")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
Cite the R Observatory
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From data release v2026-10-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.