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Update Rows in Excel - Data Modifier for Make

PDF4me Update Rows in Excel module enables in-place modification of existing rows in Excel documents using JSON data within Make scenarios with intelligent header matching and automatic type conversion. This powerful data update service modifies cells without inserting or deleting rows, using automatic matching of JSON property names to column headers, with support for automatic conversion of strings to numbers/dates, culture-specific parsing, customizable date/numeric formatting, and null value handling—perfect for automated database synchronization, record updates, and data refresh workflows across cloud storage platforms and business applications.

Authenticating Your API Request

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

Update Rows in Excel Make

Key Features

  • In-Place Updates: Modify existing cells without inserting or deleting rows
  • Header Matching: Automatically match JSON property names to Excel column headers
  • Sequential Row Updates: Update multiple consecutive rows starting from specified row
  • Automatic Type Conversion: Convert JSON strings to Excel numbers and dates automatically
  • Format Customization: Apply custom date and numeric formatting patterns
  • Culture Support: Parse dates and numbers according to specified culture codes
  • Null Value Handling: Option to skip null values or update as empty cells

Parameters

Complete list of parameters for the Update Rows in Excel module. Configure these parameters to control data update behavior.

Important: Parameters marked with an asterisk (***) are required and must be provided for the module to function correctly. Json Data must be a JSON array.

ParameterTypeDescriptionExample
File Name***StringExcel Filename
• Specify filename with .xlsx or .xls extension
• Map from previous module output
• Used for output file identification
• Supports dynamic naming from scenario variables
sales_data.xlsx
Document***BufferExcel File Content
• Map Excel file buffer from previous module
• Source from Dropbox, Google Drive, HTTP request
• Binary Excel data to update existing rows
• Contains existing worksheet structure
[Buffer from Get File]
Json Data***StringJSON Array of Objects to Update
Must be a JSON array - single objects NOT supported
• Each object updates one row sequentially
• Property names must match column headers
Array Format: [{"Name":"John","Age":31},{"Name":"Jane","Age":29}] - Multiple rows
Single Object: Must wrap in array [{"Name":"John","Age":31}]
• ❌ Invalid: {"Name":"John"} (will cause error)
[{"Product":"Widget","Price":55.99}]
Worksheet NameStringTarget Worksheet Name
• Name of worksheet to update
• Default: "Sheet1" if not specified
• Must match worksheet name exactly
• Case-sensitive worksheet matching
Sales
Start RowIntegerFirst Row to Update
• 1-based row number to start updating
• Default: 1 (typically use 2 or higher for data rows)
• Row 1 is usually headers
• Updates proceed sequentially from this row
2
Start ColumnIntegerHeader Column Offset
• 1-based column offset for header matching
• Default: 1 (column A)
• Allows skipping initial columns
• Affects which headers are mapped
1
Convert Numeric And DateBooleanEnable Type Conversion
• Yes - Convert JSON strings to Excel numbers/dates
• No - Insert all values as-is without conversion
• Applies DateFormat and NumericFormat when enabled
• Default: Yes for intelligent type handling
Yes
Date FormatStringExcel Date Format Pattern
• Excel date format to apply
• Examples: "yyyy-MM-dd", "MM/dd/yyyy", "dd-MMM-yyyy"
• Default: "yyyy-MM-dd"
• Used when Convert Numeric And Date enabled
MM/dd/yyyy
Numeric FormatStringExcel Numeric Format Pattern
• Excel numeric format to apply
• Examples: "N2", "#,##0.00", "$#,##0.00"
• Default: "N2"
• Used when Convert Numeric And Date enabled
#,##0.00
Ignore Null ValuesBooleanNull Value Handling
• Yes - Skip updating cells with null values
• No - Update cells to empty when JSON has null
• Default: No
• Preserves existing values when true
No
Ignore Attribute TitlesBooleanCase-Insensitive Matching
• Yes - Case-insensitive header matching
• No - Case-sensitive matching
• Default: No
• Useful for flexible JSON property naming
Yes
Culture NameStringCulture for Date/Number Parsing
• Culture code for parsing (e.g., "en-US", "de-DE")
• Default: "en-US"
• Affects date and number interpretation
• Important for international data
en-US

Output

The PDF4me Update Rows in Excel module returns comprehensive output data for seamless Make scenario integration:

Table View

Response data in a structured table format:

ParameterTypeDescription
NameStringOutput Excel filename with updated data
Doc DataBufferExcel document with modified rows in Buffer format

Scenario Examples

The PDF4me Update Rows in Excel module in Make provides comprehensive scenario templates designed for real-world data synchronization needs:

Automated Database-to-Excel Sync Scenario

Keep your Excel reports in sync with database changes automatically:

Complete Scenario Steps:

  1. Trigger: Scheduled trigger runs every 4 hours for data refresh
  2. Query Database: Execute SQL query to fetch updated records since last sync
  3. Format JSON: Convert SQL results to JSON array format with proper property names
  4. Get Excel Report: Fetch master report template from Google Drive
  5. Update Rows: Modify existing rows with fresh data starting at row 2
  6. Set Parameters: ConvertNumericAndDate = Yes, IgnoreNullValues = Yes
  7. Apply Formats: DateFormat = "MM/dd/yyyy", NumericFormat = "$#,##0.00"
  8. Upload Result: Save updated Excel to Google Drive replacing old version
  9. Email Team: Send notification of data refresh completion to team
  10. Log Sync: Record sync timestamp and record count in sync log

Business Benefits:

  • Syncs 500+ database records to Excel 6 times daily automatically
  • Eliminates manual data entry and reduces errors by 100%
  • Ensures Excel reports always reflect current database state
  • Maintains Excel formulas and formatting while updating data

Industry Use Cases & Applications

  • CRM Opportunity Updates: Modify opportunity rows in Excel with latest status, amounts, and close dates
  • Campaign Performance Refresh: Update campaign metrics rows with current impressions, clicks, conversions
  • Lead Score Updates: Refresh lead scoring data in Excel tracking sheets from marketing automation
  • Customer Database Sync: Update customer record rows with latest contact info and purchase history
  • Sales Forecast Updates: Modify forecast rows with updated pipeline data and win probabilities

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