# NOT RUN {
## ftransform modifies and returns a data.frame
head(ftransform(airquality, Ozone = -Ozone))
head(ftransform(airquality, new = -Ozone, Temp = (Temp-32)/1.8))
head(ftransform(airquality, new = -Ozone, new2 = 1, Temp = NULL)) # Deleting Temp
head(ftransform(airquality, Ozone = NULL, Temp = NULL)) # Deleting columns
# This computes the median and standard-deviation of Ozone in each month
head(ftransform(airquality,
Ozone_Month_median = fmedian(Ozone, Month, TRA = "replace_fill"),
Ozone_Month_sd = fsd(Ozone, Month, TRA = "replace_fill")))
# Grouping by month and above/below average temperature in each month
head(ftransform(airquality, Ozone_Month_high_median =
fmedian(Ozone, list(Month, Temp > fbetween(Temp, Month)), TRA = "replace_fill")))
## Since v1.3.0 one can pass a list of columns, and there is a replacement method
head(ftransform(airquality, STD(airquality, cols = 1:3))) # Could use magrittr::`%<>%`
ftransform(airquality) <- fscale(get_vars(airquality, 1:3))
rm(airquality)
# This feature also allows to flexibly do grouped operations creating multiple new columns
head(ftransform(airquality,
fmedian(list(Wind_Month_median = Wind,
Ozone_Month_median = Ozone), Month, TRA = "replace_fill")))
# This performs 2 different multi-column grouped operations (need c() to make it one list)
head(ftransform(airquality, c(fmedian(list(Wind_Day_median = Wind,
Ozone_Day_median = Ozone), Day, TRA = "replace_fill"),
fsd(list(Wind_Month_sd = Wind,
Ozone_Month_sd = Ozone), Month, TRA = "replace_fill"))))
## settransform works like ftransform but modifies a data frame in the global environment..
airquality_c <- airquality
settransform(airquality_c, Ratio = Ozone / Temp, Ozone = NULL, Temp = NULL)
settransform(airquality_c, STD(airquality_c, cols = 1:2)) # This also works..
head(airquality_c)
rm(airquality_c)
## fcompute only returns the modified / computed columns
head(fcompute(airquality, Ozone = -Ozone))
head(fcompute(airquality, new = -Ozone, Temp = (Temp-32)/1.8))
head(fcompute(airquality, new = -Ozone, new2 = 1))
# }
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