facet VS ydata-profiling

Compare facet vs ydata-profiling and see what are their differences.

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facet ydata-profiling
5 43
471 12,053
- 1.5%
5.6 8.5
10 months ago 5 days ago
Jupyter Notebook Python
Apache License 2.0 MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

facet

Posts with mentions or reviews of facet. We have used some of these posts to build our list of alternatives and similar projects.

ydata-profiling

Posts with mentions or reviews of ydata-profiling. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-26.

What are some alternatives?

When comparing facet and ydata-profiling you can also consider the following projects:

transient_rotordynamic - transient dynamics of elastic rotors in journal bearings with Julia and Python

dtale - Visualizer for pandas data structures

shapash - 🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

DataProfiler - What's in your data? Extract schema, statistics and entities from datasets

wordlescraper - Combine wordle statistics metrics from various locations, data science to correlate scores with words, and a front end to display the results.

dataframe-go - DataFrames for Go: For statistics, machine-learning, and data manipulation/exploration

transformers-interpret - Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.

lux - Automatically visualize your pandas dataframe via a single print! 📊 💡

imodels - Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

get-started-with-JAX - The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning about the JAX ecosystem.

evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b

dataprep - Open-source low code data preparation library in python. Collect, clean and visualization your data in python with a few lines of code.