Nothing
## ---- message=FALSE, warning=FALSE--------------------------------------------
library(expss)
data(mtcars)
mtcars = apply_labels(mtcars,
mpg = "Miles/(US) gallon",
cyl = "Number of cylinders",
disp = "Displacement (cu.in.)",
hp = "Gross horsepower",
drat = "Rear axle ratio",
wt = "Weight (1000 lbs)",
qsec = "1/4 mile time",
vs = "Engine",
vs = c("V-engine" = 0,
"Straight engine" = 1),
am = "Transmission",
am = c("Automatic" = 0,
"Manual"=1),
gear = "Number of forward gears",
carb = "Number of carburetors"
)
## -----------------------------------------------------------------------------
nps = c(-1, 0, 1, 1, 0, 1, 1, -1)
var_lab(nps) = "Net promoter score"
val_lab(nps) = num_lab("
-1 Detractors
0 Neutralists
1 Promoters
")
## -----------------------------------------------------------------------------
var_lab(nps) # get variable label
val_lab(nps) # get value labels
# add new labels
add_val_lab(nps) = num_lab("
98 Other
99 Hard to say
")
# remove label by value
# %d% - diff, %n_d% - names diff
val_lab(nps) = val_lab(nps) %d% 98
# or, remove value by name
val_lab(nps) = val_lab(nps) %n_d% "Other"
## -----------------------------------------------------------------------------
drop_val_labs(nps)
drop_var_labs(nps)
unlab(nps)
drop_unused_labels(nps)
prepend_values(nps)
## ---- fig.height=6, fig.width=7-----------------------------------------------
with(mtcars, table(am, vs))
with(mtcars,
barplot(
table(am, vs),
beside = TRUE,
legend = TRUE)
)
## -----------------------------------------------------------------------------
# table with dimension names
use_labels(mtcars, table(am, vs))
# linear regression
use_labels(mtcars, lm(mpg ~ wt + hp + qsec)) %>% summary
# boxplot with variable labels
use_labels(mtcars, boxplot(mpg ~ am))
## ---- fig.height=6, fig.width=7-----------------------------------------------
library(ggplot2, warn.conflicts = FALSE)
use_labels(mtcars, {
# '..data' is shortcut for all 'mtcars' data.frame inside expression
ggplot(..data) +
geom_point(aes(y = mpg, x = wt, color = qsec)) +
facet_grid(factor(am) ~ factor(vs))
})
## -----------------------------------------------------------------------------
nps = c(-1, 0, 1, 1, 0, 1, 1, -1)
var_lab(nps) = "Net promoter score"
val_lab(nps) = num_lab("
-1 Detractors
0 Neutralists
1 Promoters
99 Hard to say
")
## -----------------------------------------------------------------------------
expss_disable_value_labels_support()
table(nps) # there is no labels in the result
unique(nps)
## -----------------------------------------------------------------------------
expss_enable_value_labels_support()
# table with labels but there are no label "Hard to say"
table(nps)
unique(nps)
## -----------------------------------------------------------------------------
expss_enable_value_labels_support_extreme()
# now we see "Hard to say" with zero counts
table(nps)
# weird 'unique'! There is a value 99 which is absent in 'nps'
unique(nps)
## -----------------------------------------------------------------------------
expss_enable_value_labels_support()
## -----------------------------------------------------------------------------
str(mtcars)
## -----------------------------------------------------------------------------
mtcars_subset = mtcars[1:10, ]
## -----------------------------------------------------------------------------
str(mtcars_subset)
## ---- eval = FALSE------------------------------------------------------------
# # we need to load packages strictly in this order to avoid conflicts
# library(haven)
# library(expss)
# spss_data = haven::read_spss("spss_file.sav")
# # add missing 'labelled' class
# spss_data = add_labelled_class(spss_data)
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