The two data classes
ts_tbl, used by
ricu to represent ICU
patient data, consist of a
data.table alongside some meta data. This
includes marking columns that have special meaning and for data
representing measurements ordered in time, the step size. The following
utility functions can be used to extract columns and column names with
special meaning, as well as query a
ts_tbl object regarding its time
series related meta data.
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Object to query
The following functions can be used to query an object for columns or column names that represent a distinct aspect of the data:
id_vars(): ID variables are one or more column names with the
interaction of corresponding columns identifying a grouping of the data.
Most commonly this is some sort of patient identifier.
id_var(): This function either fails or returns a string and can
therefore be used in case only a single column provides grouping
id_col(): Again, in case only a single column provides grouping
information, this column can be extracted using this function.
index_var(): Suitable for use as index variable is a column that encodes
a temporal ordering of observations as
vector. Only a single column can be marked as index variable and this
function queries a
ts_tbl object for its name.
index_col(): similarly to
id_col(), this function extracts the column
with the given designation. As a
ts_tbl object is required to have
exactly one column marked as index, this function always returns for
ts_tbl objects (and fails for
win_tbl objects, this returns the name of the column
encoding the data validity interval.
dur_col(): Similarly to
index_col(), this returns the
vector corresponding to the
ts_tbl objects, meta variables represent the union
of ID and index variables (for
win_tbl, this also includes the
dur_var()), while for
id_tbl objects meta variables consist pf ID
data_vars(): Data variables on the other hand are all columns that are
not meta variables.
data_var(): Similarly to
id_var(), this function either returns the
name of a single data variable or fails.
data_col(): Building on
data_var(), in situations where only a single
data variable is present, it is returned or if multiple data column
exists, an error is thrown.
time_vars(): Time variables are all columns in an object inheriting
data.frame that are of type
difftime. Therefore in a
ts_tbl object the index
column is one of (potentially) several time variables. For a
dur_var() is not among the
interval(): The time series interval length is represented a scalar
time_unit(): The time unit of the time series interval, represented by
a string such as "hours" or "mins" (see
time_step(): The time series step size represented by a numeric value
in the unit as returned by
Mostly column names as character vectors, in case of
time_unit() of length 1, else of variable
data_col() return table
columns as vectors, while
interval() returns a scalar valued
time_step() a number.
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tbl <- id_tbl(a = rep(1:2, each = 5), b = rep(1:5, 2), c = rnorm(10), id_vars = c("a", "b")) id_vars(tbl) tryCatch(id_col(tbl), error = function(...) "no luck") data_vars(tbl) data_col(tbl) tmp <- as_id_tbl(tbl, id_vars = "a") id_vars(tmp) id_col(tmp) tbl <- ts_tbl(a = rep(1:2, each = 5), b = hours(rep(1:5, 2)), c = rnorm(10)) index_var(tbl) index_col(tbl) identical(index_var(tbl), time_vars(tbl)) interval(tbl) time_unit(tbl) time_step(tbl)
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