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A categorical variable takes on a limited, and usually fixed, number of possible values (categories; levels in R). Factor and Categorical are the same, as far as I know. I think it was initially called Factor, and then changed to Categorical. To convert to Categorical maybe you can use pandas.Categorical.from_array, something like this: pandas.Series.factorize¶ Series. factorize (sort = False, na_sentinel =-1) [source] ¶ 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. A factor with the associated value labels as factor levels. If x is a data frame, the complete data frame x will be returned, where variables specified in are coerced to factors; if is not specified, applies to all variables in the data frame.

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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] Share. Improve this answer. answered Nov 19 '14 at 17:46. as_label () converts (replaces) values of a variable (also of factors or character vectors) with their associated value labels.

As factor pandas

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As factor pandas

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As factor 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] Share. Improve this answer.
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As factor pandas

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Sum has simple parameters. 90% of the time you’ll just be using ‘axis’ but it’s worth learning a few more. axis – Axis to sum on.

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Pandas’ Series and DataFrame objects are powerful tools for exploring and analyzing data. Part of their power comes from a multifaceted approach to combining separate datasets.

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