This article describes how to go from a crosstab where missing data results in an inconsistent **Column Sample Size** per row...

...to a table that adjusts the bottom **Column Sample Size** to ignore the missing data:

## Requirements

- A crosstab with a
**Nominal**,**Binary - Multi**or**Binary - Multi (Compact)**in the rows and**Column Sample Size**available in**STATISTICS > Below**. - Missing data in your table whereby the number of respondents that have complete data for all the rows results in a lower
**Column Sample Size**in**STATISTICS > Below**.

Please note this requires the **Data Stories** module or a **Displayr **license.

## Method

1. Select your table.

2. Go to Data** > RULES** on the **object inspector**.

3. To apply the rule, select the **Plus (+) > Modify Whole Table or Plot > Ignore Missing Values in Column Sample Size in Statistics Below > OK**.

Note, this rule affects only the **Column Sample Size** and **Weighted Column Sample Size** statistics in** STATISTICS > Below** and has no effect on any other statistics in the table.

## Next