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()`

.

## Usage

```
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, 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")`

## Examples

```
library(ggplot2)
ggplot(heights,
aes(x = year,
y = height_cm,
group = country)) +
geom_line() +
facet_strata()
ggplot(heights,
aes(x = year,
y = height_cm,
group = country)) +
geom_line() +
facet_wrap(~continent)
ggplot(heights,
aes(x = year,
y = height_cm,
group = country)) +
geom_line() +
facet_strata(along = year)
# \donttest{
library(dplyr)
heights %>%
key_slope(height_cm ~ year) %>%
right_join(heights, ., by = "country") %>%
ggplot(aes(x = year,
y = height_cm)) +
geom_line(aes(group = country)) +
geom_smooth(method = "lm") +
facet_strata(along = .slope_year)
#> `geom_smooth()` using formula = 'y ~ x'
# }
```