Extract Rows from Excel - JSON Export for Zapier

PDF4me Extract Rows from Excel bridges the gap between spreadsheets and modern applications. Export Excel data as clean JSON that any API, database, or web service can consume—whether you need the entire dataset or just a specific range. Smart filtering options let you skip hidden rows and empty cells automatically, while flexible type handling preserves numbers, dates, and booleans as native JSON types or exports everything as text for maximum compatibility. Perfect for building Excel-to-database pipelines, feeding analytics platforms, or integrating spreadsheet data into your existing tech stack.

Authenticating Your API Request

To access the PDF4me Web API through Zapier, every request must include proper authentication credentials. Authentication ensures secure communication and validates your identity as an authorized user, enabling seamless integration between your Zapier workflows and PDF4me's powerful Excel data extraction services.

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Key Features

• JSON Output Format: Extract Excel data as structured JSON for seamless integration
• Flexible Row/Column Selection: Specify exact ranges or extract all data
• Header Row Support: Use first row as headers or auto-generate column names
• Advanced Filtering: Exclude hidden rows, hidden columns, and empty rows
• Data Type Control: Export as native types (numbers, dates) or all as text
• Empty Cell Handling: Include or exclude empty cells from output

Parameters

Complete list of parameters for the Extract action. Configure these parameters to control data extraction behavior.

Important: Parameters marked with an asterisk (***) are required and must be provided for the action to function correctly. All row/column indexes use 0-based numbering (Row 0 = first row, Column 0 = column A).

Parameter	Type	Description	Example
File Name***	String	Excel Document Name • Filename with .xlsx or .xls extension • Used for processing and output identification • Supports dynamic naming from Zap variables	data.xlsx
Document***	File	Excel File Content • Map from previous step (Drive/Dropbox/HTTP) • Binary Excel document for data extraction • Must be valid Excel format	[File]
Worksheet Name	String	Target Worksheet Name • Name of worksheet to extract from • Empty defaults to first worksheet • Case-sensitive exact matching	Sheet1
First Row***	Integer	Starting Row (0-based) • First row to extract (0-based indexing) • Row 0 = Excel row 1, Row 1 = Excel row 2 • Must be ≥ 0 • Required parameter	0
Last Row	Integer	Ending Row (0-based) • Last row to extract (0-based indexing) • -1 = extract to last row with data • Default: -1 • Must be ≥ First Row	-1
First Column	Integer	Starting Column (0-based) • First column to extract (0-based indexing) • Column 0 = A, Column 1 = B, Column 2 = C • Default: 0 • Must be ≥ 0	0
Last Column	Integer	Ending Column (0-based) • Last column to extract (0-based indexing) • -1 = extract to last column with data • Default: -1 • Must be ≥ First Column	-1
Has Header Row	Boolean	First Row as Headers • True - Use First Row as column headers • False - Auto-generate headers ("Column1", "Column2"...) • Default: false	true
Exclude Hidden Rows	Boolean	Skip Hidden Rows • True - Skip rows that are hidden in Excel • False - Include hidden rows in extraction • Default: false	false
Exclude Hidden Columns	Boolean	Skip Hidden Columns • True - Skip columns that are hidden in Excel • False - Include hidden columns in extraction • Default: false	false
Exclude Empty Rows	Boolean	Skip Empty Rows • True - Skip rows where all cells are empty • False - Include empty rows in output • Default: false	false
Export Empty Cells	Boolean	Include Empty Cells • True - Include empty cells with empty string values • False - Omit empty cells from JSON output • Default: false	false
Export Values As Text	Boolean	Text Export Mode • True - Export all values as text strings • False - Preserve data types (numbers, dates, booleans) • Default: false	false

Output

The PDF4me Extract Rows from Excel action returns comprehensive JSON output data for seamless Zapier workflow integration:

Table

Table View

Response data in a structured table format:

Parameter	Type	Description
document	Base64	JSON data as byte array (serialized)
RowData	Array	Extracted rows as array of objects with column name keys
Success	Boolean	Operation result

JSON

JSON Response Format

The raw JSON response from the action:

{
  "document": "[Base64 JSON Data]",
  "RowData": [
    {
      "Name": "John Doe",
      "Age": 30,
      "Salary": 50000.50
    },
    {
      "Name": "Jane Smith",
      "Age": 28,
      "Salary": 55000.00
    }
  ],
  "Success": true
}

Zap Integration

Zapier Workflow Usage

Use extracted JSON data in subsequent steps:

• API Integration: POST JSON rows to external REST APIs
• Database Load: Insert extracted data to SQL/NoSQL databases
• BI Dashboards: Feed extracted data to analytics platforms
• Data Transformation: Process and enrich extracted JSON data

Scenario Examples

The PDF4me Extract Rows from Excel action in Zapier provides comprehensive scenario templates designed for real-world data integration needs:

API Integration

Automated Excel-to-API Data Feed Workflow

Transform your data integration with automated Excel-to-API feeding:

Complete Scenario Steps:

1. Trigger: Scheduled hourly data sync runs every hour
2. Get Excel Report: Retrieve data export Excel from Google Drive
3. Extract All Rows: Set First Row = 0, Last Row = -1 for all data
4. Use Header Row: Set Has Header Row = true to use row 0 as headers
5. Preserve Types: Set Export Values As Text = false for native types
6. Iterate Rows: Loop through RowData array from response
7. POST to API: Send each row object as JSON to REST API endpoint
8. Handle Response: Check API response and log success/failures
9. Email Summary: Send hourly sync summary to integration team
10. Log Completion: Record sync timestamp and row count in log

Business Benefits:

• Syncs 1000+ Excel rows to external API hourly
• Preserves data types (numbers, dates) for accurate API processing
• Eliminates manual CSV exports and API uploads
• Provides real-time data integration between systems

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Database Load

Automated Excel-to-Database Bulk Load Workflow

Streamline your database loading with automated Excel extraction:

Complete Scenario Steps:

1. Trigger: New Excel file uploaded to SharePoint data folder
2. Get Excel File: Retrieve uploaded data file from SharePoint
3. Extract Data Range: Set First Row = 1 (skip title), Last Row = -1
4. Set First Column: Set First Column = 0 to start from column A
5. Use Headers: Set Has Header Row = true for row 1 headers
6. Filter Empty: Set Exclude Empty Rows = true to skip blanks
7. Preserve Types: Export Values As Text = false for SQL compatibility
8. Bulk Insert SQL: Insert RowData array into SQL database table
9. Email Confirmation: Send data load confirmation to data team
10. Archive Source: Move processed Excel to archive folder

Business Benefits:

• Loads 5000+ rows from Excel to database automatically
• Preserves numeric and date types for database integrity
• Eliminates manual database import procedures
• Reduces data load time from 2 hours to 5 minutes

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Data Validation

Automated Excel Data Validation Workflow

Ensure data quality with automated Excel data validation:

Complete Scenario Steps:

1. Trigger: Daily data validation scheduled at 6 AM
2. Get Master Data Excel: Retrieve master data file from Dropbox
3. Extract All Data: Set First Row = 0, Last Row = -1, Has Header Row = true
4. Export as Text: Set Export Values As Text = true for format validation
5. Validate Each Row: Iterate through RowData validating formats
6. Check Email Format: Validate email column matches email regex
7. Check Date Format: Verify date columns match required pattern
8. Check Required Fields: Ensure required columns not empty
9. Generate Report: Create validation error report with row numbers
10. Email Data Team: Send validation report to data quality team

Business Benefits:

• Validates 10,000+ data rows daily automatically
• Text export mode enables regex and format validation
• Identifies data quality issues before downstream processing
• Reduces data errors in production systems by 85%

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Industry Use Cases & Applications

IT & Integration

• API Data Feeds: Extract Excel rows as JSON and POST to REST APIs hourly for system integration
• ETL Pipelines: Load Excel data to data warehouses with preserved data types and transformations
• System Migration: Extract legacy Excel data to JSON for migration to modern cloud systems
• Data Synchronization: Extract and sync Excel master data to multiple downstream systems
• Log Analysis: Extract operational logs from Excel to analytics platforms for monitoring

Finance & Accounting

• Transaction Import: Extract transaction rows from Excel exports for reconciliation and loading
• GL Account Load: Extract chart of accounts from Excel templates to accounting systems
• Budget Data Integration: Extract budget rows with preserved numeric types for BI tools
• Expense Report Processing: Extract employee expense rows as JSON for approval workflows
• Financial Statement Export: Extract P&L and balance sheet rows for consolidation systems

Sales & Marketing

• Campaign Data Export: Extract campaign performance rows to analytics and attribution platforms
• Lead List Integration: Extract lead rows from Excel imports to CRM systems via API
• Sales Pipeline Export: Extract opportunity data as JSON for external forecasting tools
• Customer Data Import: Extract customer rows with preserved data types for marketing automation
• Product Catalog Load: Extract product rows from Excel to e-commerce systems

Operations

• Inventory Data Extract: Extract stock level rows from Excel for warehouse management systems
• Production Log Export: Extract production run data as JSON for manufacturing analytics
• Quality Data Integration: Extract QC inspection rows for quality management platforms
• Equipment Data Load: Extract asset rows from Excel to CMMS and EAM systems
• Logistics Data Export: Extract shipment rows with dates and numbers for TMS integration

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