Paste your Excel data or drag Excel files here

.xls , .xlsx , .xlsm

Online Table Editor

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Table Generator

How to Quickly Convert Excel to Pandas DataFrame 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 Pandas DataFrame format with simple and efficient operation and precise reliable results.

3. Copy or download Pandas DataFrame with multiple export options supported

Generate standard Pandas DataFrame code with support for data type specifications, index settings, and data operations. Generated code can be directly executed in Python environment for data analysis and processing.

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 PandasDataFrame format and its application scenarios?

.py

Pandas is the most popular data analysis library in Python, with DataFrame being its core data structure. It provides powerful data manipulation, cleaning, and analysis capabilities, widely used in data science, machine learning, and business intelligence. An indispensable tool for Python developers and data analysts.

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