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"
)

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).

metrics

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.

mingroup

Numeric value setting the privacy threshold / minimum group size. Defaults to 5.

return

Character vector specifying what to return, defaults to "plot". Valid inputs are "plot" and "table".

stack_colours

A character vector to specify the colour codes for the stacked bar charts.

percent

Logical value to determine whether to show labels as percentage signs. Defaults to FALSE.

plot_title

String. Option to override plot title.

plot_subtitle

String. Option to override plot subtitle.

legend_lab

String. Option to override legend title/label. Defaults to NULL, where the metric name will be populated instead.

rank

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.

xlim

An option to set max value in x axis.

text_just

[Experimental] A numeric value controlling for the horizontal position of the text labels. Defaults to 0.5.

text_colour

[Experimental] String to specify colour to use for the text labels. Defaults to "#FFFFFF".

Value

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.

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_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()

Examples

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_Message_hours Total
#>   <chr>               <dbl>       <dbl>      <dbl>                 <dbl> <dbl>
#> 1 Engineering          9.28       10.3        4.56                 0.621  24.8
#> 2 Finance              8.35        8.17       4.28                 0.620  21.4
#> 3 G_and_A              8.11        7.93       4.20                 0.610  20.9
#> 4 IT                   7.02        7.97       3.42                 0.597  19.0
#> 5 Marketing           13.1        12.7        7.36                 0.576  33.8
#> 6 Operations           9.79        9.33       5.22                 0.655  25.0
#> 7 R_and_D              7.37        7.79       4.05                 0.593  19.8
#> 8 Sales               16.2        14.7        8.92                 0.538  40.4
#> # … with 1 more variable: Employee_Count <int>