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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
Convert existing dataframe variable to factor in Tidyverse When you have an existing character variable in a dataframe, is there an easy method for converting that variable to a factor using the tidyverse format? For example, the 2nd line of code below won't reorder the factor levels, but the last line will
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?
How to reorder factor levels in a tidy way? - Stack Overflow A couple comments: reordering a factor is modifying a data column The dplyr command to modify a data column is mutate All arrange does is re-order rows, this has no effect on the levels of the factor and hence no effect on the order of a legend or axis in ggplot All factors have an order for their levels The difference between an ordered = TRUE factor and a regular factor is how the
r - Changing factor levels with dplyr mutate - Stack Overflow 19 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:
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 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
r - summarizing counts of a factor with dplyr - Stack Overflow I want to group a data frame by a column (owner) and output a new data frame that has counts of each type of a factor at each observation The real data frame is fairly large, and there are 10 diff
r - ggplot2: Reorder items in a legend - Stack Overflow (2) I cannot find a question about ordering (of axis or legend elements) in ggplot2 that is not completely resolved by the use of factor( , levels=) When you define the factor and specify the ordering of said factors using levels=, then ggplot2 tends to honor that specification