Menu
What is the closest equivalent to an R Factor variable in Python pandas?
616
Categorical(val, categories = None, ordered = None, dtype = None) : It represents a categorical variable. Categorical are a pandas data type that corresponds to the categorical variables in statistics. Such variables take on a fixed and limited number of possible values.
Categoricals are a pandas data type corresponding to categorical variables in statistics. A categorical variable takes on a limited, and usually fixed, number of possible values ( categories ; levels in R). Examples are gender, social class, blood type, country affiliation, observation time or rating via Likert scales.
There are many ways in which conversion can be done, one such way is by using Pandas' integrated cut-function. Pandas' cut function is a distinguished way of converting numerical continuous data into categorical data.
Categorical. Categoricals can only take on only a limited, and usually fixed, number of possible values ( categories ). In contrast to statistical categorical variables, a Categorical might have an order, but numerical operations (additions, divisions, …) are not possible.
Encode the object as an enumerated type or categorical variable. This method is useful for obtaining a numeric representation of an array when all that matters is identifying distinct values. factorize is available as both a top-level function pandas.
This question seems to be from a year back but since it is still open here's an update. pandas has introduced a categorical dtype and it operates very similar to factors in R. Please see this link for more information:
http://pandas-docs.github.io/pandas-docs-travis/categorical.html
Reproducing a snippet from the link above showing how to create a "factor" variable in pandas.
In [1]: s = Series(["a","b","c","a"], dtype="category") In [2]: s Out[2]: 0 a 1 b 2 c 3 a dtype: category Categories (3, object): [a < b < c] If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With
