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Python | Pandas.CategoricalDtype()

  • Last Updated : 21 Sep, 2018

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 categorisation of the categories.
ordered : [boolean] If false, then the categorical is treated as unordered.

Return- Type specification for categorical data

Code:




# Python code explaining 
# numpy.pandas.CategoricalDtype()
     
# importing libraries
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)






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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