HEATMAPSTER — TUTORIAL EXAMPLE DATA
Edition: 17 October 2026
All example records are fictional.

Use these files to follow the HeatMapster tutorials and check your results. You can open the workbook or import the individual CSV files. The workbook contains six datasets, each with a header row and a clearly defined import range.

FILES BY TUTORIAL

H01 — First heatmap from Excel: Ready_matrix worksheet; Ready_matrix.csv or Ready_matrix.tsv for alternatives.
H02 — Sales from transactions: Sales_records worksheet or Sales_records.csv.
H03 — Actual vs budget: Actual_budget worksheet or Actual_budget.csv.
H04 — Busy days and hours: Activity_4weeks.csv, or the matching worksheet.
H05 — PNG, PDF and PowerPoint export: the sales project saved in H02; recreate it from Sales_records if needed.
H06 — Refresh an Excel source: a working copy of the workbook named Sales_refresh.xlsx, using its Sales_records worksheet.
H07 — Correlation matrix: Correlation worksheet or Correlation.csv.
H08 — Confusion matrix: Classification worksheet or Classification.csv.

GETTING STARTED

For Excel, use Home → Import Data, select the workbook and choose the worksheet and range listed below. For a ready-made matrix, you can also copy its cells and use Paste Data. For transaction or observation data, choose Raw Table and then select the appropriate analysis.

CSV files use UTF-8, a comma separator, headers in the first row and a decimal point. Blank entries represent missing values. The Excel import ranges contain no merged cells or extra title rows.

READY_MATRIX — PRODUCT SCORES

Workbook range: Ready_matrix!A1:E5
Files: Ready_matrix.csv; Ready_matrix.tsv

Use Matrix, with the first row as column headers and the first column as row labels. The table contains 4 products, 4 regions, 14 numeric scores and 2 missing scores. Desk/North = 90. Chair/South and Lamp/East should remain missing, rather than zero. These demonstration scores are neither currency amounts nor percentages.

SALES_RECORDS — SALES BY PRODUCT AND REGION

Workbook range: Sales_records!A1:C9
File: Sales_records.csv

Use Raw Table, then Matrix Builder. Set Rows = Region, Columns = Product, Calculate = Sum and Values = Sales. North/Desk = 1550, East/Lamp = 600 and total sales = 4870. Six category combinations have no records; keep No data distinct from a recorded value of zero.

You can also follow this example using Try a Sample → Sales by Product and Region.

ACTUAL_BUDGET — COMPARE ACTUAL VALUES WITH BUDGET

Workbook range: Actual_budget!A1:D7
File: Actual_budget.csv

Use Raw Table, then Compare / Variance with Two value columns. Set Department as Rows and Period as Columns. Choose Actual for Current / Actual and Budget for Baseline / Budget, with Sum for both measures.

For Q1 and Q2 respectively, Difference is +20 and −20 for Operations, +60 and −30 for Sales, and +10 and +10 for Support. Operations/Q1 has a Percentage Change of 4% and a Ratio of 1.04. The source field is named Period; Q1 and Q2 are its quarter labels. The example does not assign a currency or specify whether the values measure revenue or cost.

ACTIVITY_4WEEKS — TICKETS BY WEEKDAY AND HOUR

Workbook range: Activity_4weeks!A1:C1133
File: Activity_4weeks.csv

Use Raw Table. Timestamp must be Date & Time, using yyyy-MM-dd HH:mm:ss when importing the CSV. Each row represents one ticket created.

This example is defined as a complete fictional event log for 7 September–4 October 2026, covering four full weeks. Timestamps use one consistent local clock. HeatMapster groups the imported values without converting their time zone.

In Time & Calendar Heatmap, choose Timestamp, Count and Day of Week × Hour. Use Monday as the first day, one-hour buckets and Include Saturday and Sunday. Use all records in the file. All 1132 records should contribute, with no invalid timestamps.

Monday at 09:00 contains 48 tickets across the four Mondays. The 7 × 24 grid has 60 time buckets with events and 108 without events. For this explicitly complete example, you can choose Appearance → Missing Cells → Empty combinations: → Replace with 0. With your own data, retain No data if you cannot establish that the log is complete. Region is an additional sample field; this example focuses on time patterns.

CORRELATION — RELATIONSHIPS BETWEEN NUMERIC VARIABLES

Workbook range: Correlation!A1:F9
File: Correlation.csv

Use Raw Table, then Correlation Matrix. Select all five numeric variables: Metric A, Metric B, Metric C, Metric D and Constant. Use Pearson, Pairwise and a minimum of 3 rows per pair for this small demonstration. Choose Full matrix and keep the diagonal visible.

Expected Pearson results: A/B ≈ 0.98 with n = 8; A/C = −1 with n = 8; A/D ≈ 0.96 with n = 7. Metric D has one missing reading. Constant has no variation, so its correlations are N/A, including its diagonal cell. Switching to Spearman gives A/B = 1.00.

The minimum-row setting controls whether a coefficient is shown; it does not guarantee statistical reliability. Correlation alone does not establish cause and effect.

CLASSIFICATION — INSPECT PREDICTION ERRORS

Workbook range: Classification!A1:B10
File: Classification.csv

Use Raw Table, then Confusion Matrix. Set Actual class = Actual and Predicted class = Predicted. Use No weight, First seen for class order and Counts for display mode.

Actual classes appear in rows and predicted classes in columns. In the order Approved, Review, Rejected, the count rows are [2, 1, 0], [0, 2, 1] and [1, 0, 2]. Six of nine predictions are correct, giving an accuracy of approximately 66.67%.

The Approved → Review cell contains one record whose actual class was Approved but whose prediction was Review. Double-click it to inspect the record. In Row percentages, the Approved row shows approximately 66.67% Approved, 33.33% Review and 0% Rejected.

REFRESH — UPDATE THE SAME SOURCE FILE

Make a working copy of the workbook named Sales_refresh.xlsx. Import its Sales_records sheet, range A1:C9, build the sales matrix and save a HeatMapster project before trying Refresh Source.

In that same working source file, change Sales_records!C2 from 1200 to 1500, then save and close the workbook in Excel. Then choose Home → Refresh Source, review the prepared update and select Apply Refresh. North/Desk becomes 1850 and total sales becomes 5170; the source still contains 8 records. Save the HeatMapster project again to keep the updated state.

The folders refresh/01_original and refresh/02_updated contain CSV copies of the values before and after the change. They are reference files for checking your results. The tutorial updates one source file; it does not switch between those folders. Keep the original example workbook so you can repeat the exercise.

Pasted data and built-in samples have no external file to refresh. For this exercise, import the working workbook directly.

MORE HELP

The five small examples use the same values as the corresponding built-in HeatMapster samples. Activity_4weeks provides a larger fictional dataset for the time tutorial.

HeatMapster: https://definedbytes.com/heatmapster/
Written tutorials: https://definedbytes.com/heatmapster-tutorials/
