**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.ptp() Function:**

Using the matrix.ptp() method of the Numpy module, we can obtain the peek-to-peek value i.e, is (maximum-minimum) along the axis from a specified matrix.

**Syntax:**

matrix.ptp(axis)

**Return Value:**

The peek-to-peek value from a given matrix is returned by the ptp() function.

## Numpy matrix.ptp() Function in Python

**For 2-Dimensional (2D) Matrix **

**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 arguments to it and store it in a variable
- Print the given matrix
- Pass random axis(0/1) as an argument to the ptp() function and apply it to the given matrix to get the peek-to-peek(maximum-minimum) value along the specified axis from a given matrix.
- Here 0 represents along the column, and 1 represents a row.
- Store it in another variable
- Print the peek-to-peek value along the specified axis from a given matrix.
- 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('[10, 1; 6, 3]') # Print the given matrix print("The given matrix is:\n", gvn_matrx) # Pass random axis(0/1) as an argument to the ptp() function and apply it to the given matrix # to get the peek-to-peek(maximum-minimum) value along the specified axis from a given matrix. # Here 0 represents along column, 1 represents row. # Store it in another variable rslt = gvn_matrx.ptp(1) # Print the peek-to-peek value along the specified axis from a given matrix. print("The peek-to-peek value along the specified axis from a given matrix:") print(rslt)

**Output:**

The given matrix is: [[10 1] [ 6 3]] The peek-to-peek value along the specified axis from a given matrix: [[9] [3]]

**Explanation:**

Here it prints 10-1 = 9, 6-3=3 i.e, along the row

**NOTE:**

Here 0 represents along the column, and 1 represents a row. but generally 0 = row, 1=column.

**For 3-Dimensional (3D) Matrix **

**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 arguments to it and store it in a variable
- Print the given matrix
- Pass random axis(0/1) as an argument to the ptp() function and apply it to the given matrix to get the peek-to-peek(maximum-minimum) value along the specified axis from a given matrix.
- Here 0 represents along the column, and 1 represents a row.
- Store it in another variable
- Print the peek-to-peek value along the specified axis from a given matrix.
- 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]') # Print the given matrix print("The given matrix is:\n", gvn_matrx) # Pass random axis(0/1) as an argument to the ptp() function and apply it to the given matrix # to get the peek-to-peek(maximum-minimum) value along the specified axis from a given matrix. # Here 0 represents along column, 1 represents row. # Store it in another variable rslt = gvn_matrx.ptp(0) # Print the peek-to-peek value along the specified axis from a given matrix. print("The peek-to-peek value along the specified axis from a given matrix:") print(rslt)

**Output:**

The given matrix is: [[ 2 4 1] [ 8 7 3] [10 9 5]] The peek-to-peek value along the specified axis from a given matrix: [[8 5 4]]