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Create a density plot for any metric

Source: R/create_density.R
create_density.Rd

Provides an analysis of the distribution of a selected metric. Returns a faceted density plot by default. Additional options available to return the underlying frequency table.

Usage

create_density(
  data,
  metric,
  hrvar = "Organization",
  mingroup = 5,
  ncol = NULL,
  return = "plot"
)

Arguments

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 "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.

ncol

Numeric value setting the number of columns on the plot. Defaults to NULL (automatic).

return

String specifying what to return. This must be one of the following strings:

  • "plot"

  • "table"

  • "data"

  • "frequency"

See Value for more information.

Value

A different output is returned depending on the value passed to the return argument:

  • "plot": 'ggplot' object. A faceted density plot for the metric.

  • "table": data frame. A summary table for the metric.

  • "data": data frame. Data with calculated person averages.

  • "frequency: list of data frames. Each data frame contains the frequencies used in each panel of the plotted histogram.

See also

Other Flexible: create_bar(), create_bar_asis(), create_boxplot(), create_bubble(), create_dist(), 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()

Examples

# Return plot for whole organization
create_density(pq_data, metric = "Collaboration_hours", hrvar = NULL)


# Return plot
create_density(pq_data, metric = "Collaboration_hours", hrvar = "Organization")


# Return plot but coerce plot to three columns
create_density(pq_data, metric = "Collaboration_hours", hrvar = "Organization", ncol = 3)


# Return summary table
create_density(pq_data, metric = "Collaboration_hours", hrvar = "Organization", return = "table")
#> # A tibble: 4 × 6
#>   group                mean median   max   min Employee_Count
#>   <chr>               <dbl>  <dbl> <dbl> <dbl>          <int>
#> 1 Finance              16.7   13.4  54.5  8.83             27
#> 2 HR                   17.8   12.3 119.   8.99             21
#> 3 Product              11.7   10.8  32.5  8.13             21
#> 4 Sales and Marketing  25.8   13.3 119.   7.08             31