CSV Rows as JSON Objects

Mapping CSV Rows to JSON Objects

When converting CSV to JSON, you typically want each row to become a JSON object where the keys come from the header and the values from the respective columns. This is the most common and useful output format.

The mapping logic

Given a CSV with n columns and m data rows, the result is an array of m objects, each with n properties:

id,name,role,active
1,Alice,admin,true
2,Bob,editor,false
3,Carol,viewer,true

[
  { "id": "1", "name": "Alice", "role": "admin", "active": "true" },
  { "id": "2", "name": "Bob", "role": "editor", "active": "false" },
  { "id": "3", "name": "Carol", "role": "viewer", "active": "true" }
]

Implementation in JavaScript

function csvToJsonObjects(csv) {
  const lines = csv.trim().split("\n");
  const headers = lines[0].split(",").map(h => h.trim());
  return lines.slice(1).map(line => {
    const values = line.split(",");
    const obj = {};
    headers.forEach((key, i) => {
      obj[key] = values[i]?.trim() ?? "";
    });
    return obj;
  });
}

Objects vs arrays of arrays

There are two common JSON output formats for CSV data:

Format	Pros	Cons
Array of objects	Self-documenting, easy to query by key	Larger output, repeated key names
Array of arrays	Compact, preserves column order	Requires separate header metadata

Choose objects when the JSON will be consumed by APIs, stored in document databases, or processed by code that accesses fields by name. Choose arrays when file size matters and consumers already know the schema.

Edge cases

• Rows shorter than the header: Missing values should default to "" or null.
• Rows longer than the header: Extra values are typically discarded, but some parsers include them under generated keys.
• Completely empty rows: Skip them entirely to avoid empty objects in the output.