Create a tibble that maps the kmeans_obj()
using purrr::map()
to create a nested data.frame/tibble that holds n centers. This tibble will be
used to help create a scree plot.
Arguments
- .data
You must have a tibble in the working environment from the
kmeans_user_item_tbl()
- .centers
How many different centers do you want to try
Details
Takes in a single parameter of .centers. This is used to create the tibble
and map the kmeans_obj()
function down the list creating a nested tibble.
Examples
library(healthyR.data)
library(dplyr)
data_tbl <- healthyR_data%>%
filter(ip_op_flag == "I") %>%
filter(payer_grouping != "Medicare B") %>%
filter(payer_grouping != "?") %>%
select(service_line, payer_grouping) %>%
mutate(record = 1) %>%
as_tibble()
ui_tbl <- kmeans_user_item_tbl(
.data = data_tbl
, .row_input = service_line
, .col_input = payer_grouping
, .record_input = record
)
kmeans_mapped_tbl(ui_tbl)
#> # A tibble: 15 × 3
#> centers k_means glance
#> <int> <list> <list>
#> 1 1 <kmeans> <tibble [1 × 4]>
#> 2 2 <kmeans> <tibble [1 × 4]>
#> 3 3 <kmeans> <tibble [1 × 4]>
#> 4 4 <kmeans> <tibble [1 × 4]>
#> 5 5 <kmeans> <tibble [1 × 4]>
#> 6 6 <kmeans> <tibble [1 × 4]>
#> 7 7 <kmeans> <tibble [1 × 4]>
#> 8 8 <kmeans> <tibble [1 × 4]>
#> 9 9 <kmeans> <tibble [1 × 4]>
#> 10 10 <kmeans> <tibble [1 × 4]>
#> 11 11 <kmeans> <tibble [1 × 4]>
#> 12 12 <kmeans> <tibble [1 × 4]>
#> 13 13 <kmeans> <tibble [1 × 4]>
#> 14 14 <kmeans> <tibble [1 × 4]>
#> 15 15 <kmeans> <tibble [1 × 4]>