JSON to CSV Converter
This tool converts JSON data into CSV (Comma-Separated Values), making structured JSON easier to view, analyze, and import into spreadsheets, databases, or reporting tools. It transforms object-based data into rows and columns while preserving the original values.
CSV is widely supported but inherently flat, while JSON can contain deeply nested objects and arrays. This converter bridges that gap by flattening or serializing complex structures in a predictable and configurable way.
How the Conversion Works
The conversion starts by parsing your input JSON into a valid data structure. The tool expects either an array of objects or a single object that can be interpreted as tabular data. If the input is not valid JSON, no CSV output is produced.
Each object becomes a row in the CSV output. Object keys are mapped to column headers, and values are written into their corresponding cells. Nested objects can be flattened using dot-notation, while arrays can either be joined using a separator or preserved as JSON strings, depending on your settings.
Inputs and Options Explained
The options below control how JSON structures are translated into a flat CSV representation. They do not modify the original data values, only how they are expressed in the output.
- CSV delimiter — Defines the character used to separate columns (for example, comma or semicolon).
- Include header row — Adds a first row with column names derived from JSON object keys.
- Flatten nested objects — Converts nested objects into dot-separated column names such as
address.city. - Use null for empty values — Outputs
nullinstead of empty cells when a value is missing. - Quote all fields — Wraps every value in double quotes for maximum CSV compatibility.
- Arrays as JSON — Preserves arrays as JSON strings instead of expanding or joining them.
- Array separator — Character used to join array values when arrays are not kept as JSON.
Examples and Edge Cases
If your JSON contains objects with different sets of keys, the CSV output will include columns for all discovered keys. Rows that do not contain a particular field will leave that cell empty or use null, depending on your preference.
Arrays of objects work best when each item shares a consistent structure. Deeply nested or irregular JSON may still be converted, but the resulting CSV can become wide and harder to interpret due to the flat nature of the format.
Who Should Use This Tool
This converter is useful whenever JSON data needs to be reviewed, shared, or processed in tools that expect tabular input.
- Developers exporting API responses for analysis
- Data analysts working with spreadsheet tools
- QA teams validating structured test data
- Non-technical users who receive JSON from external systems
Related Concepts
Understanding the limitations of CSV helps explain why certain conversion options exist.
- Flat data models — CSV represents data in rows and columns without nesting.
- Schema consistency — CSV works best when all rows share the same structure.
- Serialization — Complex values may need to be encoded as strings to fit into a single cell.
If your input JSON is not well formatted or contains syntax errors, running it through the JSON Formatter first can make issues easier to spot. For converting tabular data back into structured form, the CSV to JSON Converter provides the reverse transformation.