Create list of floats python

To create a range of floats in Python, use a list comprehension.

For example, to create a range of floats from 0 to 1 with 1/10th interval:

rng = [x / 10 for x in range(0, 10)]
print(rng)

Output:

[0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]

In this guide, you will see some alternative approaches to creating a range of floats in Python.

Python range() Function Does Not Work for Floats

In Python, the built-in range() function can be used to generate a range of values between m and n.

numbers = range(1, 6) # 1, 2, 3, 4, 5

However, the range is supposed to consist of integers only.

This means you cannot have a range() call like this:

numbers = range(0.1, 1.0)

The Solution: Divide Each Number in the Range

To overcome this issue, you can produce a range and divide each number in that range to get a range of floats.

For example, let’s generate a list that represents floats between range 0.0 and 1.0:

numbers = range(0, 10)

float_nums = []

for number in numbers:
    f = number / 10
    float_nums.append(f)
    
print(float_nums)

Output:

[0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]

This for loop can be expressed in a smoother way using a list comprehension:

rng = [x / 10 for x in range(0, 10)]
print(rng)

However, it gets a bit tricky when you want to produce other types of ranges.

For example, producing a list of numbers from 1.5 to 4.25, with 0.25 intervals using a for loop already requires some thinking. Needless to mention when the numbers are not evenly divisible.

This is where NumPy library can help you.

NumPy’s arange() Function to Create a Range of Floats

Another option to produce a range of floats is to use the NumPy module’s arange() function.

This function follows the syntax:

numpy.arange(start, stop, step)

Where:

• start is the starting value of the range.
• stop specifies the end of the range. The stop is not included in the range!
• step determines how big steps to take when generating the range.

In case you do not have NumPy installed, you can install it with PIP by running the following command in the command line:

pip install numpy

Now that you have the library, you can use the arange() function to generate a range of floats:

import numpy as np
rng = np.arange(0.0, 1.0, 0.1)

print(rng)

Output:

[ 0. ,  0.1,  0.2,  0.3,  0.4,  0.5,  0.6,  0.7,  0.8,  0.9]

Notice how this range is exclusive as it does not include the end value 1.0 in the range.

To make the range inclusive, add one step size to the stop parameter.

For example, to generate a range of floats from 0.0 to 1.0:

import numpy as np

start = 0.0
stop = 1.0
step = 0.1

rng = np.arange(start, stop + step, step)

print(rng)

Output:

[0.  0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1. ]

Problem with the arange() Function

The problem with the arange() approach is the floating-point rounding errors.

For example, this creates an array of four values (1, 1.1, 1.2, 1.3), even though it should produce only three values (1, 1.1, 1.2):

import numpy as np
rng = np.arange(1, 1.3, 0.1)

print(rng)

Output:

[1. , 1.1, 1.2, 1.3]

NumPy linspace() Function for a Range of Floats

To overcome the floating-point rounding issues with the numpy’s arange() function, use numpy’s linspace() function instead.

Notice, however, that this function behaves differently. It asks how many numbers you want to linearly space between a start and an end value.

It follows this syntax:

numpy.linspace(start, stop, nvalues)

Where:

• start is the starting value of the range.
• stop is the ending value of the range.
• nvalues is the number of values to generate in-between start and stop.

For example, let’s generate values from 0.0 to 1.0 with 0.1 intervals. This means the start is 0 and the end is 1. Also, you need to realize you want 11 values in total.

Here is how it looks in code:

import numpy as np
rng = np.linspace(0, 1, 11)

print(rng)

Output:

[0.  0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1. ]

Conclusion

Today you learned three ways to create a range of floats in Python:

• List comprehension.
• NumPy’s arange() function.
• NumPy’s linspace() function.

Thanks for reading. Happy coding!

Further Reading

Python Tricks and Tips

Python Interview Questions

Python Advanced Features