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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
- 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?
- r - Re-ordering factor levels in data frame - Stack Overflow
Re-ordering factor levels in data frame [duplicate] Asked 12 years, 3 months ago Modified 4 years, 2 months ago Viewed 255k times
- 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
- 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
- How to Find the Branching Factor of a Tree - Stack Overflow
The branching factor is one characteristic of a node next to depth and gives a clue how complex a tree gets For example, for the GO Game on a 19x19 board, the branching factor on the first level is 361, after 4 more moves at depth 4 you end up having 10 billion nodes (possible moves) Source: An Introduction To Artificial Intelligence, Janet
- r - Variance Inflation Factor in Python - Stack Overflow
I'm trying to calculate the variance inflation factor (VIF) for each column in a simple dataset in python: a b c d 1 2 4 4 1 2 6 3 2 3 7 4 3 2 8 5 4 1 9 4 I have
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