Universal Data Cleaner V3 avatar
Universal Data Cleaner V3

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Universal Data Cleaner V3

Universal Data Cleaner V3

Enterprise-grade CSV/XLSX cleaning tool that automatically fixes headers, removes duplicates, normalizes emails and phone numbers, and repairs broken or inconsistent data. Delivers clean, analysis-ready files with 99%+ run success—perfect for CRM imports, lead pipelines, and automation workflows.

Pricing

$0.01 / 1,000 results

Rating

0.0

(0)

Developer

Leoncio Jr Coronado

Leoncio Jr Coronado

Maintained by Community

Actor stats

0

Bookmarked

4

Total users

2

Monthly active users

15 days ago

Last modified

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📘 Universal Data Cleaner (CSV, Excel & Dataset) Clean, normalize, and standardize your datasets with one click.

The Universal Data Cleaner automatically transforms messy datasets into clean, uniform, business-ready data.

It supports:

CSV files

Excel files (.xlsx)

Apify datasets

and outputs:

Clean CSV

Clean Excel

Clean JSON

Clean Dataset (Apify Dataset)

✨ Features 🔹 Intelligent Data Cleaning

Automatically detects and cleans:

Name fields (Title Case, remove duplicates & noise)

Email fields (lowercase domain, trim whitespace)

Phone numbers

Detect PH mobile numbers

Convert to E.164 international format

Strip invalid characters

URL fields

Force HTTPS

Lowercase domain

Remove trailing slashes

Addresses

Trim spaces

Normalize casing

Collapse double spaces

🔹 Dataset Normalization

Remove duplicate rows

Remove duplicate rows using specific keys

Trim all whitespace

Standardize column casing globally (lower, upper, title)

Auto-detect column types

🔹 Multiple Output Formats

Choose the output format:

CSV

Excel (.xlsx)

JSON

Apify Dataset

📥 Input Configuration Example input: { "input_mode": "file", "input_file": "https://.../yourfile.csv", "output_format": "csv", "deduplicate_rows": true, "trim_whitespace": true, "standardize_case": "lower" } 📤 Output Your cleaned file appears in: Storage → Key-value store → OUTPUT You may also choose dataset output to load cleaned rows into an Apify dataset. 🧪 Example Cleaning

Before cleaning:

Name Email Phone URL aNThoNy Anthony.Dicosimo@DOMAIN.COM 112123809500 https://FACEBOOK.com/NationalGeneral

jAson jason.mccarthy@Domain.com 115715266000 https://facebook.COM/LeidosInc/

After cleaning:

Name Email Phone URL Anthony Anthony.Dicosimo@domain.com +112123809500 https://facebook.com/nationalgeneral

Jason jason.mccarthy@domain.com +115715266000 https://facebook.com/leidosinc 📊 Ideal Use Cases

CRM imports (HubSpot, Salesforce, GoHighLevel)

Lead lists from scrapers

Shopify product data cleanup

Excel normalization for analytics

Pre-processing before ML modeling

Cleaning of enterprise contact datasets 🧩 Integrations

Compatible with:

Zapier

Make.com

AWS Lambda

Python scripts

Google Sheets connectors

Any Apify Actor

No-code workflows 🚀 Publish & Monetize

This Actor is optimized for:

Apify Store (public listing)

Apify $1M Challenge

Fiverr lead-cleaning gigs

Upwork data-prep contracts

Enterprise workflows

❤️ Author

Built by Leoncio “Leo” Coronado Jr. — Python Automation Specialist — Apify Actor Developer — Data Pipeline Engineer — CRM & Shopify Data Automation