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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
- Pandas - make a column dtype object or Factor - Stack Overflow
Factor and Categorical are the same, as far as I know I think it was initially called Factor, and then changed to Categorical To convert to Categorical maybe you can use pandas Categorical from_array, something like this:
- 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
- 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:
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