nb2xls - Jupyter notebooks to Excel Spreadsheets
Convert Jupyter notebooks to Excel Spreadsheets (xlsx), through a new 'Download As' option or via nbconvert on the command line.
Respects tables such as Pandas DataFrames. Also exports image data such as matplotlib output.
Markdown is supported where possible (some elements still need work).
Input (code) cells are not included in the spreadsheet.
This allows you to share your results with non-programmers such that they can still easily play with the data.
Please note this is an ALPHA version. Some notebook features may be lost. Please send example ipynb files to me along with reports of any problems.
Try it out online through Binder:
Install via pip (recommended)
pip install nb2xls
Restart Jupyter to pick up the new 'Excel Spreadsheet (.xlsx)' option under 'Download As' in the File menu.
In Jupyter Notebook, just select the 'Excel Spreadsheet (.xlsx)' option under 'Download As' in the File menu.
To run from the command line try:
jupyter nbconvert --to xls Examples/ExcelTest.ipynb
jupyter nbconvert --to nb2xls.XLSExporter Examples/ExcelTest.ipynb
This should output ExcelTest.xlsx in the same folder as the ipynb file specified.
If you want to contribute or debug:
git clone https://github.com/ideonate/nb2xls cd nb2xls pip install -e .
To run tests, you will need to install some extra dependencies. Run:
pip install -e .[test]
nb2xls requires Python 3 and is tested against recent versions of jupyter and nbconvert. Please let me know if you find incompatibilities
Contact for Feedback
Please get in touch with any feedback or questions: firstname.lastname@example.org. It is very helpful to send example notebooks, especially if you have bug reports or feature suggestions.
This code is released under an MIT license.
0.1.6 (5 Aug 2019)
- Better layout and formatting of Pandas tables
0.1.5 (1 Aug 2019)
- Displays multiple outputs in display_data and execute_data output types
0.1.4 (26 Jul 2019)
- Better handling of mimetypes application/json and text/markdown
0.1.3 (24 Jul 2019)
- Working with Pandas/NumPy NaN values
0.1.2 (11 Jul 2019)
- Minor changes, mainly to deployment mechanism
0.1.1 (10 Jul 2019)
- Displays images over multiple rows for better scrolling
- Better markdown parsing especially for nested lists
0.0.1 (14 Jun 2019)
- Initial release