# List.RemoveNulls

Updated on

List.RemoveNulls is a Power Query M function that removes all occurrences of “null” values in a list. The function returns a modified list with the null values removed.

Compatible with: Power BI Service Power BI Desktop Excel Microsoft 365

## Syntax

``List.RemoveNulls( list as list ) as list``

## Description

The List.RemoveNulls function eliminates all instances of “null” values. If your list doesn’t have any “null” values to begin with, the function returns the original list, untouched.

## Examples

Let’s say you have a list of numbers, but some of the entries are “null,” which could interfere with any calculations you might want to perform. Here’s how you can remove those pesky “null” values:

``````// Output: { 1, 2, 0, 1, 2 }
List.RemoveNulls( { 1, null, 2, null, 0, 1, 2 } )``````

In this example, the function takes the original list and returns a new one, stripped of any “null” values.

### When No Null Values Are Present

What if your list is already clean, with no “null” values? Well, the function won’t make any changes. It will simply return the original list.

``````// Output: { 1, 2, 4, 5 }
List.RemoveNulls( { 1, 2, 4, 5 } )``````

### Real-World Application: Cleaning Up Sales Data

Imagine you have a list of monthly sales figures, and some months have “null” values due to incomplete data entry. You want to compute the average sales value, but null values skew the average calculation. Using `List.RemoveNulls`, you can easily clean up the list to perform accurate calculations like averages or sums.

``````let
CleanList = List.RemoveNulls( { 1, null, 2, null, 0, 1, 2 } ), // Output: { 1, 2, 0, 1, 2 }
ListAvg = List.Average( CleanList)                             // Output 1.2
in
ListAvg``````

In this example, we first use `List.RemoveNulls` to get rid of any “null” values. Then, we calculate the average of the cleaned-up list using `List.Average`. The result is a more accurate average sales figure.

By understanding how to effectively use the `List.RemoveNulls` function, you can ensure that your data is clean and ready for analysis.