Values analysis is typically the first type of analysis that an analyst performs on relatively unfamiliar data. It helps determine the nature and overall quality of the data—for example, whether it is categorical or continuously numeric, how many null values it contains, and so on.
You can apply Values analysis to columns of any numeric type, including date types. Displayed values vary with column data type.
Given a table name and one or more column names, Values analysis provides a count of the following for each column:
- Total rows
- Rows with non-NULL values
- Rows with NULL values
- Rows with value 0 *
- Rows with positive values *
- Rows with negative values *
- Rows with blank values
- [Optional] Rows with unique values
* These counts are always zero for nonnumeric columns. A string like "000" is not equivalent to the numeric value 0.