View source: R/extract_states.R
add_states | R Documentation |
add_states()
brings states to a time series dataset. It uses the
States.dataset
to add states to the dataset
. The States.dataset
must at
least contain the same variables as the dataset
grouping, as well as a
start and end time. Beware if both datasets operate on different time zones
and consider to set force.tz = TRUE
.
add_states(
dataset,
States.dataset,
Datetime.colname = Datetime,
start.colname = start,
end.colname = end,
force.tz = FALSE,
leave.out = c("duration", "epoch")
)
dataset |
A light logger dataset. Needs to be a dataframe. |
States.dataset |
A light logger dataset. Needs to be a dataframe. This
dataset must contain the same variables as the |
Datetime.colname |
The column that contains the datetime. Needs to be a
|
start.colname , end.colname |
The columns that contain the start and end
time. Need to be |
force.tz |
If |
leave.out |
A character vector of columns that should not be carried
over to the |
Beware if columns in the dataset
and States.dataset
have the same name
(other then grouping variables). The underlying function,
dplyr::left_join()
will mark the columns in the dataset
with a suffix
.x
, and in the States.dataset
with a suffix .y
.
a modified dataset
with the states added. The states are added as
new columns to the dataset
. The columns are named after the columns in
the States.dataset
, except for the start and end times, which are
removed.
states <-
sample.data.environment |>
filter_Date(length = "1 day") |>
extract_states(Daylight, MEDI > 1000)
states |> head(2)
#add states to a dataset and plot them - as we only looked for states on the
# first day (see above), only the first day will show up in the plot
sample.data.environment |>
filter_Date(length = "2 day") |>
add_states(states) |>
gg_days() |>
gg_state(Daylight)
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