CSV Parser - Parse & View CSV Data Online
Parse and view CSV (Comma-Separated Values) files online. Our CSV parser reads your data, displays it in a readable table format, and helps you understand the structure of your comma-separated data—perfect for data analysis, debugging, and quick data inspection.
What Is CSV?
CSV (Comma-Separated Values) is a simple file format used to store tabular data in plain text. Each line represents a row, with values separated by commas (or other delimiters). CSV is universally supported and remains one of the most common formats for data exchange.
Example CSV:
name,age,city
John,30,New York
Jane,25,Los Angeles
How to Use
- Paste CSV data - Enter your comma-separated content
- Set delimiter - Choose comma, semicolon, tab, or custom
- Enable/disable header row - First row as column names
- Click "Parse" - View data in table format
- Analyze results - Explore your structured data
Key Features
- Multiple delimiters - Comma, semicolon, tab, pipe, or custom
- Header detection - Automatic or manual first row handling
- Table visualization - Clear, sortable data display
- Quote handling - Proper parsing of quoted fields
- Row/column counts - Understand data dimensions
- Error detection - Identify malformed rows
Understanding CSV Structure
Basic Format
column1,column2,column3
value1,value2,value3
With Quoted Fields
Quotes are used when values contain commas or newlines:
name,description,price
"Widget","A small, useful item",9.99
"Gadget","Multi-line
description",19.99
Different Delimiters
Not all CSVs use commas:
| Delimiter | Example | Common In |
|---|---|---|
Comma , | a,b,c | Default CSV |
Semicolon ; | a;b;c | European locales |
Tab \t | a b c | TSV files |
Pipe | | a|b|c | Unix/Linux data |
Use Cases
Data Analysis
- Preview data files - Quick look at contents
- Validate structure - Check for consistency
- Count records - Know your data size
- Identify issues - Find malformed rows
- Prepare for import - Verify before database import
Development & Integration
- API response debugging - Parse CSV responses
- Data migration - Verify export/import data
- ETL processes - Inspect intermediate data
- Log file analysis - Query structured logs
- Testing data - Validate test fixtures
Business Operations
- Spreadsheet preview - View Excel exports
- Report inspection - Check report data
- Customer data - Verify CRM exports
- Financial data - Review transaction logs
- Inventory management - Check product lists
Common CSV Issues
| Issue | Symptoms | Solution |
|---|---|---|
| Wrong delimiter | All data in single column | Change delimiter setting |
| Missing quotes | Split field appears as multiple | Add quotes around problematic values |
| Inconsistent columns | Some rows have more/fewer fields | Fix source data or handle in code |
| Encoding issues | Strange characters | Ensure UTF-8 encoding |
| Trailing commas | Empty last column | Remove trailing commas |
CSV Best Practices
When Creating CSV Files
- Use headers - First row should be column names
- Quote text fields - Especially if they might contain delimiters
- Escape quotes - Double quotes within quoted fields (
"") - Consistent columns - Same number of fields per row
- UTF-8 encoding - For international character support
When Parsing CSV
- Specify encoding - Default UTF-8, but check source
- Handle edge cases - Empty fields, quotes, newlines
- Validate data types - Numbers, dates, strings
- Check for duplicates - If uniqueness matters
- Handle errors gracefully - Log and continue or fail
CSV vs. Other Formats
| Format | Pros | Cons | Best For |
|---|---|---|---|
| CSV | Universal, simple | No types, flat structure | Data exchange |
| JSON | Nested data, typed | Larger file size | APIs, configs |
| Excel | Rich formatting | Binary format | Business users |
| Parquet | Compressed, fast | Complex to read | Big data |
Frequently Asked Questions
What's the maximum file size I can parse?
This browser-based tool handles files up to several megabytes well. For very large files (100MB+), consider using desktop tools or programming libraries.
Can I parse Excel files?
This tool is for CSV (plain text). Export your Excel file as CSV first: File → Save As → CSV.
Why are my numbers showing as text?
CSV is pure text—numbers have no inherent type. Applications that read CSV decide how to interpret each value.
How do I handle commas inside my data?
Wrap fields containing commas in double quotes: "Hello, World". The parser will treat the entire quoted string as one field.
Why does my CSV look different in Excel vs. this parser?
Excel may interpret some values as dates or apply regional settings (semicolons vs. commas). This parser shows the raw, uninterpreted data.
Can I edit and download the parsed data?
Currently, this is a read-only preview tool. For editing, use our CSV Editor or a spreadsheet application.