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Return a new array with the same shape as a given array but change the default type in Numpy
To return a new array with the same shape and type as a given array, use the numpy.empty_like() method in Python Numpy. It returns the array of uninitialized (arbitrary) data with the same shape and type as prototype. The 1st parameter here is the shape and data-type of prototype(array-like) that define these same attributes of the returned array. The 2nd parameter is the dtype i.e. the data-type we want for the resultant array.
The order overrides the memory layout of the result. ‘C’ means C-order, ‘F’ means F-order, ‘A’ means ‘F’ if prototype is Fortran contiguous, ‘C’ otherwise. ‘K’ means match the layout of prototype as closely as possible. The shape overrides the shape of the result. If order=’K’ and the number of dimensions is unchanged, will try to keep order, otherwise, order=’C’ is implied. The overrides parameter overrides the data type of the result.
The subok parameter, if True, then the newly created array will use the sub-class type of prototype, otherwise it will be a base-class array. Defaults to True.
Steps
At first, import the required library −
import numpy as np
Create a new array using the numpy.array() method in Python Numpy −
arr = np.array([[35.7, 56.2, 66.4], [88.2, 73.7, 98.3]])
Display the array −
print("Array...
",arr)Get the type of the array −
print("
Array type...
", arr.dtype)
Get the dimensions of the Array −
print("
Array Dimensions...
", arr.ndim)To return a new array with the same shape and type as a given array, use the numpy.empty_like() method in Python Numpy −
newArr = np.empty_like(arr, dtype = int)
print("
New Array..
", newArr)Get the type of the new array −
print("
New Array type...
", newArr.dtype)
Get the dimensions of the new array −
print("
New Array Dimensions...
", newArr.ndim)Example
import numpy as np
# Create a new array using the numpy.array() method in Python Numpy
arr = np.array([[35.7, 56.2, 66.4], [88.2, 73.7, 98.3]])
# Display the array
print("Array...
",arr)
# Get the type of the array
print("
Array type...
", arr.dtype)
# Get the dimensions of the Array
print("
Array Dimensions...
", arr.ndim)
# To return a new array with the same shape and type as a given array, use the numpy.empty_like() method in Python Numpy
# It returns the array of uninitialized (arbitrary) data with the same shape and type as prototype.
# The 1st parameter here is the shape and data-type of prototype(array-like) that define these same attributes of the returned array.
# The 2nd parameter is the dtype i.e. the data-type we want for the resultant array
newArr = np.empty_like(arr, dtype = int)
print("
New Array..
", newArr)
# Get the type of the new array
print("
New Array type...
", newArr.dtype)
# Get the dimensions of the new array
print("
New Array Dimensions...
", newArr.ndim)Output
Array... [[35.7 56.2 66.4] [88.2 73.7 98.3]] Array type... float64 Array Dimensions... 2 New Array.. [[4630221145643784602 4633106264155068826 4634372901550266778] [4635906940173339853 4634886593382763725 4636617664489534259]] New Array type... int64 New Array Dimensions... 2
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