CSV to JSON Converter
This tool converts CSV (Comma-Separated Values) data into JSON, turning flat, row-based text into structured objects that are easier to work with in modern applications, APIs, and scripts. Each row in the CSV becomes a JSON object, with columns mapped to named properties.
CSV is simple and widely supported, but it lacks structure and data types. JSON, on the other hand, is explicit and expressive. This converter helps bridge that gap by inferring types, normalizing values, and producing clean, predictable JSON output.
How the Conversion Works
The conversion process begins by splitting the CSV input into rows and columns using the specified delimiter. If a header row is present, its values are used as property names for the JSON objects.
Each subsequent row is converted into an object. Cell values can be trimmed, interpreted as numbers or booleans, or left as strings depending on your selected options. The final result is emitted as either formatted (pretty) or compact (minified) JSON.
Inputs and Options Explained
The following options control how CSV text is interpreted and how the resulting JSON is generated.
- CSV delimiter — Character used to separate columns, such as a comma or semicolon.
- JSON format — Choose between Pretty (multi-line, indented) and Minified (single-line) output.
- Indent size — Controls indentation depth when Pretty formatting is enabled.
- Header included — Uses the first row as object keys instead of treating it as data.
- Trim values — Removes leading and trailing whitespace from each cell.
- Auto type inference — Attempts to convert numeric and boolean-looking values into proper JSON types.
- Use null for empty values — Outputs
nullinstead of empty strings for missing data.
Examples and Edge Cases
If your CSV has uneven rows or missing columns, the converter will still generate valid JSON, but some properties may be missing or set to empty values. Enabling the null option can make these cases explicit.
Auto type inference works best with clean data. Mixed or ambiguous values (for example, IDs with leading zeros) may be kept as strings to avoid unintended data loss.
Who Should Use This Tool
This tool is helpful whenever CSV data needs to be consumed by software systems that expect structured input.
- Developers importing CSV data into applications or APIs
- Data analysts preparing exports for further processing
- QA teams converting test data into JSON fixtures
- Non-technical users moving spreadsheet data into tools
Related Concepts
Understanding the nature of CSV helps explain why certain conversion options exist.
- Flat vs structured data — CSV represents rows and columns, while JSON represents objects and arrays.
- Type inference — Automatically detecting numbers and booleans from text input.
- Data normalization — Cleaning and standardizing values during conversion.
If you need to convert data in the opposite direction, the JSON to CSV Converter allows you to export structured JSON back into spreadsheet- friendly form. For cleaning or inspecting JSON output further, the JSON Formatter can help improve readability or validate structure.