How to Normalize Data in R: Techniques & Best Practices

How to Normalize Data in R: Techniques & Best Practices

Key points Data normalization is transforming the values of a variable or a set of variables so that they have a standard scale or range. Different ways to normalize data in R include z-score normalization, min-max normalization, range normalization, decimal scaling, and max_scale normalization . Z-score normalization transforms each value by subtracting its mean and dividing it by its standard deviation. The result is a new variable with a mean of zero and a standard deviation of one. Min-max normalization transforms each value by subtracting its minimum and dividing by its range (maximum-minimum). The result is a new variable with a minimum of zero and a maximum of one. Range normalization transforms each value by dividing by its range (maximum-minimum). The result is a new variable that has a range of one. Decimal scaling transforms each value by dividing by a power of 10 that is equal to or larger than the maximum absolute value of the variable. The result is a new variable ranging from …