Analyzes a selected metric and returns a box plot by default. Additional options available to return a table with distribution elements.
create_boxplot(
data,
metric,
hrvar = "Organization",
mingroup = 5,
return = "plot"
)
A Standard Person Query dataset in the form of a data frame.
Character string containing the name of the metric, e.g. "Collaboration_hours"
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).
Numeric value setting the privacy threshold / minimum group size. Defaults to 5.
String specifying what to return. This must be one of the following strings:
"plot"
"table"
See Value
for more information.
A different output is returned depending on the value passed to the return
argument:
"plot"
: 'ggplot' object. A box plot for the metric.
"table"
: data frame. A summary table for the metric.
This is a general purpose function that powers all the functions in the package that produce box plots.
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()
,
create_bar_asis()
,
create_bubble()
,
create_dist()
,
create_fizz()
,
create_inc()
,
create_line()
,
create_line_asis()
,
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()
,
meetingtype_dist_ca()
,
meetingtype_dist_mt()
,
meetingtype_summary()
,
mgrcoatt_dist()
,
mgrrel_matrix()
,
one2one_dist()
,
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 Flexible:
create_bar()
,
create_bar_asis()
,
create_bubble()
,
create_density()
,
create_dist()
,
create_fizz()
,
create_hist()
,
create_inc()
,
create_line()
,
create_line_asis()
,
create_period_scatter()
,
create_rank()
,
create_sankey()
,
create_scatter()
,
create_stacked()
,
create_tracking()
,
create_trend()
,
period_change()
# Create a fizzy plot for Work Week Span by Level Designation
create_boxplot(sq_data,
metric = "Workweek_span",
hrvar = "LevelDesignation",
return = "plot")
# Create a summary statistics table for Work Week Span by Organization
create_boxplot(sq_data,
metric = "Workweek_span",
hrvar = "Organization",
return = "table")
#> # A tibble: 5 × 8
#> group mean median sd min max range n
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
#> 1 Customer Service 41.6 40.2 5.19 34.0 58.4 24.4 61
#> 2 Finance 43.6 39.7 8.30 32.2 65.8 33.7 292
#> 3 Financial Planning 40.1 38.3 6.07 30.0 62.2 32.2 75
#> 4 Human Resources 44.0 42.5 6.27 32.6 59.6 27.0 71
#> 5 IT 41.8 40.6 6.54 31.6 62.6 31.0 130
# Create a fizzy plot for Collaboration Hours by Level Designation
create_boxplot(sq_data,
metric = "Collaboration_hours",
hrvar = "LevelDesignation",
return = "plot")