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 - 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
Convert data. frame column format from character to factor The complete conversion of every character variable to factor usually happens when reading in data, e g , with stringsAsFactors = TRUE, but this is useful when say, you've read data in with read_excel() from the readxl package and want to train a random forest model that doesn't accept character variables
Pandas - make a column dtype object or Factor - Stack Overflow In pandas, how can I convert a column of a DataFrame into dtype object? Or better yet, into a factor? (For those who speak R, in Python, how do I as factor()?) Also, what's the difference between