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# What is the numpy.trapz() function in NumPy? Onyejiaku Theophilus Chidalu

Grokking Modern System Design Interview for Engineers & Managers

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### Overview

The numpy.trapz() function in NumPy is used to perform integration along a given axis by using the composite trapezoidal rule.

### Syntax

numpy.trapz(y, x=None, dx=1.0, axis=- 1)
Syntax for the numpy.trapz() function

### Parameters

The numpy.trapz() function takes the following parameter values:

• y: This is the input array to be integrated. This is a required parameter.
• x: This is the given sample points that corresponds to the y values. This is an optional parameter.
• dx: This is the spacing provided between the sample points when x is None. The default value is 1. This is an optional parameter.
• axis: This represents the angle along which the integration is done.

### Example

import numpy as np

# creating the input array to be integrated
myarray = np.array([1,2,3])

# creating the sample points
x = np.array([4, 6, 8])

# implementing the numpy.trapz() function
intarray = np.trapz(myarray, x)

print(intarray)
Implementing the numpy.trapz() function

### Explanation

• Line 1: We import the numpy module.
• Line 4: We create an input array myarray using the array() function.
• Line 7: We create an array x containing the sample points using the array() function.
• Line 10: We implement the numpy.trapz() function on the arrays and assign the result to a variable intarray.
• Line 12: We print the variable intarray.

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function
numpy
python
communitycreator

CONTRIBUTOR Onyejiaku Theophilus Chidalu

Grokking Modern System Design Interview for Engineers & Managers

Ace your System Design Interview and take your career to the next level. Learn to handle the design of applications like Netflix, Quora, Facebook, Uber, and many more in a 45-min interview. Learn the RESHADED framework for architecting web-scale applications by determining requirements, constraints, and assumptions before diving into a step-by-step design process.

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