Python | Pandas.CategoricalDtype()
Last Updated :
10 Mar, 2022
pandas.api.types.CategoricalDtype(categories = None, ordered = None) : This class is useful for specifying the type of Categorical data independent of the values, with categories and orderness.
Parameters-
categories : [index like] Unique categorization of the categories.
ordered : [boolean] If false, then the categorical is treated as unordered.
Return- Type specification for categorical data
Code:
Python3
import numpy as np
import pandas as pd
from pandas.api.types import CategoricalDtype
a = CategoricalDtype([ 'a' , 'b' , 'c' ], ordered = True )
print ("a : ", a)
b = CategoricalDtype([ 'a' , 'b' , 'c' ])
print ("\nb : ", b)
print ("\nTrue / False : ", a = = CategoricalDtype([ 'a' , 'b' , 'c' ],
ordered = False ))
c = pd.api.types.CategoricalDtype(categories = ["a","b","d","c"], ordered = True )
print ("\nType : ", c)
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Python3
c1 = pd.Series([ 'a' , 'b' , 'a' , 'e' ], dtype = c)
print ("c1 : \n", c1)
c2 = pd.DataFrame({ 'A' : list ( 'abca' ), 'B' : list ( 'bccd' )})
c3 = CategoricalDtype(categories = list ( 'abcd' ), ordered = True )
c4 = c2.astype(c3)
print ("\n c4[ 'A' ] : \n", c4[ 'A' ])
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