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This article shows you how to use R language and Python to achieve factor variables and classification recoding, concise and easy to understand, absolutely can make you shine, through the detailed introduction of this article I hope you can gain something.

Today we introduce the use of factor variables in data types in R and Python.

Factor variables are important variables used to describe classified objects in data structure. It corresponds to a large number of classified things with practical significance in real life.

Such as age, gender, position, hobbies, astrology, etc.

In addition to its special position in data structure, factor variables often play an important role in describing the important dimensional characteristics of a certain thing in the process of data visualization and data analysis and modeling. Its significance is extraordinary, and it cannot be ignored either in the process of data processing or in the later analysis and modeling.

Generally speaking, according to the actual meaning of the dimensions described, factor variables can generally be subdivided into disordered factors (no specific order between categories, equal levels) and ordered factors (there is a conventional order among categories, such as age group, professional title, education, weight, etc.).

In statistics, variables are divided into four categories: fixed variables, ordered variables, distance variables and ratio variables. The constant class and constant ratio variables correspond to the factor variables (disordered and ordered) that we are going to cover today.

Factor variables contain more descriptive information than pure qualitative variables (text variables), but less information than numerical variables (fixed distance variables and fixed ratio variables).

Thus, in principle, numerical variables can be converted into factor variables, and factor variables can be converted into text variables, but the above order is irreversible (variables with more information can be converted to variable types with less information, but variables with less information cannot increase information content).

In R, factor is usually used to generate factor variables directly, and we only need a vector (in principle, it can be textual or numeric, but usually in the practical sense, what is transformed should be a categorical text variable with multiple categories).

factor(x, levels,labels=levels,ordered=)

In the above parameters, x is the variable we will convert, levels is the factor level to be set (optional parameter, if omitted, the non-repeating object in the vector will automatically be the factor level), labels is the factor label (optional parameter, corresponding to the above factor level, if set, the corresponding factor label will be displayed when printing, if omitted, the same as the factor level, use the non-repeating value [i.e. category] in the vector as the label), ordered is a logical parameter, set whether to sort the factor levels.

vector%str()

Factor Variable Recode in R Language

If you have a metric that you need to convert into a piecewise factor variable, you can do this with the cut function.

scale

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