fg-data-profiling
One line of code exploratory data analysis and data quality reports for Pandas and Spark.
Generate comprehensive HTML and JSON exploratory data analysis reports with a single function call.
fg-data-profiling generates extended data quality and exploratory reports for Pandas and Spark DataFrames with one line of code. It suits data scientists and analysts who need to automate data auditing, missing value detection, and visual correlations.
What it is
The package automatically infers data types, detects data quality issues and warnings, and runs univariate and multivariate analyses including time-series statistics and text metrics. You can export these reports directly to HTML files, interactive Jupyter widgets, or JSON for automated pipeline integration.
Who it's for
Suits data professionals working in Python or Spark environments who want to bypass manual EDA plotting. It is not designed for non-technical users who require a graphical database user interface without writing code.
Key features
Type Inference
Automatic detection of categorical, numerical, date, and other column data types.
Data Quality Warnings
Summarizes missing data, inaccuracies, skewness, and constant values automatically.
Time-Series Analysis
Provides auto-correlation, seasonality insights, along with ACF and PACF plots.
Dataset Comparison
Generates a fast and complete comparison report between two different dataset versions.
Up and running in 3 steps
Our honest verdict
What's great
- Generates extensive multi-section reports from a single line of Python code.
- Supports both Pandas DataFrames and Spark for scaling up analysis.
- Exports clean HTML reports that can be easily shared with stakeholders.
- Includes specialized text, image, and time-series profiling metrics.
Where it falls short
- Renamed from ydata-profiling, requiring codebase import updates and uninstallation.
- Large datasets require explicit configuration tuning and memory preparation.
- Running heavy profiling operations locally can consume significant CPU and RAM.
Pricing & license
Free under its MIT license, with the only cost being the compute resources required to run the Python environment and process your datasets.
Open remote AI-training roles
880 open remote AI-training roles, updated November 15, 2026; most pay $20–$175 an hour. Zekai lists them free; the application goes to the employer’s platform.
Alternatives
Use it, or have us set it up
FAQ
How do I migrate from the old package name?
Uninstall ydata-profiling, install fg-data-profiling, and update your code imports from ydata_profiling to data_profiling.
Can I export the report to formats other than HTML?
Yes, you can export reports to JSON format or render them directly as interactive widgets inside Jupyter Notebooks.
