Extract Table From PDF using n8n action

PDF4me Extract Table From PDF identifies and extracts structured table data from PDF documents through n8n automation workflows. Process PDFs via n8n triggers, binary data, base64 strings, or public URLs to automatically detect tables, preserve cell structure, maintain data relationships, extract headers and values, and output structured data in JSON or Excel format. This solution is ideal for financial report analysis, data digitization, statistical data extraction, invoice processing, form analysis, and automated table extraction workflows that require accurate table recognition with structured output and seamless integration.

Setup

Add the PDF4me "Extract Table From PDF" node to your n8n workflow and configure the required parameters. For initial setup instructions, see our n8n Integration Guide.

Prerequisites:

• PDF4me API credentials
• n8n workflow access

Get Your API Key

Configuration:

1. Add PDF4me node to workflow
2. Select "Extract Table From PDF" action
3. Configure input parameters (see below)

Parameters

Complete list of parameters for the Extract Table From PDF action. Configure these parameters to control table extraction.

Important: Parameters marked with an asterisk (***) are required and must be provided for the action to function correctly.

Parameter	Type	Description	Example
Input Data Type***	String	PDF Input Format Selection • Choose the format of your PDF data input • PDF4me supports multiple input types • Options: Binary Data, Base64 String, or URL	Binary Data
Input Binary Field	Binary	Binary PDF File Input (Required if Binary Data) • Reference PDF file from previous n8n node or file upload • PDF4me processes binary PDF files with automatic format detection • Required when Input Data Type is "Binary Data"	{{ $binary.data }}
Base64 Document Content	String	Base64 Encoded PDF Input (Required if Base64 String) • Provide PDF data as base64 encoded string • PDF4me automatically decodes and processes the PDF content • Required when Input Data Type is "Base64 String"	UEsDBBQABgAI...
File URL	String	Public PDF URL Input (Required if URL) • Provide a public/open permission URL to the PDF file • PDF4me downloads and processes the file from URL • Required when Input Data Type is "URL"	https://abc.com/report.pdf
Document Name***	String	Source PDF Reference • Specify the name of the source PDF file • For reference and tracking purposes in table extraction • Helps with processing tracking	financial_report.pdf

Advanced Options

The following parameters are available in the Advanced Options section and are optional:

Parameter	Type	Description	Example
Custom Profiles	String	Custom Configuration Profiles • Set additional options using custom profiles • JSON-like format containing predefined parameters • Enables advanced table processing settings • Optional for specialized requirements	{ "OutputDataFormat": "json" }

Supported Table Types

Table Type	Description	Common Use Cases
Financial Tables	Financial statements, budgets, and accounting data	Financial reports, invoices, balance sheets
Data Tables	Statistical data, metrics, and analytical information	Research reports, analytics, performance data
List Tables	Product catalogs, directories, and inventory lists	Product listings, employee directories, catalogs
Comparison Tables	Feature comparisons, pricing tables, and specifications	Product comparisons, pricing matrices, specifications
Schedule Tables	Timetables, calendars, and planning documents	Meeting schedules, project timelines, calendars
Summary Tables	Executive summaries, key metrics, and overview data	Dashboard data, KPI summaries, executive reports

Table Processing Features

Feature	Description	Use Case
Table Detection	Automatic identification of table boundaries and structures	Processing documents with multiple tables
Cell Extraction	Precise extraction of individual cell values and content	Data analysis and processing
Header Recognition	Identification of table headers and column labels	Structured data organization
Row Processing	Extraction of complete table rows with proper formatting	Database integration and storage
Column Alignment	Preservation of column structure and alignment	Maintaining data relationships
Multi-Page Tables	Processing tables that span across multiple pages	Complex document analysis

Output

Output Parameters

Parameter	Type	Description	Example
fileName	String	PDF4me output file name - Name of the generated JSON file containing the extracted table data. The file contains all structured table information in JSON format	table_extraction_results_1756997087699.json
mimeType	String	PDF4me file MIME type - MIME type of the output file, always "application/json" for JSON format table data	application/json
fileSize	Number	PDF4me file size in bytes - Size of the generated JSON file in bytes, provided for storage planning and transfer monitoring	563
success	Boolean	PDF4me extraction status indicator - Boolean flag indicating the success or failure of the table extraction process. PDF4me returns true for successful extractions and false for any errors	true
message	String	PDF4me extraction status message - Human-readable status message providing details about the table extraction process result. Includes success confirmation or error details for troubleshooting	Table extraction completed successfully
docName	String	PDF4me source document reference - Original filename of the PDF document that was processed for table extraction	document.pdf

N8N Action Response

The PDF4me Extract Table From PDF API returns a response that can be viewed in multiple formats. Choose the view that best fits your needs:

JSON

JSON Response Format

The raw JSON response from the API:

[
  {
    "fileName": "table_extraction_results_1756997087699.json",
    "mimeType": "application/json",
    "fileSize": 563,
    "success": true,
    "message": "Table extraction completed successfully",
    "docName": "document.pdf"
  }
]

Table

Table View

Response data in a structured table format:

Parameter	Value
fileName	table_extraction_results_1756997087699.json
mimeType	application/json
fileSize	563
success	true
message	Table extraction completed successfully
docName	document.pdf

Schema

Schema View

The data structure and types of the response:

1 item
fileName: AB table_extraction_results_1756997087699.json
mimeType: AB application/json
fileSize: # 563
success: ☑ true
message: AB Table extraction completed successfully
docName: AB document.pdf

Type Indicators:

• AB = String
• # = Number
• ☑ = Boolean
• {} = Object
• [] = Array

Binary

Binary Data View

The actual JSON file data and metadata:

data
─────────────────────────────
File Name: table_extraction_results_1756997087699.json
File Extension: json
Mime Type: application/json
File Size: 0.55 KB

JSON File Content Example:

{
  "tableData": [
    {
      "headers": ["Product", "Price", "Quantity", "Total"],
      "rows": [
        ["Laptop", "$999", "2", "$1998"],
        ["Mouse", "$25", "5", "$125"],
        ["Keyboard", "$75", "3", "$225"]
      ],
      "columnCount": 4,
      "rowCount": 3
    }
  ]
}

Use Cases

Data Processing and Analysis

• Automated Data Import: Download and process the generated JSON file to automatically import tabular data into databases, spreadsheets, or business applications
• Data Transformation: Process the JSON file content to transform table data into different formats for various business systems
• Statistical Analysis: Analyze extracted tabular data from the JSON file to generate insights, trends, and statistical reports

Business Intelligence and Reporting

• Report Automation: Automatically extract data from financial reports, invoices, and business documents, then process the JSON file for automated reporting
• Dashboard Integration: Parse the JSON file and feed extracted table data into business intelligence dashboards and analytics platforms
• Data Validation: Validate and verify tabular data extracted from the JSON file against existing business records

Document Processing and Management

• Invoice Processing: Extract pricing tables, line items, and financial data from invoices, then process the generated JSON file for automated processing
• Contract Analysis: Extract terms, conditions, and structured data from contracts and legal documents using the downloadable JSON file
• Inventory Management: Process product catalogs, inventory lists, and supply chain data from PDF documents via the JSON output file

Enterprise Integration

• System Integration: Download and integrate the JSON file with existing enterprise systems including ERP, CRM, and data warehouses
• Workflow Automation: Trigger automated workflows based on JSON file processing and extracted tabular data
• Data Synchronization: Process the JSON file and synchronize extracted data across multiple systems and platforms for consistent information management

Get Help

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