Using and Plotting Data With Geographical Information

Using and Plotting Data With Geographical Information

In an increasingly location-aware world, the ability to use and plot data with geographical information is no longer reserved for cartographers and GIS professionals. Whether you’re a business analyst, urban planner, or data enthusiast, understanding how to visualize spatial data can unlock powerful insights and drive smarter decisions. This guide walks you through the essentials of working with geographic data—from data preparation to plotting techniques—so you can start mapping your world with confidence.

What Is Geographical Information?

Geographical information, also known as geospatial or spatial data, refers to any data that is tied to a specific location on Earth. This could be as simple as a set of coordinates or as complex as a multi-layered dataset showing population density, land use, and infrastructure.

Common formats include:

• Coordinates (latitude and longitude)

• Addresses or postcodes

• Grid references (e.g., Eastings and Northings)

• Shapefiles and GeoJSONs

Step 1: Preparing Your Data

Before plotting, your data must include location identifiers. These can be:

• Coordinates (e.g., 34.0522° N, 118.2437° W)

• Postcodes or ZIP codes

• Grid references (e.g., UTM, Ordnance Survey)

For best results:

• Use zero-padded grid references for consistency.

• Store Eastings first, Northings second (think: across the hallway, then up the stairs).

• Ensure your data is clean and formatted correctly—missing or malformed entries can derail your map.

Step 2: Choosing a Mapping Tool

Depending on your needs and technical comfort, you can choose from a range of tools:

• GIS Software: ArcGIS, QGIS (great for advanced spatial analysis)

• Online Platforms: Mapize, Google My Maps, Data Map Pins

• Programming Libraries: Python’s GeoPandas, Plotly, or R’s ggmap

For example, GIS for Life outlines how Data Map Pins can connect to databases and plot data using postcodes or grid references.

Step 3: Plotting Your Data

There are several ways to visualize your data:

📍 Pin Plotting

Place markers (pins) on a map to represent individual data points. Ideal for:

• Customer locations

• Store branches

• Incident reports

You can customize pins with icons, colors, or even embedded documents.

🗺️ Colored Area Plotting

Use polygons or shapes to represent data ranges across regions. Great for:

• Sales territories

• Demographic heatmaps

• Service coverage zones

Each area is color-coded based on data values (e.g., darker shades for higher counts).

🔁 Line Plotting

Connect points with lines to show routes or relationships. Useful for:

• Delivery paths

• Migration patterns

• Infrastructure layouts

🧭 Region Plotting

Similar to area plotting but without color fills. Data is attached to drawn regions, and screen tips display values on hover.

Step 4: Enhancing Your Map

To make your map more informative:

• Add screen tips that display data when hovering over pins or regions.

• Use legends to explain color coding.

• Include interactive filters for dynamic exploration.

Real-World Applications

• Retail: Identify high-performing store locations and underserved areas.

• Public Health: Track disease outbreaks and healthcare access.

• Urban Planning: Visualize zoning, traffic flow, and infrastructure needs.

• Environmental Monitoring: Map pollution levels, deforestation, or wildlife habitats.

Using and Plotting Data

To plot data using Data Map Pins Geographical Information GIS, you need to bear a few things in mind.

Firstly, how are you going to connect to the Database?

Do you have the ODBC drivers for it? Your system administrator may be able to help with ODBC drivers, and these will usually ship with your database software. Data Map Pins does, however, have a built-in method for connecting to many popular database and spreadsheet formats.

Next, What Type of GIS Data Can you plot?

Anything that represents a geographical location, such as addresses, customers, locations, etc. These locations should then be stored in each record of your database, and additionally, to plot the data, you must include at least one more data field containing a grid reference. The best arrangement would be to have two fields, one for eating and the other for non-data. The grid reference should ideally have 0 padding. Some examples of best practices are shown below.

Postcodes or Zipcodes

The inclusion of postcodes or zipcodes is always recommended because it is possible to plot data from these using suitable commercially available databases, such as ADDRESS-POINT. Typically, they store the postcode and addresses along with the corresponding grid reference and other data as well. These are used by Data Map Pins to convert a postcode or zip code to a suitable grid reference so that a plot can be made.

The following data examples give ideas of how grid references and postcodes could be stored for Data Map Pins to read your data. The software can cope with a lot of variations, but zero paddings and some sort of separation are recommended for grid references. When you plot your data, you use a plot dialog and indicate to the program which fields contain either a postcode or grid references. Each record in your data is then scanned, and the fields are read and the data plotted onto a map.

1. Data Storage Examples Using Eastings and Northings

2. Data Example Using Ordnance Survey Grid References

3. Data example using Irish National Grid references.

4. Data example using UTM Grid references. (N.B. Must be within the same UTM zone 1 -60)

Always remember easting first, nothing last (across the hallway and up the stairs).

See the help file that ships with Data Map Pins™ for more advice on using databases and maps.

 Map Data Pin – Plot Types

Data Map Pins can plot data in the following ways… see also scenarios

Pin Plotting Data

This is where pins are placed on the map. The pins can be designed in the Pin Designer before plotting, and this affords a wide choice for the look of your pins. The default pins are the colored round heads as seen on these pages, but you can also use polygons, pictures, icons, etc. You can also plot OLE documents as pins! This all means you have a very wide choice to decide what the pins will look like and can therefore relate them to your data plots.

When the plot is made, you can also decide which fields from your data are used as screen tips. The pins, when plotted, show the actual field data in a screen tip when the mouse hovers over them. You can change the look of your pins later at will. Pin plotting is ideal where the actual location needs to be shown. Full undo and redo are available.

Coloured Area Plotting Data

To enable plotting of colored areas, you have to draw enclosed shapes such as circles, rectangles, polygons, and irregular shapes over the map to outline areas of interest. These areas could include your business target areas, Police beats, sectors, etc. These shapes/areas should be selected before plotting. A special dialog opens during the plot, enabling you to format the various data ranges and colors used for each range. You can use presets here to simplify things or manually edit them.

You can choose how to combine the data from a selected field, such as count, add, average, etc. When the plotting is done, the data is plotted into the areas selected. These areas then take on the color for the range they fall into, darker colors holding more, lighter less. A screen tip is also added to the area showing the plot results and a legend is generated if desired. For clarity, the colored areas should not overlap but should be distinct individual areas. This type of plotting is ideal for getting an overall view of your data across many areas. Full undo and redo are available.

Region Plotting Data

Region plotting is similar to colored area plotting, except that no colors are used. Instead, any drawn object can be selected, other than pins, and the data is plotted to the object’s region, and a screen tip is produced with the results of the plot stored for each object.

Line Plotting Data

There are two styles of line plotting, Bezier and multiline. This type of plot draws the lines from point to point as described by your grid references. You could use this to lay out areas on your map as an example. The lines are given a screen tip with the result of the plot. Full undo and redo are available.

Final Thoughts: Mapping for Meaning

Plotting data with geographical information transforms raw numbers into visual stories. It helps you see patterns, spot anomalies, and make decisions grounded in location-based context. Whether you’re mapping customer behavior or planning your next expansion, spatial data is your compass.