TidyRawData | R Documentation |
Tidies a data frame, by applying subets, weights, removing duplicate variables, and dealing with missing values.
TidyRawData(
data,
as.numeric = FALSE,
as.binary = FALSE,
subset = NULL,
weights = NULL,
missing = "Exclude cases with missing data",
error.if.insufficient.obs = TRUE,
remove.missing.levels = TRUE,
extract.common.lab.prefix = FALSE,
auto.correct.class = FALSE
)
data |
A |
as.numeric |
If TRUE, converts factors into numeric variables. |
as.binary |
If |
subset |
An optional vector specifying a subset of
observations to be used in the fitting process, or, the name of
a variable in |
weights |
An optional vector of sampling weights, or, the name
of a variable in |
missing |
character; One of |
error.if.insufficient.obs |
Throw an error if there are more variables than observations. |
remove.missing.levels |
Logical; whether levels are removed if they do not occur in the observed data. |
extract.common.lab.prefix |
logical; if true,
|
auto.correct.class |
If |
A data.frame
containing the filtered raw data, which
has an attribute called "weights"
, containing the
(filtered) vector of weights. If
extract.common.lab.prefix
is TRUE
and a common
label prefix is found, it will be return in an attribute called
"label.prefix"
.
ExtractCommonPrefixFromLabels
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