Data Explorer

The Data Explorer provides a spreadsheet-like interface for structured JSON arrays. It is the fastest way to browse large datasets, apply filters, sort columns, and inspect individual records.

✨ Key Features

• Table View: Renders JSON arrays as sortable, paginated tables with column headers derived from object keys.
• Column Inspector: Click any column header to see type distribution, unique values, null counts, and sample values.
• Search: Full-text search across all visible rows.
• Filtering: Apply conditions per column (equals, contains, starts with, ends with, regex, gt/lt/gte/lte, is null, not null).
• Sorting: Click column headers to sort ascending/descending.
• Pagination: Browse through thousands of records without performance issues.
• Row Detail Modal: Click a row to inspect its full JSON representation.
• Export: Download filtered results as JSON or CSV.

🔍 Column Types

The Data Explorer automatically detects and badges each column's predominant data type:

Badge	Type	Example
#	Number	42, 3.14
Abc	String	"hello"
T/F	Boolean	true, false
{ }	Object	{"nested": ...}
[ ]	Array	[1, 2, 3]
∅	Null	null
📅	Date	"2025-01-15"

⚙️ Filter Operators

Operator	Works On	Description
equals	All	Exact value match
contains	String	Substring search
starts_with	String	Prefix match
ends_with	String	Suffix match
regex	String	Regular expression match
gt	Number	Greater than
lt	Number	Less than
gte	Number	Greater than or equal to
lte	Number	Less than or equal to
is_null	All	Field is null or undefined
not_null	All	Field is not null or undefined

🛠️ How to Use

1. Navigate to the Home page.
2. Upload a JSON array (or CSV/NDJSON file).
3. Switch to the Explore & Filter section in the workspace carousel.
4. Browse data in the table, click column headers to sort.
5. Use the filter panel to narrow results.
6. Export filtered results with the download button.

💡 Tips

• Large datasets: The explorer uses virtualized rendering and pagination — it handles files with 100,000+ records smoothly.
• Nested JSON: If your data has nested objects, use the Column Inspector to explore nested keys. For deeply nested JSON, use the JSON View tree instead.
• Combined workflow: Filter your data here, then switch to the Tools panel to run the comparator or transform builder on the filtered subset.

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🚀 Try it now

Upload a JSON array in the Editor and navigate to Explore & Filter to see your data in tabular form.