Forcats cheat sheet

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R uses factors to handle categorical variables, variables that have a fixed and known set of possible values. Factors are also helpful for reordering character vectors to improve display. The goal of the forcats package is to provide a suite of tools that solve common problems with factors, including changing the order of levels or the values. Some examples include:. You can learn more about each of these in vignette "forcats".

Forcats cheat sheet

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The goal of the forcats package is to provide a suite of useful tools that solve common problems with factors. Factors are useful when you have categorical data, variables that have a fixed and known set of values, and when you want to display character vectors in non-alphabetical order. If you want to learn more, the best place to start is the chapter on factors in R for Data Science. This is a case of an unordered categorical variable where we want it ordered by its frequency. To understand why we need to make a brief digression to discuss NA s in values vs. NA s in levels. You can include it in the values of the factor; it does not appear in the levels and is. This is how missing values are encoded in a factor by default:.

Forcats cheat sheet

R uses factors to handle categorical variables, variables that have a fixed and known set of possible values. Factors are also helpful for reordering character vectors to improve display. The goal of the forcats package is to provide a suite of tools that solve common problems with factors, including changing the order of levels or the values. Some examples include:. You can learn more about each of these in vignette "forcats". If you want to learn more about other approaches to working with factors and categorical data, I recommend Wrangling categorical data in R , by Amelia McNamara and Nicholas Horton.

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