# How to generate evenly spaced sample in Numpy?

Let’s learn How to generate evenly spaced sample in Numpy Python library. We will use Numpy linspace method for that purpose.

To generate evenly spaced sample within given interval you may need linpsace function. It generates the array and takes starting point, end point and the number of needed elements.

## More on Numpy linspace method

The linspace method in Numpy can be used to generate evenly spaced sample within given interval. It takes starting point, end point and the number of needed elements as its parameters.

The syntax for the linspace method is as follows:

```linspace(start, end, num=5)
```

Where:

```start is the starting point of the interval
end is the end point of the interval
num is the number of elements to be generated
```

## The simpliest example

Let’s see how to generate even sample from 0 to 100. I will need 5 elements in my sample array.

```import numpy as np

cities = ["New York", "London", "Austin", "Chicago", "Quebec"]
my_linspace_array = np.linspace(0, 100, len(cities))
print(f"This is my sample array generated using linspace method: "
f"\n {my_linspace_array}")

```

```import numpy as np

my_array = ([0, 20, 25, 40, 100])
my_linspace_array = np.linspace(min(my_array), max(my_array), len(my_array))
print(f"This is my sample array generated using linspace method: "
f"\n {my_linspace_array}")

```

The result is the same. Linspace interval is fully parametrized by my_array list.

## Other parameters of Numpy linspace method

The linspace method in Numpy has several other parameters that can be used to customize the output.

endpoint : If set to True, the end point will be included in the output array. The default value is True.
dtype : The data type of the output array. The default value is float.
retstep : If set to True, the step size between elements in the output array will be returned as well. The default value is False.
```import numpy as np