Python | Pandas.CategoricalDtype()

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

# 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)

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'])