Transposing a Vector or Matrix

By Normally Transposing a vector or matrix is method to swapped the value with each other.
Like ,
suppose we have one matrix 2*2. When we perform trasposing that time column value swapped in raw and waw value swapped in column.

Problem/Example

You need to transposing a vector or matrix.

Solution

For the transposing we use T method.

Transposing Matrix</4>

import numpy as np

# Create matrix
matrix = np.array([[1, 2, 3],
[4, 5, 6],
[7, 8, 9]])

# Transpose matrix
matrix.T

OUTPUT:

array([[1, 4, 7],
[2, 5, 8],
[3, 6, 9]])

Discussion :

Transposing is a common operation in linear algebra where the column and row indices of each element are swapped.
One nuanced point that is typically overlooked outside of a linear algebra class is that,
technically, a vector cannot be transposed because it is just a collection of values:

Transpose vector

import numpy as np

np.array([1, 2, 3, 4, 5, 6]).T

OUTPUT:

array([1, 2, 3, 4, 5, 6])

However, it is common to refer to transposing a vector as converting a row vector to
a column vector (notice the second pair of brackets) or vice versa:

Transpose vector with array

import numpy as np

np.array([[1, 2, 3, 4, 5, 6]]).T

[/code

array([,
,
,
,
,
])

Latest Blog

What is New in Android studio 3.5

Android studio 3.5 include some of the new features and behavioures changes. like, Memory Management Setting, Memory usage report,...

Application Of Various Operation Research Techniques

Application Of Various Operation Research Techniques are, Linear programming, Decision theory, Simulation, Inventory control, Network techniques and CPM