Analyze Manager 1:1 Time distribution. Returns a stacked bar plot of different buckets of 1:1 time. Additional options available to return a table with distribution elements.

one2one_dist(
  data,
  hrvar = "Organization",
  mingroup = 5,
  dist_colours = c("#facebc", "#fcf0eb", "#b4d5dd", "#bfe5ee"),
  return = "plot",
  cut = c(5, 15, 30)
)

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.

dist_colours

A character vector of length four to specify colour codes for the stacked bars.

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.

See also

Other Visualization: afterhours_dist(), afterhours_fizz(), afterhours_line(), afterhours_rank(), afterhours_summary(), afterhours_trend(), collaboration_area(), collaboration_dist(), collaboration_fizz(), collaboration_line(), collaboration_rank(), collaboration_sum(), collaboration_trend(), create_bar_asis(), create_bar(), create_boxplot(), create_bubble(), create_dist(), create_fizz(), create_inc(), create_line_asis(), create_line(), create_period_scatter(), create_rank(), create_sankey(), create_scatter(), create_stacked(), create_tracking(), create_trend(), email_dist(), email_fizz(), email_line(), email_rank(), email_summary(), email_trend(), external_dist(), external_fizz(), external_line(), external_network_plot(), external_rank(), external_sum(), hr_trend(), hrvar_count(), hrvar_trend(), internal_network_plot(), keymetrics_scan(), meeting_dist(), meeting_fizz(), meeting_line(), meeting_quality(), meeting_rank(), meeting_summary(), meeting_trend(), meetingtype_dist_ca(), meetingtype_dist_mt(), meetingtype_dist(), meetingtype_summary(), mgrcoatt_dist(), mgrrel_matrix(), one2one_fizz(), one2one_freq(), one2one_line(), one2one_rank(), one2one_sum(), one2one_trend(), period_change(), workloads_dist(), workloads_fizz(), workloads_line(), workloads_rank(), workloads_summary(), workloads_trend(), workpatterns_area(), workpatterns_rank()

Other Managerial Relations: mgrcoatt_dist(), mgrrel_matrix(), one2one_fizz(), one2one_freq(), one2one_line(), one2one_rank(), one2one_sum(), one2one_trend()

Examples

# Return plot
one2one_dist(sq_data, hrvar = "Organization", return = "plot")


# Return summary table
one2one_dist(sq_data, hrvar = "Organization", return = "table")
#> # A tibble: 15 × 6
#>    group           `< 5 minutes` `5 - 15 minutes` `15 - 30 minut…` `30+ minutes`
#>    <fct>                   <dbl>            <dbl>            <dbl>         <dbl>
#>  1 Biz Dev                 0.267            0.307            0.373        0.0533
#>  2 Customer Servi…         0.148            0.279            0.295        0.279 
#>  3 Facilities              0.25             0.292            0.333        0.125 
#>  4 Finance-Corpor…         0.147            0.515            0.25         0.0882
#>  5 Finance-East            0.1              0.314            0.329        0.257 
#>  6 Finance-South           0.160            0.407            0.309        0.123 
#>  7 Finance-West            0.247            0.356            0.329        0.0685
#>  8 Financial Plan…         0.267            0.387            0.24         0.107 
#>  9 G&A Central             0.158            0.246            0.386        0.211 
#> 10 G&A East                0.277            0.2              0.262        0.262 
#> 11 G&A South               0.197            0.447            0.25         0.105 
#> 12 Human Resources         0.239            0.254            0.324        0.183 
#> 13 IT-Corporate            0.265            0.265            0.294        0.176 
#> 14 IT-East                 0.435            0.290            0.242        0.0323
#> 15 Inventory Mana…         0.1              0.433            0.333        0.133 
#> # … with 1 more variable: Employee_Count <int>