Data Cleaner

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Data Cleaner

Clean messy data — remove nulls, normalize case, trim whitespace, format phone numbers and emails, extract domains, convert types, and more. Works with Apify datasets or direct JSON input. The first general-purpose data cleaner on Apify.

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Copy this block into ChatGPT, Claude, Cursor, or any LLM to start using this actor.

parsebird/data-cleaner on Apify. Call: ApifyClient("TOKEN").actor("parsebird/data-cleaner").call(run_input={...}), then client.dataset(run["defaultDatasetId"]).list_items().items for cleaned results. Key inputs: datasetId (string, Apify dataset ID), jsonData (array of objects, direct JSON input), operations (array of {field, action, options} — required), outputDatasetId (string, optional), maxItems (integer, default 1000000). Actions: trim_whitespace, normalize_case (options: {case: "lower"|"upper"|"title"}), format_email, format_phone (options: {countryCode: "US"}), extract_domain, to_number, to_date, fill_nulls (options: {value: "..."}), remove_nulls, remove_duplicates, replace_value (options: {find, replace}). Full actor spec: fetch build via GET https://api.apify.com/v2/acts/parsebird~data-cleaner (Bearer TOKEN). Get token: https://console.apify.com/account/integrations

What does Data Cleaner do?

This Actor takes messy scraped or imported data and applies a configurable pipeline of cleaning operations. Each operation targets a specific field and transforms its values — trimming whitespace, normalizing case, formatting phone numbers, and more.

Use cases:

• CRM cleanup — normalize names, emails, and phone numbers before import
• Lead list hygiene — remove rows with missing emails, deduplicate by company
• Post-scrape processing — extract domains from URLs, convert price strings to numbers
• Data pipeline prep — standardize data format before analysis or export

Supported operations

Input parameters

*Provide either datasetId or jsonData (or both).

Operations format

Each operation is a JSON object with:

{
"field":"email",
"action":"format_email",
"options":{}
}

Operations are applied in order. You can chain multiple operations on the same field:

[
{"field":"name","action":"trim_whitespace"},
{"field":"name","action":"normalize_case","options":{"case":"title"}},
{"field":"email","action":"format_email"},
{"field":"phone","action":"format_phone","options":{"countryCode":"US"}},
{"field":"website","action":"extract_domain"},
{"field":"revenue","action":"to_number"},
{"field":"email","action":"remove_nulls"}
]

Before and after example

Input (dirty data)

[
{"name":" john doe ","email":" JOHN@EXAMPLE.COM ","phone":"(555) 123-4567","website":"https://www.example.com/about","revenue":"$1,234,567"},
{"name":"JANE SMITH","email":"Jane.Smith@Company.IO","phone":"555.987.6543","website":"info@company.io","revenue":"2345678"},
{"name":"","email":null,"phone":"1-800-555-0199","website":"company.io","revenue":"$99.99"},
{"name":"bob wilson","email":"bob@test.com","phone":"+14155550100","website":"https://test.com/page?id=1","revenue":"not a number"}
]

Output (cleaned data)

[
{"name":"John Doe","email":"john@example.com","phone":"+15551234567","website":"example.com","revenue":1234567},
{"name":"Jane Smith","email":"jane.smith@company.io","phone":"+15559876543","website":"company.io","revenue":2345678},
{"name":"Bob Wilson","email":"bob@test.com","phone":"+14155550100","website":"test.com","revenue":"not a number"}
]

Row 3 was removed (null email with remove_nulls). All names are title-cased, emails lowercased, phones in E.164, domains extracted, and revenues converted to numbers.

How to use via API

Python

from apify_client import ApifyClient
client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("parsebird/data-cleaner").call(run_input={
"datasetId":"YOUR_DATASET_ID",
"operations":[
{"field":"email","action":"format_email"},
{"field":"name","action":"trim_whitespace"},
{"field":"name","action":"normalize_case","options":{"case":"title"}},
{"field":"phone","action":"format_phone","options":{"countryCode":"US"}},
],
})
items = client.dataset(run["defaultDatasetId"]).list_items().items
print(f"Cleaned items: {len(items)}")

cURL

curl-X POST "https://api.apify.com/v2/acts/parsebird~data-cleaner/runs?token=YOUR_API_TOKEN"\
-H"Content-Type: application/json"\
-d'{
 "jsonData": [
 {"name": " JOHN DOE ", "email": " JOHN@CO.COM "}
 ],
 "operations": [
 {"field": "name", "action": "trim_whitespace"},
 {"field": "name", "action": "normalize_case", "options": {"case": "title"}},
 {"field": "email", "action": "format_email"}
 ]
 }'

Output

Cleaned items retain their original structure. A stats key is stored in the key-value store:

{
"totalLoaded":5000,
"totalCleaned":4800,
"operationsApplied":7,
"fieldsCleaned":5,
"totalChanges":15200
}

Pricing

This Actor uses a pay-per-event pricing model.

Charged per 1,000 items loaded. Platform compute costs are additional.