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Interpret the input as a matrix in Numpy
To Interpret the input as a matrix, use the numpy.asmatrix() method in Python Numpy. Unlike matrix, asmatrix does not make a copy if the input is already a matrix or an ndarray. Equivalent to matrix(data, copy=False).
NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. It supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries.
Steps
At first, import the required library −
import numpy as np
Create a 2d array −
arr = np.array([[36, 36, 78, 88], [92, 81, 98, 45], [22, 67, 54, 69 ], [69, 80, 80, 99]])
Displaying our array −
print("Array...
",arr)
Get the datatype −
print("
Array datatype...
",arr.dtype)
Get the dimensions of the Arra −
print("
Array Dimensions...
",arr.ndim)
Get the shape of the Array −
print("
Our Array Shape...
",arr.shape)
Get the number of elements of the Array −
print("
Elements in the Array...
",arr.size)
To Interpret the input as a matrix, use the numpy.asmatrix() method in Python Numpy −
res = np.asmatrix(arr) print("
Result...
",res)
Set some values −
arr[0,2] = 99 arr[1,1] = 199 arr[2,1] = 299
Display the updated matrix −
print("
Updated Matrix...
",arr)
Example
import numpy as np # Create a 2d array arr = np.array([[36, 36, 78, 88], [92, 81, 98, 45], [22, 67, 54, 69], [69, 80, 80, 99]]) # Displaying our array print("Array...
",arr) # Get the datatype print("
Array datatype...
",arr.dtype) # Get the dimensions of the Array print("
Array Dimensions...
",arr.ndim) # Get the shape of the Array print("
Our Array Shape...
",arr.shape) # Get the number of elements of the Array print("
Elements in the Array...
",arr.size) # To Interpret the input as a matrix, use the numpy.asmatrix() method in Python Numpy res = np.asmatrix(arr) print("
Result...
",res) # Set some values arr[0,2] = 99 arr[1,1] = 199 arr[2,1] = 299 # Display the updated matrix print("
Updated Matrix...
",arr)
Output
Array... [[36 36 78 88] [92 81 98 45] [22 67 54 69] [69 80 80 99]] Array datatype... int64 Array Dimensions... 2 Our Array Shape... (4, 4) Elements in the Array... 16 Result... [[36 36 78 88] [92 81 98 45] [22 67 54 69] [69 80 80 99]] Updated Matrix... [[ 36 36 99 88] [ 92 199 98 45] [ 22 299 54 69] [ 69 80 80 99]]