| create_dist | R Documentation |
Provides an analysis of the distribution of a selected metric. Returns a stacked bar plot by default. Additional options available to return a table with distribution elements.
create_dist(
data,
metric,
hrvar = "Organization",
mingroup = 5,
return = "plot",
cut = c(15, 20, 25),
dist_colours = c("#facebc", "#fcf0eb", "#b4d5dd", "#bfe5ee"),
unit = "hours",
lbound = 0,
ubound = 200,
sort_by = NULL,
labels = NULL
)
data |
A Standard Person Query dataset in the form of a data frame. |
metric |
String containing the name of the metric, e.g. "Collaboration_hours" |
hrvar |
String containing the name of the HR Variable by which to split
metrics. Defaults to |
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:
See |
cut |
A numeric vector of length three to specify the breaks for the distribution, e.g. c(10, 15, 20) |
dist_colours |
A character vector of length four to specify colour codes for the stacked bars. |
unit |
String to specify what unit to use. This defaults to |
lbound |
Numeric. Specifies the lower bound (inclusive) value for the minimum label. Defaults to 0. |
ubound |
Numeric. Specifies the upper bound (inclusive) value for the maximum label. Defaults to 100. |
sort_by |
String to specify the bucket label to sort by. Defaults to
|
labels |
Character vector to override labels for the created categorical variables. Must be a named vector - see examples. |
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.
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_boxplot(),
create_bubble(),
create_fizz(),
create_inc(),
create_line(),
create_line_asis(),
create_period_scatter(),
create_rank(),
create_rogers(),
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_rank(),
external_sum(),
hr_trend(),
hrvar_count(),
hrvar_trend(),
keymetrics_scan(),
meeting_dist(),
meeting_fizz(),
meeting_line(),
meeting_rank(),
meeting_summary(),
meeting_trend(),
one2one_dist(),
one2one_fizz(),
one2one_freq(),
one2one_line(),
one2one_rank(),
one2one_sum(),
one2one_trend()
Other Flexible:
create_bar(),
create_bar_asis(),
create_boxplot(),
create_bubble(),
create_density(),
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()
# Return plot
create_dist(pq_data, metric = "Collaboration_hours", hrvar = "Organization")
# Return summary table
create_dist(pq_data, metric = "Collaboration_hours", hrvar = "Organization", return = "table")
# Use custom labels by providing a label vector
eh_labels <- c(
"Fewer than fifteen" = "< 15 hours",
"Between fifteen and twenty" = "15 - 20 hours",
"Between twenty and twenty-five" = "20 - 25 hours",
"More than twenty-five" = "25+ hours"
)
pq_data %>% create_dist(metric = "Meeting_hours", labels = eh_labels, return = "plot")
# Sort by a category
pq_data %>% create_dist(metric = "Collaboration_hours", sort_by = "25+ hours")
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