Parse CSV in Make
Parse CSV is a data transformation operation that reads a delimited text file and converts each row into a structured JSON object, using either the first-row headers or custom column names you define. The PDF4me Parse CSV module in Make supports any delimiter character, culture-specific date and number formatting, and outputs a Base64-encoded JSON array ready to iterate or insert into any downstream system. For CSV format standards, see RFC 4180 and Microsoft Excel import guidance.
What this module does
PDF4me Excel, Parse CSV converts any CSV file into a structured JSON array in your Make scenario, supporting any delimiter, custom or auto-detected headers, and culture-specific number and date formatting. Feed the output directly into a database insert, REST API call, Excel row addition, or Iterator to loop through records. No manual column mapping, no intermediate conversion steps, CSV in, structured JSON out, ready to use in the next module.
Authenticating Your API Request
Every PDF4me module in Make requires a valid Connection. Create or select one that holds your PDF4me API key so the scenario can authenticate CSV parsing requests securely.
Important Facts You Should Not Miss

CSV Delimiter defaults to comma. Column Headers and Culture Name allow flexible handling of international and headerless CSV formats.
Parameters
Required: Connection, File Name, and Document must be provided. CSV Delimiter, Column Headers, Skip First Line, and Culture Name are optional, defaults are comma delimiter, auto-generated headers, and en-US culture.
| Parameter | Required | What it does | Example |
|---|---|---|---|
| Connection | Yes | PDF4me API connection. Click Add and paste your API key if connecting for the first time. | Your PDF4me connection |
| File Name | Yes | CSV filename including extension (.csv or .txt). Map from the prior module's file name output. | sales_data.csv |
| Document | Yes | CSV file content as a binary buffer from a cloud storage download, email attachment, or HTTP response. | 1. Data |
| CSV Delimiter | No | Character separating columns in the CSV. Defaults to comma. Use semicolon for European CSVs, \t for TSV, or any custom string your source uses. | , or ; or \t |
| Column Headers | No | Custom column names as a comma-separated list. Used as JSON property names in the output. When provided, Skip First Line is ignored. | Name,Age,Email |
| Skip First Line | No | Yes skips the first data line (useful for title rows above headers). No treats all lines as data. Ignored when Column Headers is set. | No |
| Culture Name | No | Locale code for date and number interpretation. Defaults to en-US. Change to match your source data region: e.g. de-DE for German format. | en-US |
Output
| Field | Type | What it contains |
|---|---|---|
| document | String (Base64) | A Base64-encoded JSON array. Each element is an object whose keys are column header names and values are cell data. Decode with Make built-in functions, then pass to an Iterator to loop through records. |
How to Parse a CSV File in Make
- Add PDF4me Excel → CSV - Parse a CSV file to your Make scenario.
- Select Connection (or click Add to create one with your API key).
- Map File Name and Document from a prior module: a Google Drive download, Dropbox file, email attachment, or HTTP response.
- Set CSV Delimiter to match your file format: comma (
,) for standard CSV, semicolon (;) for European, or\tfor tab-separated. - If the file has a header row, leave Column Headers empty and Skip First Line at its default. If there is no header row, enter your own names in Column Headers.
- Set Culture Name if your file uses non-US date or number formatting, then click Save and run. The document output contains the parsed JSON array as Base64: decode it and pass to an Iterator or downstream module.
When Should I Use Parse CSV in Make?
When Should I Use Parse CSV in Make?Common Make scenario patterns using Parse CSV.
- A Google Drive Watch Folder triggers when a new CSV export lands in the import folder.
- Parse CSV runs with comma delimiter and Skip First Line at default, the first row headers become JSON property names.
- A Make Iterator loops through each record in the decoded JSON array.
- An HTTP module posts each record to the database API. Errors are logged to a Google Sheet for review.
- A scheduled hourly trigger retrieves the latest export from Dropbox, a semicolon-delimited European CSV.
- Parse CSV runs with CSV Delimiter set to ";" and Culture Name set to "de-DE" to correctly interpret German date and number formats.
- An Iterator loops through the parsed records and an HTTP module POSTs each one to the target REST API endpoint.
- A Slack message reports the sync count and any failures to the integration team channel.
- A daily scheduled trigger downloads a tab-separated export from SharePoint, the file has no header row.
- Parse CSV runs with CSV Delimiter "\t" and Column Headers "ID,Name,Amount,Date" to assign meaningful names to the columns.
- An Add Rows module populates a branded Excel template with the parsed records.
- The finished report is uploaded to Google Drive and emailed to the business team.