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Prepare Data for Centroid and Raster Maps in 23degrees

In this tutorial, we want to show you how to prepare your datasets to create centroid or raster maps. The goal here is to make sure your dataset has everything it needs to be turned into beautifully colored maps.

applicationUI.publishedAt 6 de mayo de 2026
1. Introduction

In today’s example, we’re using a dataset showing the largest religious group in Germany, based on 10 by 10 kilometer raster cells. Let’s take a closer look at how this dataset is structured

Introduction
Introduction
2. Select ID Field

The first important column is the ID column. This column ensures uniqueness across all points in the dataset and makes each point identifiable.

Select ID Field
Select ID Field
3. Choose Longitude Field

Next, we have the coordinate columns. Without these, it’s not possible to locate the points on the map. Please make sure your data is in WGS84, also known as the Mercator projection.

Choose Longitude Field
Choose Longitude Field
5. Access Second Configuration Option

Here, you can correctly assign which column represents longitude and which represents latitude. If you’re unsure, here’s a quick tip: Longitude values range from -180° (west) to +180° (east), with the zero meridian running through Greenwich, London.Latitude values range from -90° (south) to +90° (north) from the equator.

Access Second Configuration Option
Access Second Configuration Option
6. Select Value Field

After assigning the correct longitudes and latitudes, the next step is to look at the value column. In this case, it shows the count and share of the dominant religion in Germany.

Select Value Field
Select Value Field
7. Choose Dominant Religion Field

To color the map correctly, we also need a category column. This column defines how the cells are colored. n our example, it’s the name of the largest religious group.

Choose Dominant Religion Field
Choose Dominant Religion Field
8. Confirm Data Integrity

And that’s about it! Just make sure all cells are properly recognized, there are no duplicates, and each ID is unique.

Confirm Data Integrity
Confirm Data Integrity

Now you know everything you need to create raster or centroid-based maps. In the next tutorial, we’ll turn this dataset into a beautiful map visualization.