Facet data into groups to facilitate exploration

This function requires a tbl_ts object, which can be created with tsibble::as_tsibble(). Under the hood, facet_strata is powered by stratify_keys().

facet_strata(
  n_strata = 12,
  along = NULL,
  fun = mean,
  nrow = NULL,
  ncol = NULL,
  scales = "fixed",
  shrink = TRUE,
  strip.position = "top"
)

Arguments

n_strata	number of groups to create
along	variable to stratify along. This groups by each key and then takes a summary statistic (by default, the mean). It then arranges by the mean value for each key and assigns the n_strata groups.
fun	summary function. Default is mean.
nrow	Number of rows and columns.
ncol	Number of rows and columns.
scales	Should scales be fixed ("fixed", the default), free ("free"), or free in one dimension ("free_x", "free_y")?
shrink	If TRUE, will shrink scales to fit output of statistics, not raw data. If FALSE, will be range of raw data before statistical summary.
strip.position	By default, the labels are displayed on the top of the plot. Using strip.position it is possible to place the labels on either of the four sides by setting strip.position = c("top", "bottom", "left", "right")

Value

a ggplot object

Examples

library(ggplot2)
ggplot(heights,
       aes(x = year,
           y = height_cm,
           group = country)) +
  geom_line() +
  facet_strata()
  
if (FALSE) {

ggplot(heights,
       aes(x = year,
           y = height_cm,
           group = country)) +
  geom_line() +
  facet_wrap(~continent)

ggplot(wages,
       aes(x = xp,
           y = ln_wages,
           group = id)) +
  geom_line() +
  facet_strata(along = xp_since_ged)

library(dplyr)
wages %>%
  key_slope(ln_wages ~ xp) %>%
  right_join(wages, ., by = "id") %>%
  ggplot(aes(x = xp,
             y = ln_wages)) +
  geom_line(aes(group = id)) +
  geom_smooth(method = "lm") + 
  facet_strata(along = .slope_xp)
}