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Provides a week by week view of a selected Viva Insights metric. By default returns a week by week heatmap bar plot, highlighting the points in time with most activity. Additional options available to return a summary table.

Usage

create_trend(
  data,
  metric,
  hrvar = "Organization",
  mingroup = 5,
  palette = c("steelblue4", "aliceblue", "white", "mistyrose1", "tomato1"),
  return = "plot",
  legend_title = "Hours"
)

Arguments

data

A Standard Person Query dataset in the form of a data frame.

metric

Character string containing the name of the metric, e.g. "Collaboration_hours"

hrvar

String containing the name of the HR Variable by which to split metrics. Defaults to "Organization". To run the analysis on the total instead of splitting by an HR attribute, supply NULL (without quotes).

mingroup

Numeric value setting the privacy threshold / minimum group size. Defaults to 5.

palette

Character vector containing colour codes, ranked from the lowest value to the highest value. This is passed directly to ggplot2::scale_fill_gradientn().

return

Character vector specifying what to return, defaults to "plot". Valid inputs are "plot" and "table".

legend_title

String to be used as the title of the legend. Defaults to "Hours".

Value

Returns a 'ggplot' object by default, where 'plot' is passed in return. When 'table' is passed, a summary table is returned as a data frame.

Examples

create_trend(pq_data, metric = "Collaboration_hours", hrvar = "LevelDesignation")


# custom colours
create_trend(
  pq_data,
  metric = "Collaboration_hours",
  hrvar = "LevelDesignation",
  palette = c(
    "#FB6107",
    "#F3DE2C",
    "#7CB518",
    "#5C8001"
  )
  )