Paste your Excel data or drag Excel files here

.xls , .xlsx , .xlsm

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How to Quickly Convert Excel to JSONLines Format Online Format?

1. Upload, paste, or extract Excel from web pages with multiple input methods supported

Upload Excel files (supports .xlsx, .xls formats) or copy table data directly from Excel and paste. The tool supports multi-worksheet processing, complex format recognition, and fast parsing of large files, automatically handling merged cells and data types.

2. Modify Excel using our professional online table editor

Edit data using our professional online table editor. Supports deleting empty row data, removing duplicate rows, transposing data, sorting by rows, regex find & replace, and real-time preview. All changes will automatically convert to JSONLines Format format with simple and efficient operation and precise reliable results.

3. Copy or download JSONLines Format with multiple export options supported

Generate standard JSONLines format with each line outputting a complete JSON object. Suitable for streaming processing, batch import, and big data analysis scenarios, supporting data validation and format optimization.

Note: Our online conversion tool uses advanced data processing technology, runs completely in the browser, ensures data security and privacy, and does not store any user data.

What is Excel format and its application scenarios?

.xls .xlsx .xlsm

Microsoft Excel is the world's most popular spreadsheet software, widely used in business analysis, financial management, data processing, and report creation. Its powerful data processing capabilities, rich function library, and flexible visualization features make it the standard tool for office automation and data analysis, with extensive applications across almost all industries and fields.

What is JSONLines format and its application scenarios?

.jsonl .json .jsonline

JSON Lines (also known as NDJSON) is an important format for big data processing and streaming data transmission, with each line containing an independent JSON object. Widely used in log analysis, data stream processing, machine learning, and distributed systems. Supports incremental processing and parallel computing, making it the ideal choice for handling large-scale structured data.

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