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Subsetting-functions usually drop value and variable labels from
subsetted data frames (if the original data frame has value and variable
label attributes). This function copies these value and variable
labels back to subsetted data frames that have been subsetted, for instance,
with subset
.
copy_labels(df_new, df_origin = NULL, ...)
The new, subsetted data frame.
The original data frame where the subset (df_new
) stems from;
use NULL
, if value and variable labels from df_new
should be removed.
Optional, unquoted names of variables that should be selected for
further processing. Required, if x
is a data frame (and no
vector) and only selected variables from x
should be processed.
You may also use functions like :
or tidyselect's select-helpers.
See 'Examples'.
Returns df_new
with either removed value and variable label attributes
(if df_origin = NULL
) or with copied value and variable label
attributes (if df_origin
was the original subsetted data frame).
# NOT RUN {
data(efc)
# create subset - drops label attributes
efc.sub <- subset(efc, subset = e16sex == 1, select = c(4:8))
str(efc.sub)
# copy back attributes from original dataframe
efc.sub <- copy_labels(efc.sub, efc)
str(efc.sub)
# remove all labels
efc.sub <- copy_labels(efc.sub)
str(efc.sub)
# create subset - drops label attributes
efc.sub <- subset(efc, subset = e16sex == 1, select = c(4:8))
if (require("dplyr")) {
# create subset with dplyr's select - attributes are preserved
efc.sub2 <- select(efc, c160age, e42dep, neg_c_7, c82cop1, c84cop3)
# copy labels from those columns that are available
copy_labels(efc.sub, efc.sub2) %>% str()
}
# copy labels from only some columns
str(copy_labels(efc.sub, efc, e42dep))
str(copy_labels(efc.sub, efc, -e17age))
# }
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