R: Run a summary of Key Metrics from the Standard Person Query...

keymetrics_scan {vivainsights}

R Documentation

Run a summary of Key Metrics from the Standard Person Query data

Description

Returns 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, supply `NULL` (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.

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")