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Period comparison scatter plot for any two metrics

Source: R/create_period_scatter.R
create_period_scatter.Rd

Returns two side-by-side scatter plots representing two selected metrics, using colour to map an HR attribute and size to represent number of employees. Returns a faceted scatter plot by default, with additional options to return a summary table.

Usage

create_period_scatter(
  data,
  hrvar = "Organization",
  metric_x = "Large_and_long_meeting_hours",
  metric_y = "Meeting_hours",
  before_start = min(as.Date(data$MetricDate, "%m/%d/%Y")),
  before_end,
  after_start = as.Date(before_end) + 1,
  after_end = max(as.Date(data$MetricDate, "%m/%d/%Y")),
  before_label = "Period 1",
  after_label = "Period 2",
  mingroup = 5,
  return = "plot"
)

Arguments

data

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

hrvar

HR Variable by which to split metrics. Accepts a character vector, defaults to "Organization" but accepts any character vector, e.g. "LevelDesignation"

metric_x

Character string containing the name of the metric, e.g. "Collaboration_hours"

metric_y

Character string containing the name of the metric, e.g. "Collaboration_hours"

before_start

Start date of "before" time period in YYYY-MM-DD

before_end

End date of "before" time period in YYYY-MM-DD

after_start

Start date of "after" time period in YYYY-MM-DD

after_end

End date of "after" time period in YYYY-MM-DD

before_label

String to specify a label for the "before" period. Defaults to "Period 1".

after_label

String to specify a label for the "after" period. Defaults to "Period 2".

mingroup

Numeric value setting the privacy threshold / minimum group size. Defaults to 5.

return

Character vector specifying what to return, defaults to "plot". Valid inputs are "plot" and "table".

Value

Returns a 'ggplot' object showing two scatter plots side by side representing the two periods.

Details

This is a general purpose function that powers all the functions in the package that produce faceted 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_fizz(), create_inc(), create_line(), create_line_asis(), 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_fizz(), create_hist(), create_inc(), create_line(), create_line_asis(), create_rank(), create_sankey(), create_scatter(), create_stacked(), create_tracking(), create_trend()

Other Time-series: create_line(), create_line_asis(), create_trend()

Examples

# Return plot
create_period_scatter(pq_data,
                      hrvar = "LevelDesignation",
                      before_start = "2024-05-01",
                      before_end = "2024-05-31",
                      after_start = "2024-06-01",
                      after_end = "2024-07-03")


# Return a summary table
create_period_scatter(pq_data, before_end = "2024-05-31", return = "table")
#> # A tibble: 14 × 5
#>    group      Large_and_long_meeting_hours Meeting_hours Period       n
#>    <chr>                             <dbl>         <dbl> <chr>    <int>
#>  1 Finance                            1.09          18.3 Period 1    68
#>  2 HR                                 1.08          18.4 Period 1    33
#>  3 IT                                 1.02          17.2 Period 1    68
#>  4 Legal                              1.12          22.3 Period 1    44
#>  5 Operations                         1.19          20.5 Period 1    22
#>  6 Research                           1.12          20.6 Period 1    52
#>  7 Sales                              1.13          19.4 Period 1    13
#>  8 Finance                            1.16          19.1 Period 2    68
#>  9 HR                                 1.17          18.3 Period 2    33
#> 10 IT                                 1.11          17.7 Period 2    68
#> 11 Legal                              1.06          16.9 Period 2    44
#> 12 Operations                         1.11          19.6 Period 2    22
#> 13 Research                           1.18          20.1 Period 2    52
#> 14 Sales                              1.11          18.8 Period 2    13