CSV to JSON Converter — Transform Spreadsheet Data to JSON

CSV to JSON conversion maps each row in a CSV file to a JSON object, using the header row as the object keys. A CSV with 100 rows and 5 columns becomes a JSON array of 100 objects, each with 5 properties.

Use the CSV to JSON converter to paste CSV data and get formatted JSON instantly.

What the conversion looks like

CSV input:

name,age,city,active
Alice,30,New York,true
Bob,25,London,false
Carol,35,Tokyo,true

JSON output:

[
  {"name": "Alice", "age": "30", "city": "New York", "active": "true"},
  {"name": "Bob", "age": "25", "city": "London", "active": "false"},
  {"name": "Carol", "age": "35", "city": "Tokyo", "active": "true"}
]

All values are strings by default. Type coercion (converting "30" to 30 as a number) requires additional handling.

Type coercion in CSV to JSON

CSV has no type system — every cell is a string. When converting to JSON, you often want numeric columns to be numbers and boolean columns to be actual booleans.

Without coercion (default):

{"name": "Alice", "age": "30", "active": "true"}

With coercion:

{"name": "Alice", "age": 30, "active": true}

Most converters offer a “type coercion” or “infer types” option. The logic:

1. If the value matches true/false (case-insensitive) → boolean
2. If parseFloat(value) returns a valid number and String(parseFloat(value)) === value → number
3. Otherwise → string

Handling edge cases in CSV

Quoted fields with commas

CSV standard (RFC 4180) allows fields to contain the delimiter character if the field is quoted:

name,address,city
Alice,"123 Main St, Apt 4",New York

"123 Main St, Apt 4" is one field despite containing a comma. A CSV parser handles this; a naive split(',') would break it.

Quoted fields with newlines

A field can contain newlines if quoted:

name,notes
Alice,"Line one
Line two"

This is valid CSV. The record spans two text lines but is one CSV row.

Escaped quotes

A double quote inside a quoted field is escaped as "":

quote,"He said ""hello""",end

Parses to: { quote: 'He said "hello"' }.

Different delimiters

CSV technically means “comma-separated,” but many spreadsheet exports use tabs (TSV — tab-separated values) or semicolons (common in European locales where the comma is the decimal separator).

The CSV to JSON converter handles comma, tab, and semicolon separators.

How to convert CSV to JSON in code

JavaScript (Papa Parse — recommended)

import Papa from 'papaparse';

const csv = `name,age,city
Alice,30,New York
Bob,25,London`;

const result = Papa.parse(csv, {
  header: true,         // Use first row as keys
  dynamicTyping: true,  // Auto-convert numbers and booleans
  skipEmptyLines: true
});

console.log(result.data);
// [
//   { name: 'Alice', age: 30, city: 'New York' },
//   { name: 'Bob', age: 25, city: 'London' }
// ]

Papa Parse handles all CSV edge cases (quoted fields, escaped quotes, multiple delimiter types).

JavaScript (manual, simple case)

function csvToJson(csv) {
  const lines = csv.trim().split('\n');
  const headers = lines[0].split(',');
  
  return lines.slice(1).map(line => {
    const values = line.split(',');
    return Object.fromEntries(
      headers.map((header, i) => [header.trim(), values[i]?.trim()])
    );
  });
}

// WARNING: This breaks on commas inside quoted fields
// Use Papa Parse for production code

Python

import csv
import json

# From a file:
with open('data.csv', 'r', newline='') as f:
    reader = csv.DictReader(f)
    data = list(reader)

print(json.dumps(data, indent=2))

# From a string:
import io

csv_text = """name,age,city
Alice,30,New York
Bob,25,London"""

reader = csv.DictReader(io.StringIO(csv_text))
data = list(reader)
print(json.dumps(data, indent=2))

Python’s csv.DictReader uses the first row as keys and handles all RFC 4180 edge cases.

Command line (csvkit)

# Install:
pip install csvkit

# Convert:
csvjson data.csv > data.json

# With indentation:
csvjson --indent 2 data.csv

# Filter columns:
csvjson --columns name,age data.csv

jq approach (when you already have the CSV as lines)

# Simple CSV to JSON with awk + jq:
awk -F',' 'NR==1{split($0,h,",")} NR>1{for(i=1;i<=NF;i++) printf "%s%s",h[i]"="$i,(i==NF?"\n":",")}'  data.csv | \
  jq -Rs 'split("\n")'

For complex CSV, csvkit or Python is more reliable.

Nested JSON from flat CSV

CSV is inherently flat (two dimensions: rows and columns). JSON can be nested. Some converters support dot notation in headers to create nested JSON:

name,address.street,address.city,address.zip
Alice,123 Main St,New York,10001

Converts to:

[{
  "name": "Alice",
  "address": {
    "street": "123 Main St",
    "city": "New York",
    "zip": "10001"
  }
}]

This is a convention, not a CSV standard. The CSV to JSON converter supports this dot-notation expansion.

Common conversion mistakes

Not handling the header row: Treating the header as data produces a first object like {"name": "name", "age": "age"}. Most converters use the first row as headers by default.

Ignoring quoted fields: Splitting on commas breaks when fields contain commas. Use a proper CSV parser.

Losing type information: All-string JSON may break downstream code expecting numbers. Enable type coercion if the consumer expects typed values.

Encoding issues: CSV files from Excel may be in Windows-1252 encoding. Open with encoding='windows-1252' or convert to UTF-8 first.

Related tools

• CSV to JSON — convert CSV data to JSON
• CSV Quoting Rules — how CSV handles commas and quotes
• JSON Formatter — format and validate your JSON output