Skip to contents

Fizzy Drink / Jittered Scatter Plot for any metric

Source: R/create_fizz.R
create_fizz.Rd

Analyzes a selected metric and returns a 'fizzy' scatter plot by default. Additional options available to return a table with distribution elements.

Usage

create_fizz(
  data,
  metric,
  hrvar = "Organization",
  mingroup = 5,
  return = "plot"
)

Arguments

data

A Standard Person Query dataset in the form of a data frame.

metric

Character 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.

return

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

  • "plot"

  • "table"

See Value for more information.

Value

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

  • "plot": 'ggplot' object. A jittered scatter plot for the metric.

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

Details

This is a general purpose function that powers all the functions in the package that produce 'fizzy drink' / jittered scatter plots.

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_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_dist(), 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

# Create a fizzy plot for Collaboration hours by Level Designation
create_fizz(pq_data, metric = "Collaboration_hours", hrvar = "LevelDesignation", return = "plot")


# Create a summary statistics table for Collaboration hours by Organization
create_fizz(pq_data, metric = "Collaboration_hours", hrvar = "Organization", return = "table")
#> # A tibble: 7 × 8
#>   group       mean median    sd   min   max range     n
#>   <chr>      <dbl>  <dbl> <dbl> <dbl> <dbl> <dbl> <int>
#> 1 Finance     23.1   23.1  1.24  20.3  25.4  5.10    68
#> 2 HR          23.1   22.9  1.01  21.0  24.8  3.78    33
#> 3 IT          22.8   22.8  1.43  20.3  26.9  6.65    68
#> 4 Legal       22.5   22.6  1.23  19.7  24.8  5.06    44
#> 5 Operations  23.5   23.3  1.62  20.0  26.4  6.39    22
#> 6 Research    23.3   23.3  1.30  20.1  25.5  5.39    52
#> 7 Sales       23.1   23.2  1.13  21.2  24.7  3.48    13