Categories

← View All Tools

Data Range Limiter

Limit numerical values to specified ranges by clipping, filtering, or marking out-of-bounds values. Perfect for data quality control, sensor data cleaning, business rule enforcement, and data preprocessing. Features: - Range clipping (clip values to min/max boundaries) - Range filtering (remove out-of-bounds rows) - Range marking (flag modified values) - Per-column range configuration - Automatic numeric column detection - Multiple handling strategies - Detailed modification reports - Statistical analysis of changes - Business rule enforcement Common Use Cases: - Sensor data validation and cleaning - Machine learning input preparation - Data quality control and validation - Business constraint enforcement - Outlier management and control - Data preprocessing pipelines

CSV data with headers and numeric values to be processed

JSON object specifying min/max ranges for each column. Example: {"age": {"min": 18, "max": 65}}

Specify which columns to apply range limits to. Leave empty to auto-detect numeric columns.

Automatically suggest reasonable ranges based on data distribution

Keep original values with "_original" suffix

Add flags to indicate which values were modified

Generate detailed statistics about modifications

Key Facts

Category
Data Processing
Input Types
textarea, select, checkbox
Output Type
text
Sample Coverage
4
API Ready
Yes

Overview

The Data Range Limiter is a powerful utility designed to enforce numerical constraints on your datasets by clipping, filtering, or flagging values that fall outside defined boundaries. It ensures data consistency and quality, making it an essential tool for cleaning sensor outputs, preparing machine learning inputs, and enforcing strict business rules across your CSV files.

When to Use

  • •When you need to clean sensor data by removing or capping extreme outliers.
  • •When preparing datasets for machine learning models that require strictly normalized input ranges.
  • •When enforcing business constraints, such as ensuring age, salary, or temperature values remain within logical limits.

How It Works

  • •Upload your CSV data and define your range constraints using a simple JSON configuration.
  • •Select a handling strategy: 'Clip' to force values to boundaries, 'Filter' to remove invalid rows, or 'Mark' to flag discrepancies.
  • •Optionally enable auto-detection to identify numeric columns and generate statistical reports on the modifications performed.
  • •Download your processed, validated dataset with optional modification flags for easy auditing.

Use Cases

Sensor data validation and cleaning to remove noise and hardware errors.
Machine learning input preparation to ensure feature values stay within expected bounds.
Data quality control to identify and rectify entries that violate business logic or safety constraints.

Examples

1. Sensor Data Cleaning

Data Engineer
Background
A set of temperature sensor logs contains occasional spikes due to electrical interference, with values reading above 100°C in a room-temperature environment.
Problem
The spikes are skewing the average temperature calculations and need to be capped at a realistic maximum.
How to Use
Upload the CSV, set the strategy to 'Clip', and define the range for the 'temperature' column.
Example Config
{"temperature": {"min": 15, "max": 40}}
Outcome
All temperature readings above 40°C are automatically set to 40°C, ensuring the dataset remains usable for analysis without extreme outliers.

2. Enforcing Business Rules

HR Analyst
Background
An employee database contains age entries that are clearly erroneous, such as values below 18 or above 100.
Problem
These invalid entries need to be removed from the report to ensure accurate demographic analysis.
How to Use
Upload the employee CSV, select the 'Filter' strategy, and configure the age range.
Example Config
{"age": {"min": 18, "max": 100}}
Outcome
Any row containing an age outside the 18-100 range is removed, resulting in a clean dataset ready for HR reporting.

Try with Samples

json, csv, video
CSV Samples
Sample CSV files with various data types, sizes, and complexity levels
preferred input family csv,json
csv, json
Python Samples
Essential Python code examples and Hello World demonstrations
preferred input family csv,json
csv, json
WebRTC Real-Time Communication Samples
Comprehensive WebRTC samples for peer-to-peer audio/video communication, data channels, screen sharing, and signaling server implementation
preferred input family json
json
Regex Replace Samples
Collection of common and useful regex replacement patterns for text transformation and data cleaning
preferred input family csv
csv

Related Hubs

Json Convert Tools
Explore 100 json tools for convert workflows and compare closely related utilities quickly.
Csv Convert Tools
Explore 37 csv tools for convert workflows and compare closely related utilities quickly.
Video Convert Tools
Explore 36 video tools for convert workflows and compare closely related utilities quickly.
Barcode Convert Tools
Explore 6 barcode tools for convert workflows and compare closely related utilities quickly.

FAQ

What is the difference between clipping and filtering?

Clipping adjusts out-of-bounds values to the nearest allowed minimum or maximum, while filtering removes the entire row containing the invalid value.

Can I apply different ranges to different columns?

Yes, the JSON configuration allows you to specify unique min and max values for each individual column in your dataset.

What happens if I don't specify target columns?

The tool will automatically detect all numeric columns in your CSV and apply the range constraints to them.

Can I keep my original data for comparison?

Yes, by enabling 'Preserve Original Columns', the tool will retain your original values with an '_original' suffix in the output.

Does this tool support non-numeric data?

The tool is designed for numeric range enforcement; non-numeric columns are ignored during the range processing phase.

API Documentation

Request Endpoint

POST /en/api/tools/data-range-limiter

Request Parameters

Parameter Name Type Required Description
inputData textarea Yes CSV data with headers and numeric values to be processed
rangeConfiguration textarea Yes JSON object specifying min/max ranges for each column. Example: {"age": {"min": 18, "max": 65}}
targetColumns textarea No Specify which columns to apply range limits to. Leave empty to auto-detect numeric columns.
handlingStrategy select No -
autoDetectRanges checkbox No Automatically suggest reasonable ranges based on data distribution
preserveOriginal checkbox No Keep original values with "_original" suffix
markModified checkbox No Add flags to indicate which values were modified
includeStatistics checkbox No Generate detailed statistics about modifications

Response Format

{
  "result": "Processed text content",
  "error": "Error message (optional)",
  "message": "Notification message (optional)",
  "metadata": {
    "key": "value"
  }
}
Text: Text

AI MCP Documentation

Add this tool to your MCP server configuration: 

{
  "mcpServers": {
    "elysiatools-data-range-limiter": {
      "name": "data-range-limiter",
      "description": "Limit numerical values to specified ranges by clipping, filtering, or marking out-of-bounds values. Perfect for data quality control, sensor data cleaning, business rule enforcement, and data preprocessing.

Features:
- Range clipping (clip values to min/max boundaries)
- Range filtering (remove out-of-bounds rows)
- Range marking (flag modified values)
- Per-column range configuration
- Automatic numeric column detection
- Multiple handling strategies
- Detailed modification reports
- Statistical analysis of changes
- Business rule enforcement

Common Use Cases:
- Sensor data validation and cleaning
- Machine learning input preparation
- Data quality control and validation
- Business constraint enforcement
- Outlier management and control
- Data preprocessing pipelines",
      "baseUrl": "https://elysiatools.com/mcp/sse?toolId=data-range-limiter",
      "command": "",
      "args": [],
      "env": {},
      "isActive": true,
      "type": "sse"
    }
  }
}

You can chain multiple tools, e.g.: `https://elysiatools.com/mcp/sse?toolId=png-to-webp,jpg-to-webp,gif-to-webp`, max 20 tools.

If you encounter any issues, please contact us at [email protected]