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This function scans a Standard Person Query for groups with high levels of External Collaboration. Returns a plot by default, with an option to return a table with all groups (across multiple HR attributes) ranked by hours of External Collaboration.

Usage

external_rank(
  data,
  hrvar = extract_hr(data),
  mingroup = 5,
  mode = "simple",
  plot_mode = 1,
  return = "plot"
)

Arguments

data

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

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.

mode

String to specify calculation mode. Must be either:

  • "simple"

  • "combine"

plot_mode

Numeric vector to determine which plot mode to return. Must be either 1 or 2, and is only used when return = "plot".

  • 1: Top and bottom five groups across the data population are highlighted

  • 2: Top and bottom groups per organizational attribute are highlighted

return

String specifying what to return. This must be one of the following strings:

  • "plot" (default)

  • "table"

See Value for more information.

Value

When 'table' is passed in return, a summary table is returned as a data frame.

Details

Uses the metric Collaboration_hours_external. See create_rank() for applying the same analysis to a different metric.

Examples

# Return rank table
external_rank(data = pq_data, return = "table")
#> # A tibble: 21 × 4
#>    hrvar               group               External_collaboration_hours     n
#>    <chr>               <chr>                                      <dbl> <int>
#>  1 LevelDesignation    Director                                    6.26     6
#>  2 SupervisorIndicator Manager+                                    6.26     6
#>  3 FunctionType        Sales                                       4.96    11
#>  4 FunctionType        Marketing                                   2.90    12
#>  5 Organization        Sales and Marketing                         2.87    31
#>  6 Organization        HR                                          2.70    21
#>  7 Organization        Finance                                     2.64    27
#>  8 FunctionType        G_and_A                                     2.62     6
#>  9 FunctionType        Customer_Service                            2.54    12
#> 10 WeekendDays         [SUNDAY, SATURDAY]                          2.44   100
#> # ℹ 11 more rows

# Return plot
external_rank(data = pq_data, return = "plot")