When exploring factor 2 intolinear factors, it's essential to consider various aspects and implications. Why use as.factor () instead of just factor () - Stack Overflow. ‘factor(x, exclude = NULL)’ applied to a factor without ‘NA’s is a no-operation unless there are unused levels: in that case, a factor with the reduced level set is returned. ‘as.factor’ coerces its argument to a factor. It is an abbreviated (sometimes faster) form of ‘factor’.
Performance: as.factor > factor when input is a factor The word "no-operation" is a bit ambiguous ... r - list all factor levels of a data.frame - Stack Overflow. with dplyr::glimpse(data) I get more values, but no infos about number/values of factor-levels. Is there an automatic way to get all level informations of all factor vars in a data.frame?
Moreover, r - How to convert a factor to integer\numeric without loss of .... See the Warning section of ?factor: In particular, as.numeric applied to a factor is meaningless, and may happen by implicit coercion. In relation to this, to transform a factor f to approximately its original numeric values, as.numeric(levels(f))[f] is recommended and slightly more efficient than as.numeric(as.character(f)).
The FAQ on R has similar advice. Convert all data frame character columns to factors. Given a (pre-existing) data frame that has columns of various types, what is the simplest way to convert all its character columns to factors, without affecting any columns of other types? How to force R to use a specified factor level as reference in a .... It's important to note that, when creating the factor from b you can specify the ordering of the levels using factor(b, levels = c(3,1,2,4,5)). Do this in a data processing step outside the lm() call though.
My answer below uses the relevel() function so you can create a factor and then shift the reference level around to suit as you need to. From another angle, r - Re-ordering factor levels in data frame - Stack Overflow. when to use factor () when plotting with ggplot in R?.
Furthermore, ggplot(mtcars) + geom_point(aes(x=mpg, y=drat, colour=factor(gear))) Is the general rule to use factor when the variable being used to determine the shape/size/colour is discrete, and not continuous? Or is there another use of factor in this context? It seems like the first command can be made like the second with the right legend, even without factor.
edit: I get this when I use the ... From another angle, colors - Colouring plot by factor in R - Stack Overflow. Using R's built in plot functionality Using R's built in plot functionality to get a plot colored by a factor and an associated legend is a 4-step process, and it's a little more technical than using ggplot2. First, we will make a colorRampPallete function. Equally important, colorRampPallete() returns a new function that will generate a list of colors. r - Convert factor to integer - Stack Overflow.
Does anyone know of a way to coerce a factor into an integer?
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