Reverse Dependencies of pandas-profiling

The following projects have a declared dependency on pandas-profiling:

• AI-Starter — Python library which is extensively used for all AI projects
• ai2xl — ai2xl is a free Python library that allows using Excel for ML data preparation, zero dependency ML model deployment, model debugging, model explainability and collaboration.
• ai2xlcore — ai2xl is a free Python library that allows using Excel for ML data preparation, zero dependency ML model deployment, model debugging, model explainability and collaboration.
• Analyze — Analyze is a python library that provides comprehensive statistical analysis of a dataframe in 5 lines of code. It creates significant insight for data scientists, analysts and machine learning engineers, enabling quick understanding of a dataset.
• animal-classification — classification of animals using machine learning models
• AutoBrewML — With AutoBrewML Framework the time it takes to get production-ready ML models with great ease and efficiency highly accelerates.
• automlkiller — Auto machine learning, deep learning library in Python.
• autotonne — Auto machine learning, deep learning library in Python.
• awesome-panel-extensions — A package of awesome Panel extensions. Provided by awesome-panel.org
• csvapi — An instant JSON API for your CSV
• data-quality-validator — A package for validating data quality
• data-science-toolbox — Various code to aid in data science projects for tasks involving data cleaning, ETL, EDA, NLP, viz, feature engineering, feature selection, model validation, etc.
• datalab — Google Cloud Datalab
• Ddnet — This is a test. This project is not very useful!!!
• deep-xf — DEEPXF - An open-source, low-code explainable forecasting and nowcasting library with state-of-the-art deep neural networks and Dynamic Factor Model. Now available with additional addons like Denoising TS signals with ensembling of filters, TS signal similarity test with Siamese Neural Networks
• digen — DIGEN: Diverse Generative ML Benchmark
• doyle — doyle description
• dproc — A convenient data flow to preprocess data using metadata.
• dtaledesktop — Build a data visualization dashboard with simple snippets of python code
• dummyML — Automated data analysis pipelines on tabular data for data analyst
• DXC-Industrialized-AI-Starter — Python library which is extensively used for all AI projects
• DXC-RL — Python library which is extensively used for all AI projects
• edgaro — Explainable imbalanceD learninG compARatOr
• end2endML — Automated data analysis pipelines on tabular data for data analyst
• EtaML — An automated machine learning platform with a focus on explainability
• gui-pandas-ai — GUIPandasAI - A Simple GUI-based APP for making DataFrames Coversational along with key data analysis utilities!!! - Bringing Generative AI capabilities into Pandas as Web Interface
• house-prices — no summary
• howiml — A top-level machine learning framework
• inspec-ai — Library containing all the prototypes that were developped by the Moov AI product team.
• intelligenzaartificiale — Intelligenza Artificiale la libreria python italiana dedicata all'I.A.
• intellihub — Python Client for INTELLIHUB.
• kedro-pandas-profiling — Kedro-Pandas-Profiling is a small Kedro plugin for profiling dataframes
• linmo — Package for Lineage Motif Analysis. Extracts statistically over- or under- represented cell fate patterns within a set of lineage trees.
• machnamh — An ipywidgets based package for detecting bias in ML data and Models
• machnamh-unmakingyou — An ipywidgets based package for detecting bias in ML data and Models
• met-ml-project — MADE MLOps homework 1
• MeUtils — description
• ml-express — A Python library for day to day data analysis and machine learning.
• Mlassist — Helping Package for creating Machine Learning models
• nessiedemo — Project Nessie Demos Helper
• nlprep — Download and pre-processing data for nlp tasks
• odd-ml — SDK for working with pipeline's metadata from notebooks
• opoca — Opoca library aims to drastically speed up producing proof of concepts (PoC) for machine learning projects.
• palma — no summary
• pandas-profiling-cli — no summary
• pandaslearn — `pandaslearn` is a small wrapper on top of `scikit-learn` to automate common modeling tasks.
• pipelinex — PipelineX: Python package to build ML pipelines for experimentation with Kedro, MLflow, and more
• pipelitools — Tools for data analysis
• pmlb — A Python wrapper for the Penn Machine Learning Benchmark data repository.
• polywhirl — Run pandas-profiling HTML reports for a given list of database tables.
• poniard — Streamline scikit-learn model comparison
• prenigma-automl — prenigma_automl - An open source, low-code machine learning library.
• prenigmaautoml — prenigma_automl - An open source, low-code machine learning library.
• pug-data — Add a short description here!
• pycaret-nightly — Nightly version of PyCaret - An open source, low-code machine learning library in Python.
• pycaret-ts-alpha — PyCaret - An open source, low-code machine learning library in Python.
• Qantio.Sdk.Public — The official SDK to interract with qant.io time series analysis and prediction services.
• qubitai-dltk — Python Client for DLTK.
• quickda — Simple & Easy-to-use python modules to perform Quick Exploratory Data Analysis for any structured dataset!
• scattack — scattack
• semla — Study, ExaMine, Learn and Analyze
• sho — Visualize python objects in the best way possible
• sidechannelattack — sidechannelattack
• skself — Self-supervised learning sklearn-style
• smart-data-science — Personal side project to streamline the most common tasks of data science solutions in an efficient manner. This project is based on my experience as a lead data scientist in the industry and financial services sectors, where I have gained expertise in delivering effective data-driven insights and solutions
• SoSciKit — Social Science Kit - Open Source Software for Social Science
• sql-profiling — Automatically profile table by name, source database type, and DSN.
• SSAP — tonylab
• stglance — stglance is a small collection of streamlit widgets (for machine learning) that you can include in your streamlit app.
• streamlit-pandas-profiling — Pandas Profiling component for Streamlit.
• TAILab — TAILab = T.+AI+Lab
• thoth-lab — Code for Thoth experiments in Jupyter notebooks.
• toai — To AI helper library
• twip — Tweet Impact Predictor
• validmind — ValidMind Developer Framework
• WaveyMcWaveFace — A quick way to run Google's TiDE model