I am new to loops, and I am trying to iterate over all items in a list, and I need to generate the values between 0 and 2 with a given step value. I have tried to use the "range" function, but cannot get it to work.

The end result should look something like this (doesn’t have to be in a pandas dataframe, just for illustrative purposes):

```
import pandas as pd
import numpy as np
data = {'range_0.5' : [0,0.5,1,1.5,2, np.nan, np.nan, np.nan, np.nan],
'range_0.25' : [0,0.25,0.5,0.75,1,1.25,1.5,1.75,2]}
df = pd.DataFrame(data)
df
```

Here is what I have tried:

```
import numpy
x = []
seq = [0.5, 0.25, 0.125, 0.0625, 0.03125, 0.015625, 0.0078125, 0.00390625]
for i in seq:
x = range(0, 2, i)
```

The following error is thrown:

```
TypeError Traceback (most recent call last)
Input In [10], in <cell line: 1>()
1 for i in seq:
----> 2 x = range(0, 2, i)
TypeError: 'float' object cannot be interpreted as an integer
```

How can I properly create my loop?

### >Solution :

## np.arange()

You can use `numpy.arange()`

which supports floats as step values.

```
import numpy as np
for step in [0.5, 0.25]:
print([i for i in np.arange(0, 2, step))
```

Expected output:

```
[0.0, 0.5, 1.0, 1.5]
[0.0, 0.25, 0.5, 0.75, 1.0, 1.25, 1.5, 1.75]
```

To include `2`

just add the step value once again:

```
for step in [0.5, 0.25]:
print([i for i in np.arange(0, 2 + step, step)])
```

Expected output:

```
[0.0, 0.5, 1.0, 1.5, 2.0]
[0.0, 0.25, 0.5, 0.75, 1.0, 1.25, 1.5, 1.75, 2.0]
```

## np.linspace()

Alternatively you can use `np.linspace()`

:

This has the ability to include the endpoint using `endpoint=True`

;

```
for step in [0.5, 0.25]:
print([i for i in np.linspace(0, 2, int(2 // step) + 1, endpoint=True)])
```

Expected output:

```
[0.0, 0.5, 1.0, 1.5, 2.0]
[0.0, 0.25, 0.5, 0.75, 1.0, 1.25, 1.5, 1.75, 2.0]
```