sheetframe

Interactive spreadsheet-style pandas tables for Jupyter notebooks and Google Colab. Select cells, rows, columns, or the whole table; resize rows and columns; copy a selection as plain text or an HTML table. Optional KPIs summarize the DataFrame.

Install

pip install sheetframe

The PyPI package is named sheetframe; the Python import is labframe.

Use

import pandas as pd
from labframe import lab_table

df = pd.DataFrame({"Name": ["Ada", "Lin"], "Score": [9.25, 8.5]})
lab_table(df, decimal=2, showIndex=False, include_header=True, kpi=False)

lab_table displays the table in a Jupyter or Colab output cell. It accepts a pandas DataFrame or Series. decimal=0 preserves the original numeric text. Set showIndex=True to show the index initially, include_header=False to omit column names from copied selections, and kpi=True to show the summary above the table.

Browser clipboard permissions and notebook security settings may affect copying and inline JavaScript behavior.

Publish to PyPI

The first public release is 0.1.0. From this folder on Windows, create a virtual environment and build the distributions:

py -m venv .venv
.\.venv\Scripts\python -m pip install build twine
.\.venv\Scripts\python -m build
.\.venv\Scripts\python -m twine check dist\*

Create a PyPI account and an API token. Then upload the files:

.\.venv\Scripts\python -m twine upload dist\*

When prompted, use __token__ as the username and paste the full pypi-... token as the password. After PyPI finishes processing, verify with py -m pip install sheetframe in a fresh environment. For later releases, increase the version in pyproject.toml and src/labframe/__init__.py before building again; PyPI does not permit replacing an uploaded version.