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CSV Filter

Filter CSV data by column values with multiple conditions and operators. Supports 12 filter operators including equals, contains, greater_than, less_than, and empty value checks. Additional Filters examples: [{"column": "age", "operator": "greater_than", "value": "25"}] [{"column": "status", "operator": "equals", "value": "active"}, {"column": "score", "operator": "greater_equal", "value": "80"}] [{"column": "name", "operator": "contains", "value": "john"}, {"column": "email", "operator": "is_not_empty"}]

Click to upload file or drag and drop file here

Maximum file size: 10MB

Key Facts

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

Overview

The CSV Filter tool allows you to quickly refine large datasets by applying precise column-based conditions. With support for 12 operators including comparison, text matching, and empty value checks, you can extract specific rows from your CSV files without needing complex spreadsheet software.

When to Use

  • •When you need to extract specific subsets of data from a large CSV file based on column criteria.
  • •When you need to clean your dataset by removing rows with missing or empty values.
  • •When you want to perform multi-condition queries to isolate records that meet several requirements simultaneously.

How It Works

  • •Upload your CSV file and specify the primary column and filter operator you wish to apply.
  • •Define your filter value and toggle options like case sensitivity or whitespace trimming for accuracy.
  • •Use the Additional Filters field to add complex, multi-condition logic via JSON.
  • •Select your preferred output format and download the filtered results.

Use Cases

Isolating high-value customer records from a master sales list based on purchase amount.
Cleaning contact lists by filtering out entries that lack an email address or phone number.
Extracting specific project tasks from a team export based on status and priority levels.

Examples

1. Filter Active Customers

Marketing Analyst
Background
A marketing analyst has a customer database with thousands of entries and needs to contact only those with an 'active' status.
Problem
Manually sorting through thousands of rows in a spreadsheet is prone to error.
How to Use
Upload the customer CSV, set the filter column to 'status', and use the 'equals' operator with the value 'active'.
Outcome
A clean CSV file containing only active customer records is generated for the email campaign.

2. Identify High-Priority Tasks

Project Manager
Background
A project manager needs to review tasks that are both 'In Progress' and have a 'High' priority level.
Problem
Standard spreadsheet filters are difficult to save and share for recurring reports.
How to Use
Upload the task list and use the 'Additional Filters' JSON field to define the two-part condition.
Example Config
[{"column": "status", "operator": "equals", "value": "In Progress"}, {"column": "priority", "operator": "equals", "value": "High"}]
Outcome
The tool outputs a filtered list of high-priority tasks, allowing the manager to focus on critical items.

Try with Samples

json, csv, file
CSV Samples
Sample CSV files with various data types, sizes, and complexity levels
title token csv
json
Python Samples
Essential Python code examples and Hello World demonstrations
preferred input family json
json
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preferred input family json
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json

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FAQ

What file formats are supported?

This tool is specifically designed for CSV files.

Can I filter by multiple columns at once?

Yes, you can use the 'Additional Filters' field to define multiple conditions across different columns using JSON syntax.

How do I handle empty cells?

You can select the 'is_empty' or 'is_not_empty' operators to filter rows based on whether a specific column contains data.

Is the filtering case-sensitive?

By default, it is not, but you can enable the 'Case Sensitive' checkbox to ensure exact matching.

What output formats can I choose?

You can export your results as a new CSV file, a JSON object, or a summary report.

API Documentation

Request Endpoint

POST /en/api/tools/csv-filter

Request Parameters

Parameter Name Type Required Description
csvFile file (Upload required) Yes -
filterColumn text Yes -
filterOperator select No -
filterValue text No -
additionalFilters textarea No -
outputFormat select No -
includeHeader checkbox No -
caseSensitive checkbox No -
trimValues checkbox No -

File type parameters need to be uploaded first via POST /upload/csv-filter to get filePath, then pass filePath to the corresponding file field.

Response Format

{
  "filePath": "/public/processing/randomid.ext",
  "fileName": "output.ext",
  "contentType": "application/octet-stream",
  "size": 1024,
  "metadata": {
    "key": "value"
  },
  "error": "Error message (optional)",
  "message": "Notification message (optional)"
}
File: File

AI MCP Documentation

Add this tool to your MCP server configuration: 

{
  "mcpServers": {
    "elysiatools-csv-filter": {
      "name": "csv-filter",
      "description": "Filter CSV data by column values with multiple conditions and operators. Supports 12 filter operators including equals, contains, greater_than, less_than, and empty value checks.

Additional Filters examples:
[{\"column\": \"age\", \"operator\": \"greater_than\", \"value\": \"25\"}]
[{\"column\": \"status\", \"operator\": \"equals\", \"value\": \"active\"}, {\"column\": \"score\", \"operator\": \"greater_equal\", \"value\": \"80\"}]
[{\"column\": \"name\", \"operator\": \"contains\", \"value\": \"john\"}, {\"column\": \"email\", \"operator\": \"is_not_empty\"}]",
      "baseUrl": "https://elysiatools.com/mcp/sse?toolId=csv-filter",
      "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.

Supports URL file links or Base64 encoding for file parameters.

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