Home / Statistical Tools / Analysis Tools / Piechart / Preparing Your Data
Preparing Your Data¶
Quantum XL is flexible about data layout. This page explains how different data types behave in pie charts and helps you prepare your data correctly.
How Data Types Work¶
The table below shows what happens when you assign each column type to each role in the Pie Chart dialog. Click a numbered badge to see an example using that configuration.
| Data Column | ||||||
|---|---|---|---|---|---|---|
| Nominal | Continuous | Integer | Count | DateTime | ||
| Frequency Column | None | Slice size = count of each unique category 12 | Treats continuous data as Nominal (see Nominal column) | Treats integer data as Nominal (see Nominal column) | Slice name = column header; slice size = sum of values | Treats DateTime data as Nominal (see Nominal column) |
| Nominal | — | |||||
| Continuous | Slice size = sum of frequency for each unique category 4 | Treats continuous data as Nominal (see Nominal column) | Treats integer data as Nominal (see Nominal column) | Slice name = column header; slice size = sum of (value × frequency) | Treats DateTime data as Nominal (see Nominal column) | |
| Integer | Slice size = sum of frequency for each unique category | Treats continuous data as Nominal (see Nominal column) | Treats integer data as Nominal (see Nominal column) | Slice name = column header; slice size = sum of (value × frequency) | Treats DateTime data as Nominal (see Nominal column) | |
| Count | Slice size = sum of frequency for each unique category 3 | Treats continuous data as Nominal (see Nominal column) | Treats integer data as Nominal (see Nominal column) | Slice name = column header; slice size = sum of (value × frequency) | Treats DateTime data as Nominal (see Nominal column) | |
| DateTime | — | |||||
— indicates this frequency type is not available for selection
Examples¶
1 Quick Start — Count occurrences of each category
2 Multiple Categories — Analyze multiple category columns
3 Count Frequency — Use pre-aggregated counts
4 Continuous Frequency — Sum measurement values (revenue, cost) for each category
GroupBy — Compare segments side by side
Data Layout Options¶
Raw Data (One Row Per Observation)¶
Best for most situations. Each row represents a single event or observation.
| Department | Revenue |
|---|---|
| Sales | 245.78 |
| Engineering | 89.32 |
| Sales | 187.45 |
| Marketing | 52.16 |
When you select only the Department column (no frequency), Quantum XL counts occurrences: Sales appears twice, Engineering once, Marketing once.
When you select Department as Data Column and Revenue as Frequency, Quantum XL sums the revenue: Sales = $433.23, Engineering = $89.32, Marketing = $52.16.
Pre-Aggregated Data (Counts Already Calculated)¶
Use when your data has already been summarized.
| Product | Units Sold |
|---|---|
| Widget A | 540 |
| Widget B | 210 |
| Widget C | 78 |
Select Product as Data Column and Units Sold as Frequency. Each row becomes one slice with the specified count.
Common Mistakes¶
Avoid These Issues
- Forgetting to check Frequency — If your data is pre-aggregated with counts, you must check the count column under Frequency Data. Without it, Quantum XL counts occurrences of each numeric value as a category.
- Missing data — Empty cells in the category column are excluded from analysis.