**NumPy Library **

NumPy is a library in python that is created to work efficiently with arrays in python. It is fast, easy to learn, and provides efficient storage. It also provides a better way of handling data for the process. We can create an n-dimensional array in NumPy. To use NumPy simply have to import it into our program and then we can easily use the functionality of NumPy in our program.

NumPy is a Python library that is frequently used for scientific and statistical analysis. NumPy arrays are grids of the same datatype’s values.

**Numpy matrix.put() Function:**

Using the matrix.put() method of the Numpy module, we can put(insert) the value by passing index and value in a given particular matrix.

**Syntax:**

matrix.put(index, value)

**Return Value:**

A new matrix (after putting values ) is returned by the put() function.

## Numpy matrix.put() Function in Python

**For 2-Dimensional (2D) Matrix (Inserting an element at Multiple Indices)**

**Approach:**

- Import numpy module using the import keyword
- Create a matrix(2-Dimensional) using the matrix() function of numpy module by passing some random 2D matrix as an argument to it and store it in a variable
- Pass the index/indices(as a tuple) and value as arguments to the put() function and apply it to the given matrix
- Here we passed multiple indices and the value gets inserted at corresponding indices of the tuple.
- Store it in another variable
- Print the given matrix after inserting an element at the multiple indices.
- The Exit of the Program.

**Below is the implementation:**

# Import numpy module using the import keyword import numpy as np # Create a matrix(2-Dimensional) using the matrix() function of numpy module by passing # some random 2D matrix as arguments to it and store it in a variable gvn_matrx = np.matrix('[2, 1; 6, 3]') # Pass the index/indices(as a tuple) and value as an argument to the put() function and apply it to the given matrix # Here we passed multiple indices and the value gets inserted at corresponding indices of the tuple. # Store it in another variable gvn_matrx.put((0, 2), 50) # Print the given matrix after inserting an element at the multiple indices print("The given matrix after inserting an element at the multiple indices:") print(gvn_matrx)

**Output:**

The given matrix after inserting an element at the multiple indices: [[50 1] [50 3]]

**Explanation:**

Here it inserts 50 at the indices 0 and 2.

**NOTE:**

The matrix indices starts from '0'

**For 3-Dimensional (3D) Matrix (Inserting an element at Single Index)**

**Approach:**

- Import numpy module using the import keyword
- Create a matrix(3-Dimensional) using the matrix() function of numpy module by passing some random 3D matrix as an argument to it and store it in a variable
- Pass the index and value as arguments to the put() function and apply it to the given matrix
- Here we passed a single index and the value gets inserted at that corresponding index.
- Store it in another variable
- Print the given matrix after inserting an element at the given index.
- The Exit of the Program.

**Below is the implementation:**

# Import numpy module using the import keyword import numpy as np # Create a matrix(3-Dimensional) using the matrix() function of numpy module by passing # some random 3D matrix as an argument to it and store it in a variable gvn_matrx = np.matrix('[2, 4, 1; 8, 7, 3; 10, 9, 5]') # Pass the index and value as arguments to the put() function and apply it to the given matrix # Here we passed single index and the value gets inserted at that corresponding index. # Store it in another variable gvn_matrx.put((4), 100) # Print the given matrix after inserting an element at the given index. print("The given matrix after inserting an element {100} at the given index{4}:") print(gvn_matrx)

**Output:**

The given matrix after inserting an element {100} at the given index{4}: [[ 2 4 1] [ 8 100 3] [ 10 9 5]]