## Pythonic way to replace list values with upper and lower bound (clipping)?

Question

I want to replace outliners from a list. Therefore I define a upper and lower bound. Now every value above `upper_bound`

and under `lower_bound`

is replaced with the bound value. My approach was to do this in two steps using a numpy array.

Now I wonder if it's possible to do this in one step, as I guess it could improve performance and readability.

*Is there a shorter way to do this?*

```
import numpy as np
lowerBound, upperBound = 3, 7
arr = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
arr[arr > upperBound] = upperBound
arr[arr < lowerBound] = lowerBound
# [3 3 3 3 4 5 6 7 7 7]
print(arr)
```

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## Answers to Pythonic way to replace list values with upper and lower bound (clipping)? ( 2 )

You can use

`numpy.clip`

:For an alternative that doesn't rely on

`numpy`

, you could always doIf you just wanted to set an upper bound, you could of course write

`arr = [min(x, upper_bound) for x in arr]`

. Or similarly if you just wanted a lower bound, you'd use`max`

instead.Here, I've just applied both operations, written together.

Edit:Here's a slightly more in-depth explanation:Given an element

`x`

of the array (and assuming that your`upper_bound`

is at least as big as your`lower_bound`

!), you'll have one of three cases:i)

`x < lower_bound`

ii)

`x > upper_bound`

iii)

`lower_bound <= x <= upper_bound`

.In case (i), the

`max/min`

expression first evaluates to`max(lower_bound, x)`

, which then resolves to`lower_bound`

.In case (ii), the expression first becomes

`max(lower_bound, upper_bound)`

, which then becomes`upper_bound`

.In case (iii), we get

`max(lower_bound, x)`

which resolves to just`x`

.In all three cases, the output is what we want.