CSV Cleanup and Column Mapping API API ID: 12804

Analyzes, validates, maps, previews, and cleans CSV text for import preparation.
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CSV Cleanup and Column Mapping API analyzes, validates, maps, previews, and cleans CSV data for import preparation.

The API handles CSV structure, row count, column count, detected headers, duplicate headers, blank headers, missing expected fields, column type detection, email-like values, integer-like values, float-like values, boolean-like values, empty values, required field validation, row-level validation errors, column mapping suggestions, source-to-target field mapping, cleaned CSV output, preview rows, warnings, validation status, usage status, safety notes, and disclaimer.

The API returns CSV analysis results, row count, column count, detected columns, duplicate headers, blank headers, column type guesses, missing expected fields, validation status, row-level errors, warnings, column mapping output, cleaned CSV text, preview rows, normalized import-preparation output, and technical disclaimer.

This API is useful for SaaS builders, CRM platforms, data operations teams, marketing operations teams, sales operations teams, agencies, developers, backend teams, frontend teams, QA teams, ecommerce platforms, lead import services, customer import services, CSV import services, no-code platforms, internal tooling teams, B2B software teams, analytics teams, automation platforms, data onboarding teams, RevOps teams, business operations teams, spreadsheet-heavy teams, developer platforms, lightweight ETL services, and workflow automation services.

The API processes CSV text submitted in API requests and returns technical analysis, validation, mapping, preview, and cleanup results. It does not hack, brute force, attempt logins, scan private systems, scrape restricted content, change customer data, send emails, create calendar events, import data into third-party systems, approve or reject data, verify tax accuracy, verify accounting accuracy, verify legal accuracy, or verify compliance accuracy. It does not replace human review of cleaned data, a full ETL platform, a data warehouse, or professional data engineering review.

API Documentation

Endpoints


Analyzes CSV text and returns row count, column count, detected columns, duplicate headers, blank headers, column type guesses, missing expected fields, warnings, and disclaimer.



                                                                            
POST https://creators.zylalabs.com/api/12804/csv+cleanup+and+column+mapping+api/25192/analyze+csv
                                                                            
                                                                        

Analyze CSV - Endpoint Features

Object Description
Request Body [Required] Json

Free test requests remaining: 3 of 3.


INPUT PARAMETERS


API EXAMPLE RESPONSE

{"ok":true,"rowCount":2,"columnCount":3,"originalHeaders":["name","email","age"],"normalizedHeaders":["name","email","age"],"duplicateHeaders":[],"blankHeaders":[],"inferredDataTypes":{"name":"string","email":"email-like","age":"integer"},"missingExpectedFields":[],"recommendations":["CSV structure looks ready for basic import checks."],"warnings":[],"disclaimer":"This API analyzes and transforms CSV text for import preparation. Review cleaned data before using it in production systems."}

Analyze CSV - CODE SNIPPETS


curl --location --request POST 'https://zylalabs.com/api/12804/csv+cleanup+and+column+mapping+api/25192/analyze+csv' --header 'Authorization: Bearer YOUR_API_KEY' 

--data-raw '{
	"csvText": "name,email,age\nAlice,[email protected],31\nBob,[email protected],42"
}'

    

Maps source CSV column names to requested target fields and returns column mapping suggestions and source-to-target field mapping output.



                                                                            
POST https://creators.zylalabs.com/api/12804/csv+cleanup+and+column+mapping+api/25193/map+columns
                                                                            
                                                                        

Map Columns - Endpoint Features

Object Description
Request Body [Required] Json

Free test requests remaining: 3 of 3.


INPUT PARAMETERS


API EXAMPLE RESPONSE

{"ok":true,"suggestedMapping":[{"targetField":"first_name","sourceColumn":"First Name","normalizedSourceColumn":"first_name","score":1.0},{"targetField":"email","sourceColumn":"Email Address","normalizedSourceColumn":"email_address","score":0.75},{"targetField":"phone_number","sourceColumn":"Phone","normalizedSourceColumn":"phone","score":0.75}],"unmappedSourceColumns":[],"missingTargetFields":[],"warnings":[],"disclaimer":"This API analyzes and transforms CSV text for import preparation. Review cleaned data before using it in production systems."}

Map Columns - CODE SNIPPETS


curl --location --request POST 'https://zylalabs.com/api/12804/csv+cleanup+and+column+mapping+api/25193/map+columns' --header 'Authorization: Bearer YOUR_API_KEY' 

--data-raw '{
	"csvText": "First Name,Email Address,Phone\nAlice,[email protected],555-1111",
	"targetFields": [
		"first_name",
		"email",
		"phone_number"
	]
}'

    

Validates CSV rows using rules such as required fields and returns row-level validation output, valid row counts, invalid row counts, errors, and warnings.



                                                                            
POST https://creators.zylalabs.com/api/12804/csv+cleanup+and+column+mapping+api/25194/validate+rows
                                                                            
                                                                        

Validate Rows - Endpoint Features

Object Description
Request Body [Required] Json

Free test requests remaining: 3 of 3.


INPUT PARAMETERS


API EXAMPLE RESPONSE

{"ok":true,"validRowsCount":1,"invalidRowsCount":1,"rowErrors":[{"rowNumber":3,"column":"email","rule":"required","valuePreview":""}],"warnings":["Some rows failed validation."],"disclaimer":"This API analyzes and transforms CSV text for import preparation. Review cleaned data before using it in production systems."}

Validate Rows - CODE SNIPPETS


curl --location --request POST 'https://zylalabs.com/api/12804/csv+cleanup+and+column+mapping+api/25194/validate+rows' --header 'Authorization: Bearer YOUR_API_KEY' 

--data-raw '{
	"csvText": "name,email,age\nAlice,[email protected],31\nBob,,42",
	"rules": {
		"name": {
			"required": true
		},
		"email": {
			"required": true
		}
	}
}'

    

Applies mapping and validation rules to submitted CSV text, then returns cleaned CSV-style output and validation results.



                                                                            
POST https://creators.zylalabs.com/api/12804/csv+cleanup+and+column+mapping+api/25195/clean+csv
                                                                            
                                                                        

Clean CSV - Endpoint Features

Object Description
Request Body [Required] Json

Free test requests remaining: 3 of 3.


INPUT PARAMETERS


API EXAMPLE RESPONSE

{"ok":true,"normalizedHeaders":["first_name","email"],"cleanedRows":[{"first_name":"Alice","email":"[email protected]"},{"first_name":"Bob","email":""}],"importReadyCsvText":"first_name,email\nAlice,[email protected]\nBob,\n","warnings":["Some rows failed validation during cleaning.","Row 3: email failed required"],"disclaimer":"This API analyzes and transforms CSV text for import preparation. Review cleaned data before using it in production systems."}

Clean CSV - CODE SNIPPETS


curl --location --request POST 'https://zylalabs.com/api/12804/csv+cleanup+and+column+mapping+api/25195/clean+csv' --header 'Authorization: Bearer YOUR_API_KEY' 

--data-raw '{
	"csvText": "First Name,Email Address\nAlice,[email protected]\nBob,",
	"mapping": {
		"First Name": "first_name",
		"Email Address": "email"
	},
	"rules": {
		"email": {
			"required": true
		}
	}
}'

    

Returns a preview of CSV rows so users can inspect data before import.



                                                                            
POST https://creators.zylalabs.com/api/12804/csv+cleanup+and+column+mapping+api/25196/csv+preview
                                                                            
                                                                        

Csv Preview - Endpoint Features

Object Description
Request Body [Required] Json

Free test requests remaining: 3 of 3.


INPUT PARAMETERS


API EXAMPLE RESPONSE

{"ok":true,"firstRows":[{"name":"Alice","email":"[email protected]"},{"name":"Bob","email":"[email protected]"},{"name":"Cara","email":"[email protected]"}],"detectedHeaders":["name","email"],"normalizedPreview":[{"name":"Alice","email":"[email protected]"},{"name":"Bob","email":"[email protected]"},{"name":"Cara","email":"[email protected]"}],"issuesSummary":{"rowCount":3,"columnCount":2,"duplicateHeaders":[],"blankHeaders":[],"hasIssues":false},"disclaimer":"This API analyzes and transforms CSV text for import preparation. Review cleaned data before using it in production systems."}

Csv Preview - CODE SNIPPETS


curl --location --request POST 'https://zylalabs.com/api/12804/csv+cleanup+and+column+mapping+api/25196/csv+preview' --header 'Authorization: Bearer YOUR_API_KEY' 

--data-raw '{
	"csvText": "name,email\nAlice,[email protected]\nBob,[email protected]\nCara,[email protected]"
}'

    

API Access Key & Authentication

After signing up, every developer is assigned a personal API access key, a unique combination of letters and digits provided to access to our API endpoint. To authenticate with the CSV Cleanup and Column Mapping API simply include your bearer token in the Authorization header.
Headers
Header Description
Authorization [Required] Should be Bearer access_key. See "Your API Access Key" above when you are subscribed.

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CSV Cleanup and Column Mapping API FAQs

Each endpoint returns structured data related to CSV analysis, column mapping, validation, preview, and cleaning. Responses may include row and column counts, detected headers, duplicate headers, blank headers, column type guesses, mapping suggestions, row-level errors, cleaned CSV text, preview rows, warnings, and disclaimers.

Key fields include `rowCount`, `columnCount`, `originalHeaders`, `normalizedHeaders`, `validRowsCount`, `invalidRowsCount`, and `cleanedRows`. These fields provide insights into the CSV structure and validation status.

Parameters vary by endpoint but generally include the CSV text to analyze, mapping specifications for columns, and validation rules for rows. Users can customize requests by specifying the CSV content and desired mapping fields.

Response data is organized in JSON format, with a top-level `ok` field indicating success, followed by relevant data fields such as counts, headers, and validation results. This structure allows easy parsing and integration into applications.

Typical use cases include preparing CSV files for import, checking required fields before processing, finding duplicate or blank headers, previewing rows, and mapping source columns to target fields for CSV import workflows.

The API performs technical checks on submitted CSV text, including required field validation, type guesses, duplicate header detection, blank header detection, and row-level validation. Results may include warnings and errors for items that need review before import.

Users can review validation results, row-level errors, warnings, mapping suggestions, preview rows, and cleaned CSV output to decide what needs review before import. The returned data can support CSV import preparation, but it does not guarantee acceptance by a destination system.

Standard data patterns include row and column counts, detected headers, normalized headers, type guesses, missing expected fields, duplicate headers, blank headers, row-level validation errors, preview rows, cleaned CSV text, warnings, and disclaimers.

The Analyze CSV endpoint provides row count, column count, detected headers, duplicate headers, blank headers, inferred data types, missing expected fields, warnings, and disclaimer information for submitted CSV text.

The 'score' in the Map Columns response indicates the confidence level of the suggested mapping between source columns and target fields. A higher score suggests a better match, helping users make informed decisions on which mappings to apply.

General FAQs

To obtain your API key, first sign in to your account and navigate to the API you want to use. From the API's Pricing section, choose a plan and complete the subscription process. Once subscribed, return to the API page and you will see your API Access Key displayed at the top of the documentation page. You can use this key to authenticate your requests.

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Prices are determined by a recurring monthly or yearly subscription, depending on the chosen plan.
API calls are deducted from your plan based on successful requests. Each plan comes with a specific number of calls that you can make per month. Only successful calls, indicated by a Status 200 response, will be counted against your total. This ensures that failed or incomplete requests do not impact your monthly quota.
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 Response Time
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