How does this tool handle commas, newlines, and quotation marks inside CSV cells?

RFC 4180 specifies that fields containing the delimiter character, carriage returns, newlines, or double quotes must be enclosed within double quotation marks. Any literal double quote inside such a field is escaped by doubling it (i.e. ""). This tool implements a complete deterministic finite state machine parser that accurately extracts multiline cells, embedded commas, and escaped quotes without corrupting row or column boundaries.

How does auto-type detection work for numbers, booleans, and nulls?

When "Auto-Parse Numbers" is enabled, strings representing valid integers, floating-point decimals, or scientific notation are converted to JavaScript numbers. The strings "true" and "false" (case-insensitive) are converted to native booleans, and empty cells or "null" strings are converted to null values. If you need to preserve exact text representation—such as phone numbers or postal codes with leading zeros (e.g. "07030")—simply uncheck the auto-parse options.

What should I do if my CSV contains duplicate column headers?

In standard JSON, object keys must be unique; duplicate keys result in later columns overwriting earlier values. When our parser detects duplicate column names in the header row, it automatically appends a numeric suffix (e.g. "status", "status_2", "status_3") to prevent silent data loss. You can also select the "2D Array (Matrix)" format to preserve duplicate headers as raw row entries.

Can this tool parse European CSV files that use semicolons and decimal commas?

Yes. In many European countries (Germany, France, Italy, Spain), localized versions of Microsoft Excel export CSV files with semicolon (;) delimiters because commas (,) serve as decimal separators (e.g. 1.250,50). Select "Semicolon (;)" or enable "Auto-Detect" to parse European CSV and TSV spreadsheets seamlessly.

Is my CSV data uploaded to an external server or stored in the cloud?

No. The entire conversion, tokenization, table preview, and formatting process executes locally in your browser memory using client-side JavaScript. Zero bytes of your text or files are uploaded to any server, ensuring complete confidentiality for proprietary business spreadsheets and customer records.

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RFC 4180 Compliant Auto-Delimiter Detection Zero Server Uploads

CSV to JSON Converter & Delimited Table Parser

Convert CSV, TSV, and delimited spreadsheet data into structured JSON arrays, matrices, or keyed objects. Features RFC 4180 state machine tokenization, automatic delimiter detection, intelligent type casting, interactive preview table, and 100% client-side execution.

Need to convert in the opposite direction? Transform JSON arrays back into RFC 4180 CSV spreadsheets with our JSON to CSV Converter.

CSV / Delimited Input

Tip: Drag and drop any .csv, .tsv, or .txt file directly into the editor 📂 Browse File

Delimiter

Output Structure

Indentation

First Row is Header Parse Numbers Parse Booleans Parse Nulls Trim Whitespace

Rows: 0 Cols: 0 Payload: 0 B Delimiter: Auto

JSON Output Ready

📊 Live Parsed Data Table

Visual table preview of parsed records

📐 RFC 4180 State Machine Architecture & Type Casting

Parsing delimited tabular data reliably requires a deterministic finite state machine rather than simple String.split(',') calls. Here is how our browser engine processes your dataset:

1. UTF-8 Byte Order Mark Stripping: Files exported from Excel on Windows begin with the invisible UTF-8 BOM sequence (0xEF, 0xBB, 0xBF or Unicode \uFEFF). If not stripped, the first column header becomes "\uFEFFid" instead of "id", causing silent lookup failures in code.

2. Quote State Tracking (RFC 4180 §2.5): When encountering an opening quotation mark, the tokenizer enters Quoted State. Inside this state, commas, tabs, semicolons, and CRLF line breaks are treated as literal cell content. Escaped quotes ("") are unescaped into single quotes.

3. Auto-Delimiter Histogram Scoring: The engine samples up to 4,000 characters and computes frequency distributions for commas, semicolons, tabs, and pipes outside of quote boundaries to determine the true delimiter without user intervention.

4. Strict Primitive Coercion: Values matching /^-?\d+(\.\d+)?([eE][+-]?\d+)?$/ without arbitrary leading zeros (except decimal fractions) are cast to IEEE 754 numbers; boolean strings (true/false) become native booleans; empty or null tokens resolve to JavaScript null.

⚠️ 5 Fatal Traps in CSV to JSON Conversion & ETL Pipelines

1. The Unescaped Double Quote & Commas Inside Quotes Trap Naively splitting lines on commas with line.split(',') catastrophically shatters any record with an address ("123 Main St, Apt 4") or product title into split columns. Subsequent fields shift to the wrong headers, corrupting relational schemas and database insertions. Always use an RFC 4180 compliant state-machine tokenizer.

2. The UTF-8 BOM Phantom Header Bug When Excel exports UTF-8 CSVs, it injects a 3-byte Byte Order Mark (\uFEFF) at index 0. If your script accesses record.id or record["id"], it returns undefined because the actual key in memory is record["\uFEFFid"]. This is one of the most frustrating hidden bugs in backend Node.js and Python ETL scripts.

3. European Semicolon (;) & Decimal Comma Confusion In European locales, commas denote decimals (e.g. €1.499,50) and semicolons separate columns. Parsing a German CSV with a comma-delimiter splits every financial number into two separate broken cells. Our auto-detection ensures European semicolon formats are parsed smoothly.

4. Leading Zero Stripping on ZIP Codes & Account Numbers Casting all numeric tokens to numbers destroys data integrity for US postal ZIP codes (e.g. New Jersey 07030 becomes integer 7030), phone numbers (+011...), and international IBAN/routing numbers. If your CSV contains leading-zero identifiers, uncheck "Parse Numbers" to preserve strings intact.

5. Duplicate Column Header Overwrite in JSON Objects If a CSV contains two columns with the same name (for example, two tables joined in SQL yielding two created_at columns), converting to an Array of Objects causes the second value to silently overwrite the first. Our converter automatically appends numerical suffixes (created_at_2) or allows conversion to a 2D Array matrix where duplicates are preserved.

📊 Live Parsed Data Table

📐 RFC 4180 State Machine Architecture & Type Casting

⚠️ 5 Fatal Traps in CSV to JSON Conversion & ETL Pipelines

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