facets-overview
Python code to support the Facets Overview visualization
Decision gist · record as of 2026-08-14
Yes, but with caution. The package is useful for interactive data exploration and visualization in Jupyter notebooks, has low install friction, and carries no known vulnerabilities. However, it is abandoned and unmaintained since May 2023, so compatibility with current versions of numpy, pandas, protobuf, and Jupyter is uncertain. Install only if you can tolerate potential breakage or are working in a stable, locked environment. For active projects, consider maintained alternatives.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires protobuf version 3.20.0 or later; TensorFlow is optional but needed only if analyzing TfRecord files rather than pandas DataFrames.
- Low friction installation with a pure Python wheel, though the package is abandoned as of 2023-05-24 and has not been maintained for over 1178 days.
- It depends on numpy, pandas, and protobuf (version 3.20.0 or later required as of version 1.1.0), all widely available.
License · maintenance · safety
Apache 2.0 (permissive) — Licensed under Apache 2.0, a permissive license that allows commercial and private use with minimal restrictions, making it safe to incorporate into most projects.
last release 2023-05-24 (1178 days) · last repo commit 2023-05-24 · 7,342 stars · archived
0 known vulnerabilities (OSV.dev, 2026-08-14) · 239,275 downloads/mo, #8,923 on PyPI
Alternatives
Verify before relying
from facets_overview.generic_feature_statistics_generator import GenericFeatureStatisticsGenerator
import pandas as pd
df = pd.DataFrame({'num': [1, 2, 3, 4], 'str': ['a', 'a', 'b', None]})
proto = GenericFeatureStatisticsGenerator().ProtoFromDataFrames([{'name': 'test', 'table': df}])- Whether the package works with modern versions of numpy, pandas, and protobuf despite being unmaintained since May 2023.
- Compatibility with current Jupyter notebook environments and whether the nbextension still installs correctly.
- Whether TensorFlow dependency handling remains functional given the rapid evolution of that ecosystem.
What it is and what it does
Facets Overview is a Python library that computes and visualizes summary statistics for dataset features in an interactive Jupyter notebook interface. It accepts data as pandas DataFrames or TensorFlow Example protocol buffers from TfRecord files, then generates a protocol buffer containing statistics like min, mean, median, max, and standard deviation for numeric features, and metrics like average length, unique value counts, and mode for string features. The visualization displays these statistics in two tables—one for numeric and one for categorical features—with sortable rows, distribution charts, and optional weighted statistics if example weights are provided.
The package is designed for exploratory data analysis and data quality assessment in machine learning workflows. It highlights potentially problematic statistics (such as missing values) in red and offers multiple chart types including histograms, deciles, and cumulative distribution functions. However, the package is abandoned and has not been updated since May 2023, meaning it may face compatibility issues with newer versions of its dependencies (numpy, pandas, protobuf) or modern Jupyter environments.
Use it for
- Explore feature distributions and detect data quality issues in a pandas DataFrame before training an ML model.
- Compare summary statistics across multiple datasets side-by-side to identify distribution shifts or anomalies.
- Generate weighted statistics for datasets where examples have importance weights, toggling between weighted and unweighted views.
- Analyze TensorFlow Example records from TfRecord files to understand feature statistics at scale in a TensorFlow pipeline.
- Create interactive reports of dataset characteristics in Jupyter notebooks for data documentation and team review.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, but with caution.
The package is useful for interactive data exploration and visualization in Jupyter notebooks, has low install friction, and carries no known vulnerabilities. However, it is abandoned and unmaintained since May 2023, so compatibility with current versions of numpy, pandas, protobuf, and Jupyter is uncertain. Install only if you can tolerate potential breakage or are working in a stable, locked environment. For active projects, consider maintained alternatives.
Install
facets-overview on PyPI
Before you install
Low friction installation with a pure Python wheel, though the package is abandoned as of 2023-05-24 and has not been maintained for over 1178 days. It depends on numpy, pandas, and protobuf (version 3.20.0 or later required as of version 1.1.0), all widely available.
Requires protobuf version 3.20.0 or later; TensorFlow is optional but needed only if analyzing TfRecord files rather than pandas DataFrames.
License in practice
Licensed under Apache 2.0, a permissive license that allows commercial and private use with minimal restrictions, making it safe to incorporate into most projects.
Quickstart
from facets_overview.generic_feature_statistics_generator import GenericFeatureStatisticsGenerator
import pandas as pd
df = pd.DataFrame({'num': [1, 2, 3, 4], 'str': ['a', 'a', 'b', None]})
proto = GenericFeatureStatisticsGenerator().ProtoFromDataFrames([{'name': 'test', 'table': df}])Verify before relying
- Whether the package works with modern versions of numpy, pandas, and protobuf despite being unmaintained since May 2023.
- Compatibility with current Jupyter notebook environments and whether the nbextension still installs correctly.
- Whether TensorFlow dependency handling remains functional given the rapid evolution of that ecosystem.
Package facts
| License | Apache 2.0 permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesnumpypandasprotobuf |
| Maintenance | Abandoned 1,178 days since the last release |
| Last repo commit | repository archived |
| First released | |
| Downloads | 239,275 / month, #8,923 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: facets_overview-1.1.1-py2.py3-none-any.whl
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