# vivainsights 0.7.3

* Replaced dynamic string evaluation in `network_p2p()` with allowlisted community, layout, and palette dispatch.
* Added support for passing a palette function directly to `network_p2p()`.
* Fixed `network_p2p()` ggraph colours so palettes are matched to group or cluster labels rather than vertex order.
* Fixed `heat_colors()` and `heat_colours()` so their documented default usage no longer requires an explicit `alpha` value.
* Added a task-oriented function catalogue and agent discovery guide covering primary Viva Insights workflows and R/Python capability parity.

# vivainsights 0.7.2

* Added `identify_retention()` for calculating the retention rate of individuals between two time periods based on a category condition
* Enhanced documentation for clearer function usage and discovery for agents and users
* Improved diagnostic messages for `extract_hr()`
* Improved documentation for `mingroup` in vignette and README

# vivainsights 0.7.1

* Bug fix to `identify_usage_segments()`: Fixed incorrect `n` count in table output to use distinct PersonIds instead of row count
* Improvement to `identify_usage_segments()`: Reordered table output columns to follow logical segment progression (Non-user, Low User, Novice User, Habitual User, Power User)
* Aesthetic improvements to `create_rogers()`
* Added `create_radar()` and `create_radar_viz()` for spider/radar chart visualisation, with support for flexible indexing modes (`total`, `ref_group`, `minmax`, `none`), privacy filtering, and group comparisons
* Added `create_survival()`, `create_survival_prep()`, `create_survival_calc()`, and `create_survival_viz()` for Kaplan–Meier survival (time-to-adoption) curve analysis, supporting flexible event definitions and group comparisons
* Bumped minimum R version to 4.1.0 (required for native pipe-style lambda syntax `\(x)` used in `create_radar()`)
* Added warning message to `identify_usage_segments()` when NA values are detected in the metric variable

# vivainsights 0.7.0

* Added `create_rogers()` function for analyzing technology adoption patterns using Rogers adoption curve theory
* Feature improvements to `create_hist()`, `create_density()`, `identify_usage_segments()`, `create_line()`
* Refactor superseded dplyr syntax to current best practices
* Optimized dependencies using base R functions where appropriate

# vivainsights 0.6.2

* Minor bug fixes to `validation_report()`
* Clearer diagnostic messages to `identify_*()` family of functions

# vivainsights 0.6.1

* Added `identify_usage_segments()` for classifying usage segments. 
* Added `create_itsa()` for performing interrupted time-series analysis.

# vivainsights 0.6.0

* Add `identify_habits()` for classifying habitual behavior.
* Refactored code to latest dplyr and tidyselect practices.
* Updated metrics in `pq_data` to include Copilot metrics.

# vivainsights 0.5.5

* Add new functionality on calculating Chatterjee's coefficient
* Improved test coverage

# vivainsights 0.5.4

Added new functionality to calculate Gini coefficient and Lorenz curve.

# vivainsights 0.5.3

Minor bug fixes and visual improvements.

# vivainsights 0.5.2

Minor bugfix on `create_line()`. 

# vivainsights 0.5.1

Minor changes to documentation on static report outputs.

# vivainsights 0.5.0

Added new functionality to calculate information value: `create_IV()` and `IV_report()` 

# vivainsights 0.4.3

- Updated datasets for `g2g_data` and `p2p_data`
- Improve test coverage

# vivainsights 0.4.2

- Improved versatility to `identify_query()`
- Added `any_idate()`
- Bug fixes

# vivainsights 0.4.1

- Removed the DT dependency

# vivainsights 0.4.0

Added new functionality for organizational network analysis (ONA):

  - Introduced `p2p_data` and `g2g_data` sample datasets, with an option to simulate a person-to-person dataset using `p2p_data_sim()`
  - Added `network_g2g()`, `network_p2p()`, `network_summary()`, and `create_sankey()` functions
  - `network_p2p()` now has a `centrality` argument for computing and visualizing centrality as node sizes in the network plot
  - For `network_p2p()`:
    - the `algorithm` argument is renamed to `layout` for better intuitiveness
    - Improved consistency and intuitiveness of the API, with `style` argument now controlling the network plotting mechanism and `return` argument controlling whether plots are generated interactively or saved as PDF
    - Added a large number of community detection algorithms from `igraph`

# vivainsights 0.3.1

- Fixed bug in running validation report (#11)

# vivainsights 0.3.0

- Added new text analytics functions relating to the meeting query

# vivainsights 0.2.0

- colour contrast improved for `create_dist()` family functions
- added data validation family of functions, including `validation_report()`
- adds 'wpa' as a package dependency 

# vivainsights 0.1.0

This is the first version of the **vivainsights** package to be released open-source on GitHub and CRAN. This is based on the original [wpa](https://microsoft.github.io/wpa/) library, with functions and documentation updated to reflect the latest features in Viva Insights.
