Creates a sum total calculation using selected metrics, where the typical use case is to create different definitions of collaboration hours. Returns a stacked bar plot by default. Additional options available to return a summary table.
create_stacked(
data,
hrvar = "Organization",
metrics = c("Meeting_hours", "Email_hours"),
mingroup = 5,
return = "plot",
stack_colours = c("#1d627e", "#34b1e2", "#b4d5dd", "#adc0cb"),
percent = FALSE,
plot_title = "Collaboration Hours",
plot_subtitle = paste("Average by", tolower(camel_clean(hrvar))),
legend_lab = NULL,
rank = "descending",
xlim = NULL,
text_just = 0.5,
text_colour = "#FFFFFF"
)
A Standard Person Query dataset in the form of a data frame.
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).
A character vector to specify variables to be used in calculating the "Total" value, e.g. c("Meeting_hours", "Email_hours"). The order of the variable names supplied determine the order in which they appear on the stacked plot.
Numeric value setting the privacy threshold / minimum group size. Defaults to 5.
Character vector specifying what to return, defaults to "plot". Valid inputs are "plot" and "table".
A character vector to specify the colour codes for the stacked bar charts.
Logical value to determine whether to show labels as
percentage signs. Defaults to FALSE
.
String. Option to override plot title.
String. Option to override plot subtitle.
String. Option to override legend title/label. Defaults to
NULL
, where the metric name will be populated instead.
String specifying how to rank the bars. Valid inputs are:
"descending"
- ranked highest to lowest from top to bottom (default).
"ascending"
- ranked lowest to highest from top to bottom.
NULL
- uses the original levels of the HR attribute.
An option to set max value in x axis.
A numeric value controlling for the horizontal position of the text labels. Defaults to 0.5.
String to specify
colour to use for the text labels. Defaults to "#FFFFFF"
.
Returns a 'ggplot' object by default, where 'plot' is passed in return
.
When 'table' is passed, a summary table is returned as a data frame.
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_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_dist()
,
workloads_fizz()
,
workloads_line()
,
workloads_rank()
,
workloads_summary()
,
workloads_trend()
,
workpatterns_area()
,
workpatterns_rank()
Other Flexible:
create_bar_asis()
,
create_bar()
,
create_boxplot()
,
create_bubble()
,
create_density()
,
create_dist()
,
create_fizz()
,
create_hist()
,
create_inc()
,
create_line_asis()
,
create_line()
,
create_period_scatter()
,
create_rank()
,
create_sankey()
,
create_scatter()
,
create_tracking()
,
create_trend()
,
period_change()
sq_data %>%
create_stacked(hrvar = "LevelDesignation",
metrics = c("Meeting_hours", "Email_hours"),
return = "plot")
sq_data %>%
create_stacked(hrvar = "FunctionType",
metrics = c("Meeting_hours",
"Email_hours",
"Call_hours",
"Instant_Message_hours"),
return = "plot",
rank = "ascending")
sq_data %>%
create_stacked(hrvar = "FunctionType",
metrics = c("Meeting_hours",
"Email_hours",
"Call_hours",
"Instant_Message_hours"),
return = "table")
#> # A tibble: 8 × 7
#> group Meeting_hours Email_hours Call_hours Instant_Messa…¹ Total Emplo…²
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
#> 1 Engineering 9.28 10.3 4.56 0.621 24.8 93
#> 2 Finance 8.35 8.17 4.28 0.620 21.4 146
#> 3 G_and_A 8.11 7.93 4.20 0.610 20.9 128
#> 4 IT 7.02 7.97 3.42 0.597 19.0 51
#> 5 Marketing 13.1 12.7 7.36 0.576 33.8 207
#> 6 Operations 9.79 9.33 5.22 0.655 25.0 176
#> 7 R_and_D 7.37 7.79 4.05 0.593 19.8 151
#> 8 Sales 16.2 14.7 8.92 0.538 40.4 82
#> # … with abbreviated variable names ¹Instant_Message_hours, ²Employee_Count