How to Generate Sequence Arrays in Python with Numpy arange

Let’s see how to generate sequence array using Numpy arange function in Python.

Sequence arrays are a type of Numpy array that can be used to store evenly spaced values. They are often used to represent data such as time series, temperature readings, and stock prices.

Using an arange method

There is Numpy arange function which is very useful for generating sequence array.

The numpy.arange() function can be used to generate sequence arrays. The syntax for the numpy.arange() function is as follows:

numpy.arange(start, stop, step)

The start argument specifies the starting value of the sequence. The stop argument specifies the ending value of the sequence. The step argument specifies the step size.

For example, the following code generates a sequence array of numbers from 100 to 700 with a step size of 100:

import numpy as np

sequence_array = np.arange(start=100, stop=700, step=100)
print(sequence_array)

As you can see the only thing is to set start, stop and step. Numpy arange does the rest.

Generating Sequence Arrays with Different Step Sizes

You can also use negative step sizes to generate sequence arrays that go from the ending value to the starting value.

For example, the following code generates a sequence array of numbers from 100 to 1 with a step size of -2:

import numpy as np

sequence_array = np.arange(100, 1, -2)
print(sequence_array)

The following code generates a sequence array of numbers from 1 to 0 with a step size of -0.1:

import numpy as np

sequence_array = np.arange(1, 0, -0.1)
print(sequence_array)

The numpy.arange() function is a versatile tool that can be used to generate sequence arrays of different types. It is a valuable function for any Python programmer who needs to work with sequence data.

Key Takeaways

• The `numpy.arange()` function can be used to generate sequence arrays in Python.
• The `numpy.arange()` function takes three arguments: start, stop, and step.
• The default step size is 1.
• You can use negative step sizes to generate sequence arrays that go from the ending value to the starting value.