# What does x[x < 2] = 0 mean in Python?

I came across some code with a line similar to

```
x[x<2]=0
```

Playing around with variations, I am still stuck on what this syntax does.

Examples:

```
>>> x = [1,2,3,4,5]
>>> x[x<2]
1
>>> x[x<3]
1
>>> x[x>2]
2
>>> x[x<2]=0
>>> x
[0, 2, 3, 4, 5]
```

This only makes sense with **NumPy arrays**. The behavior with lists is useless, and specific to Python 2 (not Python 3). You may want to double-check if the original object was indeed a NumPy array (see further below) and not a list.

But in your code here, x is a simple list.

Since

```
x < 2
```

is False i.e 0, therefore

`x[x<2]`

is `x[0]`

`x[0]`

gets changed.

Conversely, `x[x>2]`

is `x[True]`

or `x[1]`

So, `x[1]`

gets changed.

**Why does this happen?**

The rules for comparison are:

When you order two strings or two numeric types the ordering is done in the expected way (lexicographic ordering for string, numeric ordering for integers).

When you order a numeric and a non-numeric type, the numeric type comes first.

When you order two incompatible types where neither is numeric, they are ordered by the alphabetical order of their typenames:

So, we have the following order

numeric < list < string < tuple

See the accepted answer for *How does Python compare string and int?*.

**If x is a NumPy array** , then the syntax makes more sense because of **boolean array indexing**. In that case, `x < 2`

isn't a boolean at all; it's an array of booleans representing whether each element of `x`

was less than 2. `x[x < 2] = 0`

then selects the elements of `x`

that were less than 2 and sets those cells to 0. See *Indexing*.

```
>>> x = np.array([1., -1., -2., 3])
>>> x < 0
array([False, True, True, False], dtype=bool)
>>> x[x < 0] += 20 # All elements < 0 get increased by 20
>>> x
array([ 1., 19., 18., 3.]) # Only elements < 0 are affected
```

From: stackoverflow.com/q/36603042

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