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  2. 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

  3. But annoyingly, there is nothing to handle the factor -> numeric conversion. As an extension of Joshua Ulrich's answer, I would suggest to overcome this omission with the definition of your own idiomatic function: as.double.factor <- function(x) {as.numeric(levels(x))[x]}

  4. From my understanding, the currently accepted answer only changes the order of the factor levels, not the actual labels (i.e., how the levels of the factor are called). To illustrate the difference between levels and labels , consider the following example:

  5. I would like to change the format (class) of some columns of my data.frame object (mydf) from charactor to factor. I don't want to do this when I'm reading the text file by read.table() function. ...

  6. when to use factor () when plotting with ggplot in R?

    stackoverflow.com/questions/15070738

    ggplot(mtcars) + geom_point(aes(x=mpg, y=drat, colour=gear)) This communicates a continuum of points, and it's thus not ideal for a set of separate possibilities. (Indeed, once you get to five or six possibilities the colors can be hard to distinguish from each other). When gears is treated like a factor, the colors are chosen to be ...

  7. 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. –

  8. 3. If you wanted to forego the dplyr, you can split into lists. df <- split(df, list(df[[obs1]], df[[obs2]]) If you wanted the count, you just create an sapply or lapply call to run through the lists and get the count of each one. Or literally any other function you want. answered Dec 12, 2015 at 1:08. black_sheep07.

  9. Very short : levels are the input, labels are the output in the factor() function. A factor has only a level attribute, which is set by the labels argument in the factor() function. This is different from the concept of labels in statistical packages like SPSS, and can be confusing in the beginning. What you do in this line of code.

  10. r - Replace <NA> in a factor column - Stack Overflow

    stackoverflow.com/questions/39126537

    I had similar issues and I want to add what I consider the most pragmatic (and also tidy) solution: Convert the column to a character column, use mutate and a simple ifelse-statement to change the NA values to what you want the factor level to be (I have chosen "None"), convert it back to a factor column:

  11. Convert all data frame character columns to factors

    stackoverflow.com/questions/20637360

    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?