Sort, Filter, and Validate Spreadsheet Data

1. Introduction

Sorting and filtering help answer focused questions without changing the source records. They are also common sources of accidental damage: sorting only one column can disconnect values that belong to the same observation.

2. Understand the concept

Treat a table row as one complete record. Sort the whole table, filter on explicit criteria, and make sure hidden rows are not mistaken for deleted records. Data validation can restrict new entries; duplicate checks should use the actual business key rather than every column by default.

3. Syntax and interpretation

Filter: Status = "Complete" and Region = "North"
Sort: Order Date ascending, then Order ID ascending
Duplicate key: Customer ID + Order Date + Order Number

A composite key may identify an event when no single column is unique. Confirm the key definition with the data owner.

4. Apply it to an analysis

Inspect a dataset safely with filters, consistent sorting, data validation, and duplicate checks. Start with a small, known example and state what each row or value represents. After the transformation, check row counts, types, keys, and units against the original data. If an assumption fails, stop and investigate instead of presenting the output as a valid result.

5. Common mistakes

• Sorting a single column rather than expanding the selection to all record columns.
• Deleting duplicates without keeping a review copy or confirming the key.

6. Practice task

A row is an order line and orders can contain several lines. Is Order ID alone a valid unique row key?

7. One possible solution

Not necessarily. Use a line identifier or a composite key such as Order ID plus Line Number, depending on the source schema.

8. Summary and next step

Inspect a dataset safely with filters, consistent sorting, data validation, and duplicate checks. Continue to the next course section and apply this foundation to a different analytics tool or workflow.