Merge pull request #53 from microsoft/docs/add-lifecycle-badges

Documentation: add lifecycle badges

.Rbuildignore

@@ -1,3 +1,4 @@
+^.gitignore$
 ^.*\.Rproj$
 ^\.Rproj\.user$
 ^_data$
@@ -10,12 +11,10 @@
 ^_pkgdown\.yml$
 ^pkgdown$
 ^\.github$
-^man/figures/wpa cheatsheet_20201116.pdf$
-^man/figures/wpa cheatsheet_20201116.png$
-^man/figures/wpa cheatsheet.pdf$
-^man/figures/wpa cheatsheet.png$
-^vignettes/best-practices.Rmd$
-^vignettes/text-mining-capabilities.Rmd$
-^vignettes/IV-report.Rmd$
-^vignettes/Change-over-time.Rmd$
 ^CONTRIBUTORS.svg$
+
+# Ignore all figures
+^man/figures
+
+# Ignore all vignettes
+^vignettes

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: wpa
 Type: Package
-Title: Tools for Analysing and Visualising Workplace Analytics data
+Title: Tools for Analysing and Visualising Workplace Analytics Data
 Version: 1.3.1
 Authors@R: c(
     person(given = "Martin", family = "Chan", role = c("aut", "cre"), email = "[email protected]"),
@@ -58,7 +58,8 @@ Imports:
     rlang,
     ggwordcloud,
     methods,
-    data.table
+    data.table,
+    lifecycle
 RoxygenNote: 7.1.1
 Roxygen: list(markdown = TRUE)
 VignetteBuilder: knitr

R/heat_colours.R

@@ -1,7 +1,7 @@
 #' @title
 #' Generate a vector of `n` contiguous colours, as a red-yellow-green palette.
 #'
-#' @param n the number of colors (≥ 1) to be in the palette.
+#' @param n the number of colors (>= 1) to be in the palette.
 #' @param alpha an alpha-transparency level in the range of 0 to 1
 #' (0 means transparent and 1 means opaque)
 #' @param rev logical indicating whether the ordering of the colors should be reversed.

R/network_describe.R

@@ -8,6 +8,7 @@
 #' @author Tannaz Sattari Tabrizi <[email protected]>
 #'
 #' @description
+#' \Sexpr[results=rd]{lifecycle::badge("experimental")}
 #' Returns a data frame that gives a percentage of the group combinations that best represent
 #' the population provided. Uses a person to person query.
 #'

R/network_leiden.R

@@ -6,6 +6,7 @@
 #' @title Implement the Leiden community detection on a Person to Person network query
 #'
 #' @description
+#' \Sexpr[results=rd]{lifecycle::badge("experimental")}
 #' Take a P2P network query and implement the Leiden community detection method. To run
 #' this function, you will require all the pre-requisites of the **leiden** package installed,
 #' which includes Python and **reticulate**.

R/network_louvain.R

@@ -6,6 +6,7 @@
 #' @title Implement the Louvain community detection on a Person to Person network query
 #'
 #' @description
+#' \Sexpr[results=rd]{lifecycle::badge("experimental")}
 #' Take a P2P network query and implement the Louvain community detection method. The
 #' **igraph** implementation of the Louvain method is used.
 #'

R/network_p2p.R

@@ -6,6 +6,7 @@
 #' @title Create a network plot with the person-to-person query
 #'
 #' @description
+#' \Sexpr[results=rd]{lifecycle::badge("experimental")}
 #' Pass a data frame containing a person-to-person query and return a network visualization.
 #' Options are available for community detection using either the Louvain or the Leiden algorithms.
 #'

R/personas_hclust.R

@@ -6,6 +6,7 @@
 #' @title Create hierarchical clusters of selected metrics using a Person query
 #'
 #' @description
+#' \Sexpr[results=rd]{lifecycle::badge("questioning")}
 #' Apply hierarchical clustering to selected metrics. Person averages are computed prior to clustering.
 #' The hierarchical clustering uses cosine distance and the ward.D method
 #' of agglomeration.

R/workpatterns_hclust.R

@@ -6,6 +6,7 @@
 #' @title Create a hierarchical clustering of email or IMs by hour of day
 #'
 #' @description
+#' \Sexpr[results=rd]{lifecycle::badge("experimental")}
 #' Apply hierarchical clustering to emails sent by hour of day.
 #' The hierarchical clustering uses cosine distance and the ward.D method
 #' of agglomeration.