Contents
Float Range using NumPy in Python
By default, the built-in range class deals only with integers. But, if you would like to create a range with float values, you can do so by using NumPy library.
To create a Float Range in Python, you can use numpy.arange() function. The syntax of numpy.arange() function is given below.
numpy.arange(start, stop, step, dtype=None)
where
Parameter | Description |
---|---|
start | [Optional] The start value of sequence. Default value is 0. |
stop | The end value of the sequence. The sequence will stop before reaching this value. |
step | [Optional] The difference between consecutive values in the sequence. The default step is 1. |
dtype | [Optional] The data type of the elements in the array. If not specified, NumPy will infer the data type based on the values given in the input. |
The function returns a NumPy array.
Examples
In the following examples, we create a sequence of float values using numpy.arange() function.
1. Create a Range with start=1.4, stop=2.8 in steps of 0.2
In the following program, we create a range with a specific start value of 1.4, stop value of 2.8, and a step value of 0.2.
Output
[1.4 1.6 1.8 2. 2.2 2.4 2.6]
2. Create a Range with start=1.3 and stop=9.1
In this example, we create a range with a specific start value of 1.3, and a stop value of 9.1.
Since we have not given any step value, the default step value of 1 would take effect.
Output
[1.3 2.3 3.3 4.3 5.3 6.3 7.3 8.3]
3. Iterate over Float Range
numpy.arange() returns a NumPy Array. You can iterate over this array using a For loop, as shown in the following example.
Python Program
import numpy as np
my_range = np.arange(1.3, 9.1)
for i in my_range:
print(i)
Run Code CopyOutput
1.3
2.3
3.3
4.299999999999999
5.299999999999999
6.299999999999999
7.299999999999998
8.299999999999999
Summary
In this tutorial of Python Ranges, we learned how to create a Range (a numpy array) with Float values using numpy.arange() function, with the help of examples.