gspread-dataframe
Read/write gspread worksheets using pandas DataFrames
Decision gist · record as of 2026-08-14
Yes, if you need straightforward pandas-to-Google-Sheets integration and can tolerate aging maintenance. The package is Production/Stable, has no known vulnerabilities, and handles the core use case well. However, verify compatibility with your specific gspread and pandas versions, and be aware that the last release was 793 days ago—consider this if you need active bug fixes or new features.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a worksheet object obtained from gspread client and Google Sheets API credentials configured.
- Low install friction with a pure-Python wheel distribution.
- Maintenance is aging—last release was 793 days ago, though the repository remains active with a recent commit and no archived status.
License · maintenance · safety
MIT (permissive) — MIT license permits commercial and private use with minimal restrictions; you may use, modify, and distribute the package freely provided you retain the license notice.
last release 2024-06-12 (793 days) · last repo commit 2025-03-28 · 262 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 4,031,292 downloads/mo, #2,395 on PyPI
Alternatives
Verify before relying
pip install gspread-dataframe
import pandas as pd
from gspread_dataframe import get_as_dataframe, set_with_dataframe
df = pd.DataFrame.from_records([{'a': i, 'b': i * 2} for i in range(100)])
set_with_dataframe(worksheet, df)
df2 = get_as_dataframe(worksheet)- Whether the package works reliably with current versions of gspread and pandas beyond the stated minimum requirements.
- Performance characteristics when working with large DataFrames or worksheets.
- Actual Python 2.7 support given the aging maintenance status and modern ecosystem shifts.
What it is and what it does
gspread-dataframe bridges pandas DataFrames and Google Sheets by wrapping gspread. It provides two main functions: get_as_dataframe() reads a worksheet into a DataFrame with support for pandas read_csv options like parse_dates and usecols, and set_with_dataframe() writes a DataFrame back to a worksheet. Version 4.0.0 added drop_empty_rows and drop_empty_columns parameters to automatically trim unused cells from the default Google Sheet grid.
The package is designed for workflows where you need to move data between spreadsheets and Python analysis pipelines. It depends on gspread (>=3.0.0), pandas (>=0.24.0), and six, making it a thin adapter layer. It integrates optionally with gspread-formatting for post-write cell formatting.
Use it for
- Export analysis results from a pandas pipeline directly to a shared Google Sheet for stakeholder review.
- Read data from a Google Sheet into a DataFrame for data cleaning and statistical analysis in Python.
- Automate periodic data synchronization between a Google Sheet and a local pandas workflow.
- Build a data collection tool where users input data in Google Sheets and Python processes it automatically.
- Trim empty rows and columns from a Google Sheet after writing a DataFrame using drop_empty_rows and drop_empty_columns.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need straightforward pandas-to-Google-Sheets integration and can tolerate aging maintenance.
The package is Production/Stable, has no known vulnerabilities, and handles the core use case well. However, verify compatibility with your specific gspread and pandas versions, and be aware that the last release was 793 days ago—consider this if you need active bug fixes or new features.
Install
gspread-dataframe on PyPI
Before you install
Low install friction with a pure-Python wheel distribution. Maintenance is aging—last release was 793 days ago, though the repository remains active with a recent commit and no archived status.
Requires a worksheet object obtained from gspread client and Google Sheets API credentials configured.
License in practice
MIT license permits commercial and private use with minimal restrictions; you may use, modify, and distribute the package freely provided you retain the license notice.
Quickstart
pip install gspread-dataframe
import pandas as pd
from gspread_dataframe import get_as_dataframe, set_with_dataframe
df = pd.DataFrame.from_records([{'a': i, 'b': i * 2} for i in range(100)])
set_with_dataframe(worksheet, df)
df2 = get_as_dataframe(worksheet)Verify before relying
- Whether the package works reliably with current versions of gspread and pandas beyond the stated minimum requirements.
- Performance characteristics when working with large DataFrames or worksheets.
- Actual Python 2.7 support given the aging maintenance status and modern ecosystem shifts.
Package facts
| License | MIT permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesgspreadpandassix |
| Maintenance | Aging 793 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 4,031,292 / month, #2,395 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Topic :: Office/Business :: Financial :: SpreadsheetTopic :: Software Development :: Libraries :: Python Modules |
Evidence: gspread_dataframe-4.0.0-py2.py3-none-any.whl
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See also gspread-pandas · pandas-read-xml · df2gspread · gspread-formatting · gspread-asyncio · gsheets · gspread · pandas-td · pandas_access · pyjanitor