Analyze Work Week Span distribution. Returns a stacked bar plot by default. Additional options available to return a table with distribution elements.
workloads_dist(
data,
hrvar = "Organization",
mingroup = 5,
return = "plot",
cut = c(15, 30, 45)
)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, supplyNULL(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
Valuefor 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_dist(),
one2one_fizz(),
one2one_freq(),
one2one_line(),
one2one_rank(),
one2one_sum(),
one2one_trend(),
period_change(),
workloads_fizz(),
workloads_line(),
workloads_rank(),
workloads_summary(),
workloads_trend(),
workpatterns_area(),
workpatterns_rank()
Other Workweek Span:
workloads_fizz(),
workloads_line(),
workloads_rank(),
workloads_summary(),
workloads_trend()
Examples
# Return plot
workloads_dist(sq_data, hrvar = "Organization", return = "plot")
# Return a summary table
workloads_dist(sq_data, hrvar = "Organization", return = "table")
#> # A tibble: 15 × 4
#> group `30 - 45 hours` `45+ hours` Employee_Count
#> <fct> <dbl> <dbl> <int>
#> 1 Biz Dev 1 NA 75
#> 2 Customer Service 0.836 0.164 61
#> 3 Facilities 0.653 0.347 72
#> 4 Finance-Corporate 0.779 0.221 68
#> 5 Finance-East 0.414 0.586 70
#> 6 Finance-South 0.630 0.370 81
#> 7 Finance-West 0.548 0.452 73
#> 8 Financial Planning 0.853 0.147 75
#> 9 G&A Central 0.649 0.351 57
#> 10 G&A East 1 NA 65
#> 11 G&A South 0.776 0.224 76
#> 12 Human Resources 0.732 0.268 71
#> 13 IT-Corporate 0.75 0.25 68
#> 14 IT-East 0.887 0.113 62
#> 15 Inventory Management 0.533 0.467 60