Rather than using a decimal step directly, it’s much safer to express this in terms of how many points you want. Otherwise, floating-point rounding error is likely to give you a wrong result.

Use the `linspace`

function from the NumPy library (which isn’t part of the standard library but is relatively easy to obtain). `linspace`

takes a number of points to return, and also lets you specify whether or not to include the right endpoint:

```
>>> np.linspace(0,1,11)
array([ 0. , 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1. ])
>>> np.linspace(0,1,10,endpoint=False)
array([ 0. , 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9])
```

If you really want to use a floating-point step value, use `numpy.arange`

:

```
>>> import numpy as np
>>> np.arange(0.0, 1.0, 0.1)
array([ 0. , 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9])
```

Floating-point rounding error *will* cause problems, though. Here’s a simple case where rounding error causes `arange`

to produce a length-4 array when it should only produce 3 numbers:

```
>>> numpy.arange(1, 1.3, 0.1)
array([1. , 1.1, 1.2, 1.3])
```