numpy.dtype.kind() function – Python

numpy.dtype.subdtype() function – Python

Last Updated : 18 Jun, 2020

numpy.dtype.subdtype() function returns Tuple(item_dtype, shape) if this dtype describes a sub-array, and None otherwise.

Syntax : numpy.dtype.subdtype(type) type : [dtype] The input data-type. Return : Return Tuple(item_dtype, shape) if this dtype describes a sub-array, and None otherwise.

Code #1 :

Python3

# Python program explaining
# numpy.dtype.subdtype() function
       
# importing numpy as geek 
import numpy as geek 
   
x = geek.dtype('8f')
 
gfg = x.subdtype
 
print (gfg)

Output :

(dtype('float32'), (8, ))

Code #2 :

Python3

# Python program explaining
# numpy.dtype.subdtype() function
       
# importing numpy as geek 
import numpy as geek 
   
x = geek.dtype('i2')
 
gfg = x.subdtype
 
print (gfg)

Output :

None

numpy.dtype.kind() function – Python

sanjoy_62

Improve

Article Tags :

Practice Tags :

python

Similar Reads

numpy.result_type() function â€“ Python

numpy.result_type() function returns the type that results from applying the NumPy type promotion rules to the arguments. NumPy type promotion by example : Suppose calculating 3*arr, where arr is an array of 32-bit floats, intuitively should result in a 32-bit float output. If the 3 is a 32-bit inte

numpy.dtype.base() function - Python

numpy.dtype.base() function returns dtype for the base element of the subarrays, regardless of their dimension or shape. Syntax : numpy.dtype.base() Return : Returns data type of the base element. Code #1 : Python3 # Python program explaining # numpy.dtype.base() function # importing numpy as geek i

numpy.dtype.kind() function â€“ Python

numpy.dtype.kind() function determine the character code by identifying the general kind of data. Syntax : numpy.dtype.kind(type) Parameters : type : [dtype] The input data-type. Return : Return the character code by identifying the general kind of data. Code #1 : Python3 # Python program explaining

numpy.typename() function â€“ Python

numpy.typename() function return a description for the given data type code. Syntax : numpy.typename(char) Parameters : char : [str] Data type code. Return : [str] Description of the input data type code. Code #1 : Python3 # Python program explaining # numpy.typename() function # importing numpy as

numpy.sctype2char() function â€“ Python

numpy.sctype2char() function return the string representation of a scalar dtype. Syntax : numpy.sctype2char(sctype) Parameters : sctype : [scalar dtype or object] If a sctype is a scalar dtype, the corresponding string character is returned. If an object, sctype2char tries to infer its scalar type a

numpy.common_type() function â€“ Python

numpy.common_type() function return a scalar type which is common to the input arrays. Syntax : numpy.common_type(arrays) Parameters : array1, array2, .... : [ndarrays] Input arrays. Return : [dtype] Return the data type which is common to the input arrays. Code #1 : Python3 # Python program explain

numpy.find_common_type() function - Python

numpy.find_common_type() function determine common type following standard coercion rules. Syntax : numpy.find_common_type(array_types, scalar_types) Parameters : array_types : [sequence] A list of dtypes or dtype convertible objects representing arrays. scalar_types : [sequence] A list of dtypes or

numpy.maximum_sctype() function â€“ Python

numpy.maximum_sctype() function return the scalar type of highest precision of the same kind as the input. Syntax : numpy.maximum_sctype(t) Parameters : t : [dtype or dtype specifier] The input data type. This can be a dtype object or an object that is convertible to a dtype. Return : [dtype] The hi

type() function in Python

The type() function is mostly used for debugging purposes. Two different types of arguments can be passed to type() function, single and three arguments. If a single argument type(obj) is passed, it returns the type of the given object. If three argument types (object, bases, dict) are passed, it re

numpy.promote_types() function â€“ Python

numpy.promote_types() function is a symmetric function which returns the data type with the smallest size and smallest scalar kind to which both type1 and type2 may be safely cast. The returned data type is always in native byte order. Syntax : numpy.promote_types(type1, type2) Parameters : type1 :