Turn raw numbers into a clear pie chart by learning how to prepare, format, and import your data correctly.
Before touching your data, define what you want the pie chart to show. A pie chart answers the question 'What proportion does each category contribute to the whole?' If your data does not fit this pattern — for example, if categories overlap or do not sum to a meaningful total — a different chart type may be more appropriate.
Structure your data into two columns: one for category names and one for numeric values. If your raw data is a list of individual transactions, aggregate them first — for example, sum all electronics sales into a single 'Electronics' row with a total value of 340.
Remove duplicate categories, fix typos in category names, and ensure all values are positive numbers. Check for missing values and decide how to handle them — either exclude the row or assign a default value. The cleaner your data, the more accurate the chart.
If you have many categories where some represent tiny portions (below 3-5%), merge them into a single 'Other' category. This keeps the chart readable. A pie chart with 15 tiny slivers is less useful than one with 6 clear slices.
Either type your prepared data directly into the pie chart generator or import it as a CSV file. If using CSV, ensure the file has a header row and uses comma separation. Our tool auto-detects the label and value columns on import.
After the data is loaded, verify that every category appears with the correct value. Check that the total makes sense and no data was lost during import. Add a title, set colors, and export the finished chart.
Practice what you learned with our interactive pie chart editor below. The chart is pre-filled with sample data to get you started.