How to Combine Multiple Spreadsheets Into One Map
Teams often keep customers, facilities, events, and service locations in separate files. Combining them is useful only when the merged table preserves where each row came from.
This guide turns the workflow into a repeatable process and includes a live example you can inspect before using your own data.
How to use the live example
Start by scanning the overall distribution, then hover over individual points to compare their attributes. Use the legend and map controls to separate categories and inspect areas where several locations overlap. The example is intentionally small enough to understand quickly while preserving the fields needed for a realistic workflow.
Download the sample CSV below the article if you want to inspect its structure. Replace the example rows with your own locations while keeping the column headings that support the analysis. Before sharing the result, compare the number of source rows with the number of mapped points and review any location that appears outside the expected area.
Choose a common schema
Create a shared set of columns such as Location ID, Name, Address, Latitude, Longitude, Type, Source, and Updated At. Rename equivalent columns before appending rows.
Add a Source column to every file. It becomes a filter, legend category, and troubleshooting aid after the data is combined.
Append rows safely
Use stable IDs to detect duplicates across files. If two sources describe the same location, establish a precedence rule instead of silently keeping both.
Normalize dates, numeric fields, and category labels. A value stored as “West” in one file and “Western” in another will become two map categories.
Design the combined map
Color by source when provenance matters, or by location type when the operational role matters more. Use filters to isolate one dataset while retaining the context of the others.
Practical checklist
- Define common columns
- Add Source and Updated At
- Create stable IDs
- Normalize categories
- Document duplicate precedence
Turn the analysis into a repeatable workflow
Document the source, owner, update cadence, and meaning of each important field. Give locations stable identifiers so refreshed data updates existing points instead of creating duplicates. Save a clean source file separately from presentation-specific edits, and record any manual corrections made after import.
A useful map should lead to a decision or next action. Name the intended audience, the question the map answers, and the threshold that would trigger a response. Revisit the map when the underlying data changes materially rather than treating the first published version as permanent.
Continue in Mapize
Use these product guides when you are ready to apply the workflow to your own map.