Analyze Email Hours distribution. Returns a stacked bar plot by default. Additional options available to return a table with distribution elements.

email_dist(
  data,
  hrvar = "Organization",
  mingroup = 5,
  return = "plot",
  cut = c(5, 10, 15)
)

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.

return

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

  • "plot"

  • "table"

See Value for more information.

cut

A numeric vector of length three to specify the breaks for the distribution, e.g. c(10, 15, 20)

Value

A different output is returned depending on the value passed to the return argument:

  • "plot": 'ggplot' object. A stacked bar plot for the metric.

  • "table": data frame. A summary table for the metric.

Examples

# Return plot
email_dist(sq_data, hrvar = "Organization")


# Return summary table
email_dist(sq_data, hrvar = "Organization", return = "table")
#> # A tibble: 15 × 6
#>    group   `< 5 hours` `5 - 10 hours` `10 - 15 hours` `15+ hours` Employee_Count
#>    <fct>         <dbl>          <dbl>           <dbl>       <dbl>          <int>
#>  1 Biz Dev      0.0133          0.96           0.0267     NA                  75
#>  2 Custom…      0.0164          0.656          0.295       0.0328             61
#>  3 Facili…     NA               0.625          0.375      NA                  72
#>  4 Financ…      0.0147          0.779          0.206      NA                  68
#>  5 Financ…      0.0429          0.329          0.586       0.0429             70
#>  6 Financ…      0.0370          0.593          0.321       0.0494             81
#>  7 Financ…     NA               0.521          0.425       0.0548             73
#>  8 Financ…     NA               0.84           0.133       0.0267             75
#>  9 G&A Ce…     NA               0.614          0.368       0.0175             57
#> 10 G&A Ea…     NA               0.846          0.154      NA                  65
#> 11 G&A So…      0.0132          0.25           0.605       0.132              76
#> 12 Human …     NA               0.197          0.690       0.113              71
#> 13 IT-Cor…      0.0147          0.338          0.5         0.147              68
#> 14 IT-East     NA               0.452          0.532       0.0161             62
#> 15 Invent…     NA               0.15           0.633       0.217              60

# Return result with a custom specified breaks
email_dist(sq_data, hrvar = "LevelDesignation", cut = c(4, 7, 9))