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r - 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
r - Changing factor levels with dplyr mutate - Stack Overflow 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 - 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 different factors Here is some example input:
Filter factor levels in R using dplyr - Stack Overflow You can easily convert a factor into an integer and then use conditions on it Just replace your filter statement with: filter(as integer(Epsilon)>2) More generally, if you have a vector of indices level you want to eliminate, you can try:
r - How to reorder factor levels in a tidy way? - Stack Overflow 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 contrasts are set up in a model
How to change the number of replicas of a Kafka topic? Option "[replication-factor]" can't be used with option"[alter]" It is funny that you can change number of partitions on the fly (which is often hugely destructive action when done in runtime), but cannot increase replication factor, which should be transparent But remember, it is 0 10, not 10 0
Subset a dataframe by multiple factor levels - Stack Overflow How can I avoid using a loop to subset a dataframe based on multiple factor levels? In the following example my desired output is a dataframe The dataframe should contain the rows of the original dataframe where the value in "Code" equals one of the values in "selected" Working example:
r - Mean by factor by level - Stack Overflow Maybe this is simple but I can't find answer on web I have problem with mean calculation by factors by level My data looks typicaly: factor, value a,1 a,2 b,1 b,1 b,1 c,1 I want to get vector A