Data Formats Uploadable to Code Interpreter

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The Python code interpreter, combined with various libraries, can handle a wide range of file formats. Here are some of the most common ones:

Text Files: Plain text (.txt), comma-separated values (.csv), tab-separated values (.tsv), and other delimited text files.

Excel Files: Excel Workbooks (.xls, .xlsx) can be read using libraries like pandas and openpyxl.

JSON Files: JavaScript Object Notation (.json) is a common data interchange format.

XML and HTML Files: These can be parsed using libraries like BeautifulSoup and lxml.

Binary Files: Various binary formats can be read depending on the specific format and the libraries available. Examples include pickle (.pkl) files in Python.

Image Files: Formats like JPEG, PNG, and TIFF can be read using libraries like PIL/Pillow and OpenCV.

Audio Files: Formats like WAV and MP3 can be processed using libraries like librosa.

Video Files: Formats like MP4 and AVI can be read using libraries like OpenCV.

Database Files: SQLite (.sqlite, .db), MySQL, and other database formats can be accessed using libraries like sqlite3 and SQLAlchemy.

Data Files: Specialized data formats like HDF5 (.h5, .hdf5) and NetCDF can be read with libraries like h5py and netCDF4.

Word Documents: Libraries like python-docx allow you to read and write to MS Word documents.

PDF Files: Libraries like PyPDF2 and PDFMiner allow you to read and extract text from PDF files.

ZIP Files: The zipfile library allows you to work with .zip files.

Note that the ability to handle these file formats doesn't mean Python can understand the data contained within them out of the box. Specialized libraries or custom code may be needed to interpret the data in a meaningful way.