Overview
Sunbursts are similar to Sankeys in that they visualize patterns, but differ in how the patterns are calculated. In Sankeys, states are calculated at cross-sectional points in time and presented as flows through time. In sunbursts, order, irrelevant to time, is considered in calculation of the pattern. For example, a patient who is on Treatment A for one year then Treatment B for one day would have the exact same pattern as someone who is on Treatment A for one day, then transitions to Treatment B for one year (A -> B).
Basic Sunburst
First, the id level data are created used
sunburst_id_data. This is to help facilitate running on
partitions on the id-level first, before the summarizing step in
sunburst_maker. sunburst_id_data requires a
cohort, an ansible style data.frame, and which “states” are
wanted. It returns a list of the resulting data.frame and the states, so
it can directly be fed into sunburst_maker.
events <- nsSank::convert_tagged_cdf(cdf)
data <- nsSank::ansible(events)
data
#> # A tibble: 58,045 × 4
#> patient_id start end state
#> <int> <date> <date> <list>
#> 1 1 2010-04-01 2010-06-30 <chr [1]>
#> 2 1 2010-08-04 2010-09-12 <chr [1]>
#> 3 1 2010-09-13 2010-11-02 <chr [2]>
#> 4 1 2010-11-03 2010-12-12 <chr [1]>
#> 5 1 2010-12-21 2011-02-19 <chr [1]>
#> 6 2 2010-02-11 2010-02-21 <chr [1]>
#> 7 2 2010-02-22 2010-03-13 <chr [2]>
#> 8 2 2010-03-14 2010-04-23 <chr [1]>
#> 9 3 2010-04-07 2010-07-06 <chr [1]>
#> 10 3 2010-10-09 2011-02-02 <chr [1]>
#> # ℹ 58,035 more rows
sdata <- nsSank::sunburst_id_data(cohort, data, states = c("a", "b"))
#sdata$id_data
sunburst_list <- nsSank::sunburst_maker(cohort, sdata, max_levels = 5)
nswidgets::create_sunburst(sunburst_list$data, sunburst_list$types)