CSV Row Filter

What does the CSV Row Filter do?

The CSV Row Filter extracts rows from a CSV spreadsheet that satisfy specific column conditions such as exact match, substring containment, prefix/suffix matching, numerical comparisons (>, <, >=, <=), regular expressions, or empty/non-empty checks.

Core Concepts

• Condition Logic:
  • equals / notEquals: Exact string equality.
  • contains / notContains: Substring inclusion check.
  • startsWith / endsWith: Prefix and suffix verification.
  • greaterThan / lessThan: Numerical threshold comparisons.
  • matchesRegex: Regular expression pattern matching.
  • isEmpty / isNotEmpty: Blank cell detection.
• Inverted Filtering: Discards rows matching the condition while keeping non-matching rows.
• Header Isolation: Keeps the column header intact regardless of filtering criteria.

How to use the tool?

1. Input CSV Data: Paste your CSV spreadsheet data or click Load Sample.
2. Configure Filter:
   • Filter Column: Select the column to evaluate.
   • Condition: Select your operator (e.g. Contains, Greater Than, Equals).
   • Value: Enter the search value or numerical threshold.
   • Options: Toggle Case Sensitivity or Invert Filter.
3. Filter & Export: Click Filter CSV Rows, then click Copy or Download.

Related Developer Utilities

• CSV Column Extractor: Extract specific columns and discard all others.
• CSV Row Deduplicator: Remove duplicate rows from CSV spreadsheets.
• CSV Empty-Row Remover: Strip unpopulated rows.

REST API Integration

blueutils.com provides a free REST API endpoint (POST https://blueutils.com/api/csv/csv-row-filter) for programmatic integration.

API Request Parameters

API Request Payload Examples

cURL (String Payload)

curl -X POST https://blueutils.com/api/csv/csv-row-filter \
  -H "Content-Type: application/json" \
  -d '{
    "payload": "id,name,amount\n101,Alice,150.00\n102,Bob,45.50",
    "options": {
      "columnIndex": 2,
      "condition": "greaterThan",
      "value": "100"
    }
  }'

Python (Array Payload)

import requests

url = "https://blueutils.com/api/csv/csv-row-filter"
payload = {
    "payload": [
        ["id", "name", "amount"],
        ["101", "Alice", "150.00"],
        ["102", "Bob", "45.50"]
    ],
    "options": {
        "columnIndex": 2,
        "condition": "greaterThan",
        "value": "100"
    }
}
headers = {"Content-Type": "application/json"}
response = requests.post(url, json=payload, headers=headers)
print(response.json())

Java

import java.net.URI;
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;

public class Main {
    public static void main(String[] args) throws Exception {
        String jsonPayload = "{\"payload\": \"id,name\\n1,Alice\\n2,Bob\", \"options\": {\"columnIndex\": 1, \"condition\": \"equals\", \"value\": \"Alice\"}}";
        HttpClient client = HttpClient.newHttpClient();
        HttpRequest request = HttpRequest.newBuilder()
            .uri(URI.create("https://blueutils.com/api/csv/csv-row-filter"))
            .header("Content-Type", "application/json")
            .POST(HttpRequest.BodyPublishers.ofString(jsonPayload))
            .build();
        HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
        System.out.println(response.body());
    }
}

API Response Parameters

API Response Payload Examples

Success Response (HTTP 200 OK)

{
  "isValid": true,
  "result": "id,name,amount\n101,Alice,150.00",
  "data": [
    ["id", "name", "amount"],
    ["101", "Alice", "150.00"]
  ],
  "originalSize": 45,
  "resultSize": 30,
  "headers": ["id", "name", "amount"],
  "targetColumnIndex": 2,
  "targetColumnName": "amount",
  "condition": "greaterThan",
  "filterValue": "100",
  "originalRowCount": 3,
  "matchedRowCount": 1,
  "excludedRowCount": 1
}

Error Response (HTTP 400 Bad Request)

{
  "isValid": false,
  "error": "CSV input cannot be empty."
}

Rate Limit Exceeded Response (HTTP 429 Too Many Requests)

{
  "error": "API rate limit exceeded. Please wait or contact support@blueutils.com."
}

Why use an API to filter CSV rows?

Integrating the CSV Row Filter API into CI/CD pipelines, automated ETL pipelines, or autonomous agent workflows provides several practical advantages:

• Rapid Script Validation: Enables developers and infrastructure engineers to segment large CSV databases by customer region, status, or date range on the fly.
• Optimized Token Efficiency for AI Agents: Filtering large files to only relevant rows drastically reduces context window usage and LLM token costs.
• Deterministic Accuracy Without Hallucinations: Language models can skip rows or misapply numerical conditions in large tables. Delegating processing to a deterministic API guarantees 100% computational accuracy every time without token overhead.

Native Usage

How to achieve the same task locally without external dependencies using native operating system utilities and scripting languages:

Windows (CMD / PowerShell)

Using native PowerShell Import-Csv and Where-Object:

# Filter rows where 'amount' is greater than 100
Import-Csv -Path "input.csv" | Where-Object { [double]$_.amount -gt 100 } | Export-Csv -Path "output.csv" -NoTypeInformation

Linux / Unix (Bash / Shell)

Using standard Linux awk:

# Keep rows where 3rd column contains 'Engineering'
awk -F',' 'NR==1 || $3 ~ /Engineering/' input.csv > output.csv

Python

Using the Python standard library csv module:

import csv

with open("input.csv", mode="r", encoding="utf-8") as infile:
    reader = csv.reader(infile)
    header = next(reader)
    filtered_rows = [row for row in reader if len(row) > 3 and float(row[3]) > 100]

with open("output.csv", mode="w", newline="", encoding="utf-8") as outfile:
    writer = csv.writer(outfile)
    writer.writerow(header)
    writer.writerows(filtered_rows)

print("Rows filtered successfully.")

Java

Using standard Java java.nio.file.Files:

import java.nio.file.*;
import java.util.*;

public class FilterCsvRowsExample {
    public static void main(String[] args) throws Exception {
        List<String> lines = Files.readAllLines(Paths.get("input.csv"));
        if (lines.isEmpty()) return;

        String header = lines.get(0);
        List<String> output = new ArrayList<>();
        output.add(header);

        for (int i = 1; i < lines.size(); i++) {
            String[] cells = lines.get(i).split(",");
            if (cells.length > 2 && cells[2].trim().equalsIgnoreCase("Engineering")) {
                output.add(lines.get(i));
            }
        }

        Files.write(Paths.get("output.csv"), output);
        System.out.println("Rows filtered successfully.");
    }
}