Advanced Calculator Inputs
Example Data Table
| Region | Category | Sales | Profit | Quantity | Customer |
|---|---|---|---|---|---|
| East | Furniture | 1200 | 180 | 3 | Ali |
| West | Technology | 2320 | 510 | 6 | Zain |
| North | Office Supplies | 310 | 48 | 10 | Bilal |
Formula Used
This calculator follows the structure of level of detail expressions. A fixed expression uses only the selected LOD dimensions. An include expression adds LOD dimensions to the current view dimensions. An exclude expression removes selected LOD dimensions from the current view. A table calculation ignores dimensions and uses the full filtered dataset.
How to Use This Calculator
Paste your CSV data into the dataset box. Keep column names in the first row. Enter view dimensions as comma separated names. Enter LOD dimensions in the same way. Choose the expression type, measure column, and aggregation method. Add an optional filter when you want to restrict the records. Press the calculate button. The result appears above the form and below the header.
Level of Detail Calculations Guide
Understanding LOD Logic
Level of detail calculations help analysts control the exact grain of a summary. They are useful when the chart view does not match the question being asked. A view may show category totals, while the analysis may need region totals, customer averages, or one overall benchmark. This calculator gives a simple way to test that logic before building a dashboard.
Why Fixed Detail Matters
Fixed detail ignores the visible view and uses only the selected fixed dimensions. This is helpful for stable benchmarks. You can calculate sales by region even when the visible view also includes category. The output keeps the chosen grain steady. This makes comparisons easier and avoids accidental over grouping.
Include and Exclude Detail
Include detail makes the grain more detailed than the view. It adds another dimension before aggregation. Exclude detail does the opposite. It removes a dimension from the view before aggregation. These choices are important when summaries must follow a business question rather than the current table layout.
Mathematical Use
Each result is built by grouping rows first. The selected aggregation is then applied to each group. Sum, average, minimum, maximum, count, distinct count, median, and weighted average are supported. Weighted average uses a measure and a weight column. This is useful for rates, scores, margins, and weighted performance values.
Practical Reporting
The exported CSV is useful for spreadsheets. The PDF export is useful for reports and review notes. You can also print the result directly. Always check that column names match your dataset. Also review filters before trusting totals. A small filter mismatch can change every group value. Clean source data gives better calculations and more reliable dashboard planning.
FAQs
What is a level of detail calculation?
It is a calculation that controls the grouping level before aggregation. It helps you summarize data at a chosen grain.
What does FIXED mean?
FIXED uses only the dimensions you enter as LOD dimensions. It ignores extra dimensions from the current view.
What does INCLUDE mean?
INCLUDE adds the LOD dimensions to the view dimensions. It creates a more detailed grouping before calculating the measure.
What does EXCLUDE mean?
EXCLUDE removes selected dimensions from the view grouping. It creates a broader summary than the displayed view.
Can I use my own dataset?
Yes. Paste CSV data with headers in the first row. Then use exact column names in the calculator inputs.
How does weighted average work?
It multiplies each measure value by its weight. Then it divides the weighted sum by the total weight.
Why are my results empty?
Your filter may remove all rows, or a column name may not match. Check spelling, spaces, and CSV headers.
Can I export the result?
Yes. Use the CSV button for spreadsheet data. Use the PDF button for a clean report copy.