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Why does SQL Server say it can't convert a varchar to numeric?

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When SQL Server reports that it can't convert a `VARCHAR` to `NUMERIC`, it usually means that there is an attempt to perform an operation or comparison that involves converting a string (varchar) value to a numeric type, and the conversion is failing. This issue commonly arises when you're working with...
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When SQL Server reports that it can't convert a `VARCHAR` to `NUMERIC`, it usually means that there is an attempt to perform an operation or comparison that involves converting a string (varchar) value to a numeric type, and the conversion is failing. This issue commonly arises when you're working with numeric data, and there are non-numeric values in a column that's expected to contain only numeric data.

Here are some common scenarios that can lead to this error:

1. **Invalid Numeric Format:**
   If the `VARCHAR` column contains values that cannot be implicitly converted to numeric (e.g., due to non-numeric characters, commas, or other invalid numeric formats), the conversion will fail.

2. **Empty or NULL Values:**
   If the column contains empty strings or `NULL` values and you're attempting a numeric operation, this can cause a conversion error.

3. **Data Type Mismatch:**
   There might be situations where the column you're working with is actually of a numeric type, but the data type specified in your query or operation is incorrect.

To troubleshoot and resolve the issue, you can:

- Inspect the data in the column to identify non-numeric values.
- Use the `ISNUMERIC` function to identify rows that contain non-numeric values.
- Clean or correct the data by either removing non-numeric characters or replacing them with appropriate values.
- Ensure that your query is using the correct data types for numeric operations.

Here's an example of how you might use `ISNUMERIC` to identify non-numeric values:

```sql
SELECT YourColumn
FROM YourTable
WHERE ISNUMERIC(YourColumn) = 0;
```

This query will return rows where `YourColumn` contains non-numeric values.

Remember to handle potential edge cases and variations in your data appropriately. If you need further assistance, providing more details about the specific query and data involved would help in providing a more targeted solution.

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