Preparing Data for Pivot Tables
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What Is a Pivot Table?
A Pivot Table is a tool that lets you quickly summarize large amounts of data. Instead of manually filtering, sorting, or writing complex formulas, a Pivot Table lets you:
- Calculate totals;
- Count records;
- Compare categories;
- Analyze trends;
- Group dates;
- Filter dynamically.
For example, from a dataset of hundreds of sales transactions, you can instantly answer: total sales by region, sales by product category, monthly revenue trend, top-performing product.
A Pivot Table reorganizes data without changing the original dataset. A regular Excel table stores raw transactions. A Pivot Table summarizes and reorganizes that data for analysis.
Why Data Structure Matters
Pivot Tables only work reliably when your data follows a simple table structure. Each row must represent one record (one transaction). Each column must represent one field (Date, Product, Region, Sales, etc.). Before building a Pivot Table, quickly check four things:
- No empty rows inside the dataset;
- Headers are present in the first row;
- Numeric fields contain real numbers;
- Dates use one consistent format.
Data preparation becomes especially important after importing data from external sources (CSV files, databases, web pages), where numbers and dates are often formatted incorrectly.
Prepare the dataset so it can be used for a Pivot Table.
Do the following:
- Remove the empty row inside the dataset;
- Convert Sales values stored as text into numbers;
- Standardize the Date format to YYYY-MM-DD (replace / with -);
- Fix the missing Date value by setting it to 2025-01-13.
Do NOT create a Pivot Table yet.
Workbook Reference
Download the workbook for this chapter to complete the task.
You can also download a version of the same workbook that includes the solution.
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