Provides a week by week view of meeting time. By default returns a week by week heatmap, highlighting the points in time with most activity. Additional options available to return a summary table.
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.
- return
Character vector specifying what to return, defaults to
"plot"
. Valid inputs are "plot" and "table".
Value
Returns a 'ggplot' object by default, where '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()
,
keymetrics_scan()
,
meeting_dist()
,
meeting_fizz()
,
meeting_line()
,
meeting_rank()
,
meeting_summary()
,
one2one_dist()
,
one2one_fizz()
,
one2one_freq()
,
one2one_line()
,
one2one_rank()
,
one2one_sum()
,
one2one_trend()
Other Meetings:
meeting_dist()
,
meeting_fizz()
,
meeting_line()
,
meeting_rank()
,
meeting_summary()
,
meeting_tm_report()
Examples
# Run plot
meeting_trend(pq_data)
# Run table
meeting_trend(pq_data, hrvar = "LevelDesignation", return = "table")
#> # A tibble: 4 × 24
#> group `2024-04-28` `2024-05-05` `2024-05-12` `2024-05-19` `2024-05-26`
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 Executive 22.9 14.2 16.1 21.0 20.0
#> 2 Junior IC 18.4 18.1 20.4 18.5 17.0
#> 3 Senior IC 19.8 20.7 19.1 20.7 16.0
#> 4 Senior Manag… 17.1 19.2 22.0 29.5 22.7
#> # ℹ 18 more variables: `2024-06-02` <dbl>, `2024-06-09` <dbl>,
#> # `2024-06-16` <dbl>, `2024-06-23` <dbl>, `2024-06-30` <dbl>,
#> # `2024-07-07` <dbl>, `2024-07-14` <dbl>, `2024-07-21` <dbl>,
#> # `2024-07-28` <dbl>, `2024-08-04` <dbl>, `2024-08-11` <dbl>,
#> # `2024-08-18` <dbl>, `2024-08-25` <dbl>, `2024-09-01` <dbl>,
#> # `2024-09-08` <dbl>, `2024-09-15` <dbl>, `2024-09-22` <dbl>,
#> # `2024-09-29` <dbl>