Reverse Dependencies of modin

The following projects have a declared dependency on modin:

• anai-opensource — Automated ML
• atom-ml — A Python package for fast exploration of machine learning pipelines
• ausdex — A Python package for adjusting Australian dollars for inflation
• awswrangler — Pandas on AWS.
• connector-db-tools — connector database
• connectorx — Load data from databases to dataframes, the fastest way.
• data-describe — A Pythonic EDA Accelerator for Data Science
• datasci-stdlib-tools — Utility functions for commonly used data science packages (numpy, pandas, etc) and generic python utility functions
• dfsql — SQL interface to Pandas
• discontinuitypy — A python package for identifying and analyzing discontinuities for time series data.
• easierai-trainer-library — This library contains AI code for training purposes.
• foxcross — AsyncIO serving for data science models
• fuzzydata — Fuzzy Data Benchmark
• meerschaum — Sync Time-Series Pipes with Meerschaum
• merdb — Datastore supporting merql
• my-happy-flow — From data to information. Peformance first with easy use.
• nums — A numerical computing library for Python that scales.
• omacase — a tool to analyze optical mapping data, with _de novo_ repeat motif detection and analysis capabilities
• pacssim — Developed in PACS Lab as a performance simulator for serverless computing platforms.
• pandas2tensorboard — Pandas DataFrames converted to TensorBoard Format
• pandasai — Chat with your database (SQL, CSV, pandas, polars, mongodb, noSQL, etc). PandasAI makes data analysis conversational using LLMs (GPT 3.5 / 4, Anthropic, VertexAI) and RAG.
• pandera — A light-weight and flexible data validation and testing tool for statistical data objects.
• pyemits — python package for easy manipulation on time series data for quick insight
• scomix — Python package for analysis of data from single-cell data-science.
• serotiny — A framework of tools to structure, configure and drive deep learning projects
• slide — A collection of utility functions to unify pandas-like dataframes behaviors
• sql-profiling — Automatically profile table by name, source database type, and DSN.
• Super-ETL — no summary
• swifter — A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner
• taipy-core — A Python library to build powerful and customized data-driven back-end applications.
• whyqd — data wrangling simplicity, complete audit transparency, and at speed