Arrange decomposition plot vertically

I have the following daily data series:

> library(stR)
> library(forecast)
> library(ggplot2)
> spain_daily
# A tibble: 1,096 × 2
   Date       Daily_Load
   <date>          <dbl>
 1 2022-01-01     20872.
 2 2022-01-02     22729.
 3 2022-01-03     27358.
 4 2022-01-04     28262.
 5 2022-01-05     28048.
 6 2022-01-06     24182.
 7 2022-01-07     27763.
 8 2022-01-08     26870.
 9 2022-01-09     25605.
10 2022-01-10     29879.
# ℹ 1,086 more rows
# ℹ Use `print(n = ...)` to see more rows

I can decompose the series using ggplot2:

autoplot(mstl(msts(spain_daily$Daily_Load, seasonal.periods = c(7, 365.25))))

And that results in this:

However, I would prefer to do it in base R:

fit <- AutoSTR(msts(spain_daily$Daily_Load, seasonal.periods = c(7, 365.25)))
plot(components(fit))

But I get this result:

How do I remove the two-column plots and align all the five series vertically, as in the ggplot2-based solution?

Thank you in advance.

Your call to plot(components(fit)) is actually using plot.ts under the hood. That function accepts nc= as an argument to indicate the number of columns to use.

### note the "ts" here, indicating it's using `plot.ts` underneath
class(components(fit))
# [1] "mts"    "ts"     "matrix" "array" 

I don't have spain_daily, so I'll demonstrate with taylor. The msts(...) is taken from ?msts as an example.

library(stR)
library(forecast)
library(ggplot2)
tay <- msts(taylor, seasonal.periods=c(2*24,2*24*7,2*24*365), start=2000+22/52)
autoplot(mstl(tay))
# Warning in mstl(tay) :
#   Dropping seasonal components with fewer than two full periods.

fit <- AutoSTR(tay) # this took a minute or two
plot(components(fit))

plot(components(fit), nc=1)