The best answers to the question “Removing nan values from an array” in the category Dev.

__QUESTION__:

I want to figure out how to remove nan values from my array. My array looks something like this:

```
x = [1400, 1500, 1600, nan, nan, nan ,1700] #Not in this exact configuration
```

How can I remove the `nan`

values from `x`

?

__ANSWER__:

```
filter(lambda v: v==v, x)
```

works both for lists and numpy array

since v!=v only for NaN

__ANSWER__:

If you’re using numpy for your arrays, you can also use

```
x = x[numpy.logical_not(numpy.isnan(x))]
```

Equivalently

```
x = x[~numpy.isnan(x)]
```

[Thanks to chbrown for the added shorthand]

**Explanation**

The inner function, `numpy.isnan`

returns a boolean/logical array which has the value `True`

everywhere that `x`

is not-a-number. As we want the opposite, we use the logical-not operator, `~`

to get an array with `True`

s everywhere that `x`

**is** a valid number.

Lastly we use this logical array to index into the original array `x`

, to retrieve just the non-NaN values.

__ANSWER__:

For me the answer by @jmetz didn’t work, however using pandas isnull() did.

```
x = x[~pd.isnull(x)]
```

__ANSWER__:

Try this:

```
import math
print [value for value in x if not math.isnan(value)]
```

For more, read on List Comprehensions.