Complete Guide to Formulas and Calculated Fields in Maps

The most effective spatial analysis combines geographic visualization with data transformation, creating calculated fields that classify, categorize, and compute new values from your existing map data.

If your mapping workflows rely only on pre-existing columns without the ability to compute new values, classify data dynamically, or create custom categorizations, you're missing the data transformation capabilities that unlock deeper analysis. That's why analysts ask: can we create formulas and calculated fields that transform our spatial data without exporting to spreadsheets?

With Atlas, you can build calculated columns using formula expressions or AI-powered natural language descriptions. No spreadsheet exports, no external data processing, no barriers between your geographic data and the transformations you need. Everything starts with your data and the formulas that derive new insights.

Here's how to set it up step by step.

Why Formulas and Calculated Fields Matter for Spatial Analysis

Creating formulas enables better data classification and more effective geographic analysis across datasets that require transformation beyond their raw values.

So formulas aren't just spreadsheet features—they're essential analysis tools that transform how effectively you classify and analyze geographic information.

Step 1: Understand Formula Capabilities in Atlas

Atlas makes it easy to work with formulas through multiple approaches:

Formula columns adding calculated fields to your data tables that compute values from existing columns
AI formula generation describing what you want in natural language and letting AI create the formula
Filter by formula using formula expressions to create complex filter conditions
Conditional logic using IF/THEN expressions to classify data based on multiple conditions
Field references accessing other column values using {field_name} syntax in formulas

Each approach provides different ways to transform and analyze your geographic data.

Step 2: Create Calculated Columns with Formulas

Next, add formula columns that compute new values:

You can create various calculations:

Mathematical operations adding, subtracting, multiplying, or dividing numeric columns
Text manipulation concatenating strings, extracting substrings, or formatting text values
Conditional classification using IF statements to categorize data based on conditions
Date calculations computing time differences or extracting date components
Lookup operations referencing values from related columns in your calculations

Each calculation type transforms your raw data into more useful derived values.

Also read: Generate Formulas with AI from Natural Language Descriptions

Step 3: Generate Formulas with AI Assistance

To create formulas without knowing exact syntax:

Describe your goal writing what you want the formula to calculate in plain English
Reference your fields mentioning the column names that should be involved in the calculation
Let AI generate syntax receiving a working formula based on your description
Review and apply checking the generated formula and applying it to your data
Iterate if needed refining your description if the first result isn't quite right

AI formula generation makes complex calculations accessible even without formula syntax expertise.

Also read: 10 Essential Formulas for Spatial Data Analysis

Step 4: Use Formulas for Data Filtering

To isolate specific data subsets using complex conditions:

Create filter expressions writing formulas that evaluate to true/false for each feature
Combine multiple conditions using AND/OR logic to create complex filter criteria
Filter by calculated values using computed fields in filter expressions
Save filtered views preserving filter expressions for repeated use
Export filtered data saving subsets that match your formula conditions

Formula-based filtering provides precision that simple column filters can't match.

Also read: Filter Map Data Using Formula Expressions

Step 5: Build Classification Systems

To categorize geographic data dynamically:

Define classification logic establishing how features should be categorized based on their values
Create tiered classifications using nested IF statements for multi-level categorization
Calculate scores combining multiple factors into single classification values
Apply to visualization using classified values to drive map styling and symbology
Document classifications keeping track of how categories are defined for transparency

Classification transforms raw data into meaningful categories that support decision-making.

Also read: Create Calculated Columns for Custom Data Classification

Step 6: Integrate Formulas into Spatial Workflows

Now that formulas are creating derived values:

Style by calculated fields using formula results to drive conditional map styling
Filter by classifications isolating features that fall into specific calculated categories
Analyze computed values running spatial analysis on transformed data
Export enriched datasets saving data with calculated columns for external use
Build dashboards creating interfaces that display calculated metrics geographically

Your formulas become part of comprehensive spatial workflows that transform analysis capabilities.

Use Cases

Formulas and calculated fields in maps are useful for:

Data analysts transforming raw geographic data into classified, categorized insights
GIS specialists creating derived values without leaving the mapping environment
Business analysts applying business logic to spatial data for geographic intelligence
Operations managers calculating operational metrics across distributed locations
Research teams computing derived measurements for spatial analysis projects

It's essential for any organization where geographic data needs transformation beyond its raw form.

Tips

Start simple building basic formulas first before creating complex expressions
Use AI assistance describing calculations in natural language when unsure about syntax
Test with sample data verifying formulas produce expected results before applying broadly
Reference correct field names ensuring field references match exact column names
Document complex formulas adding notes about what complex calculations are intended to do

Formulas and calculated fields in Atlas enable data transformation without leaving your mapping environment.

No spreadsheet exports needed. Just create formulas, generate them with AI, and transform your data in place.

Data Transformation with Atlas

Effective spatial analysis requires data transformation. Formulas and calculated fields let you classify, compute, and categorize geographic information without leaving your mapping environment.

Atlas helps you turn raw data into derived insights: one platform for formulas, classification, and spatial analysis.

Transform Data with Calculated Fields

You can:

Add formula columns that compute values from existing data
Use AI to generate formulas from natural language descriptions
Filter data using complex formula expressions

Also read: Complete Guide to Connecting Enterprise Databases to Your Maps

Build Analysis That Classifies and Computes

Atlas lets you:

Create classification systems using conditional logic and calculated fields
Style maps based on computed values for visual analysis
Export enriched datasets with calculated columns included

That means no more exporting to spreadsheets, and no more manual classification processes.

Discover Better Insights Through Formulas

Whether you're classifying assets, computing metrics, or filtering by complex conditions, Atlas helps you transform geographic data into actionable intelligence.

It's data transformation—designed for spatial analysis and map visualization.

Analyze Data with the Right Tools

Geographic data is valuable, but transformation unlocks insights. Whether you're computing values, classifying features, filtering by conditions, or building visualizations—formulas matter.

Atlas gives you both creation and analysis.

In this article, we covered how to use formulas and calculated fields in maps, but that's just one of many ways Atlas helps you transform geographic data.

From formula creation to AI assistance, filtering, classification, and visualization, Atlas makes data transformation accessible for spatial analysis. All from your browser. No spreadsheets needed.

So whether you're creating your first formula or building complex classification systems, Atlas helps you move from "raw data" to "derived insights" faster.