Home / Statistical Tools / Analysis Tools / Pareto / Preparing Your Data
Preparing Your Data¶
Quantum XL is flexible about data layout. This page explains how different data types behave in Pareto charts and helps you prepare your data correctly.
Negative Values in Pareto Analysis
Traditional Pareto charts are designed for non-negative data such as counts or costs. Quantum XL extends this capability by allowing negative values in continuous frequency analysis, enabling more comprehensive financial analysis where returns, refunds, or adjustments need to be factored into category rankings.
How Data Types Work¶
The table below shows what happens when you assign each column type to each role in the Pareto dialog. Click a numbered badge to see an example using that configuration.
| Data Column | ||||||
|---|---|---|---|---|---|---|
| Nominal | Continuous | Integer | Count | DateTime | ||
| Frequency Column | None | Bar height = count of each unique category 12 | Treats continuous data as Nominal (see Nominal column) | Treats integer data as Nominal (see Nominal column) | Bar name = column header; bar height = sum of values | Treats DateTime data as Nominal (see Nominal column) |
| Nominal | — | |||||
| Continuous | Bar height = sum of frequency for each unique category 4 | Treats continuous data as Nominal (see Nominal column) | Treats integer data as Nominal (see Nominal column) | Bar name = column header; bar height = sum of (value × frequency) | Treats DateTime data as Nominal (see Nominal column) | |
| Integer | Bar height = sum of frequency for each unique category | Treats continuous data as Nominal (see Nominal column) | Treats integer data as Nominal (see Nominal column) | Bar name = column header; bar height = sum of (value × frequency) | Treats DateTime data as Nominal (see Nominal column) | |
| Count | Bar height = sum of frequency for each unique category 3 | Treats continuous data as Nominal (see Nominal column) | Treats integer data as Nominal (see Nominal column) | Bar name = column header; bar height = 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 (cost, time) 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.
| Defect Type | Cost |
|---|---|
| Scratch | 15 |
| Dent | 45 |
| Scratch | 12 |
| Crack | 120 |
When you select only the Defect Type column (no frequency), Quantum XL counts occurrences: Scratch appears twice, Dent once, Crack once.
When you select Defect Type as Data Column and Cost as Frequency, Quantum XL sums the costs: Scratch = $27, Dent = $45, Crack = $120.
Pre-Aggregated Data (Counts Already Calculated)¶
Use when your data has already been summarized.
| Defect Type | Count |
|---|---|
| Scratch | 47 |
| Dent | 23 |
| Crack | 8 |
Select Defect Type as Data Column and Count as Frequency. Each row becomes one bar with the specified count.
Common Mistakes¶
Avoid These Issues
- Wrong column type — Ensure your category columns are set to Nominal, not Continuous. Continuous data used as categories creates too many bars (one per unique value).
- Forgetting to check Frequency — If your data is pre-aggregated with counts, you must check the count column under Frequency Data. Otherwise, Quantum XL counts rows (each category would show as 1).
- Missing data — Empty cells in the category column are excluded from analysis.