Run a summary of Key Metrics from the Standard Person Query data
Source:R/keymetrics_scan.R
keymetrics_scan.RdReturns a heatmapped table by default, with options to return a table.
Usage
keymetrics_scan(
data,
hrvar = "Organization",
mingroup = 5,
metrics = c("Workweek_span", "Collaboration_hours", "After_hours_collaboration_hours",
"Meetings", "Meeting_hours", "After_hours_meeting_hours",
"Low_quality_meeting_hours", "Meeting_hours_with_manager_1_on_1",
"Meeting_hours_with_manager", "Emails_sent", "Email_hours",
"After_hours_email_hours", "Generated_workload_email_hours", "Total_focus_hours",
"Internal_network_size", "Networking_outside_organization", "External_network_size",
"Networking_outside_company"),
return = "plot",
low = rgb2hex(7, 111, 161),
mid = rgb2hex(241, 204, 158),
high = rgb2hex(216, 24, 42),
textsize = 2
)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.
- metrics
A character vector containing the variable names to calculate averages of.
- return
Character vector specifying what to return, defaults to "plot". Valid inputs are "plot" and "table".
- low
String specifying colour code to use for low-value metrics. Arguments are passed directly to
ggplot2::scale_fill_gradient2().- mid
String specifying colour code to use for mid-value metrics. Arguments are passed directly to
ggplot2::scale_fill_gradient2().- high
String specifying colour code to use for high-value metrics. Arguments are passed directly to
ggplot2::scale_fill_gradient2().- textsize
A numeric value specifying the text size to show in the plot.
Value
Returns a ggplot object by default, when '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(),
create_bar_asis(),
create_boxplot(),
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_rank(),
external_sum(),
hr_trend(),
hrvar_count(),
hrvar_trend(),
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()
Examples
# Heatmap plot is returned by default
keymetrics_scan(pq_data)
# Heatmap plot with custom colours
keymetrics_scan(pq_data, low = "purple", high = "yellow")
# Return summary table
keymetrics_scan(pq_data, hrvar = "LevelDesignation", return = "table")
#> # A tibble: 11 × 6
#> variable Director `Junior IC` Manager `Senior IC` Support
#> <fct> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 Collaboration_hours 72.0 21.4 26.9 12.1 12.9
#> 2 After_hours_collaboration_h… 42.4 11.6 13.1 4.60 5.20
#> 3 Meetings 45.3 10.9 21.1 11.3 11.5
#> 4 Meeting_hours 71.5 20.8 26.1 11.3 12.2
#> 5 After_hours_meeting_hours 41.9 11.2 12.5 4.02 4.66
#> 6 Meeting_hours_with_manager 32.2 8.26 17.7 6.86 7.36
#> 7 Emails_sent 99.7 33.0 59.6 37.1 36.0
#> 8 Email_hours 2.50 0.991 1.53 1.11 1.08
#> 9 After_hours_email_hours 1.22 0.587 0.839 0.709 0.665
#> 10 Internal_network_size 78.0 27.6 47.3 32.7 29.3
#> 11 Employee_Count 6 10 11 20 53