Dataframes
Showing 25 of 25 projects
A powerful Python library for data analysis and manipulation, providing fast, flexible data structures.
A powerful Python library for data manipulation and analysis, providing fast, flexible data structures.
An extremely fast query engine for DataFrames, written in Rust, with multi-language frontends.
A flexible and expressive API for performing statistical data validation on dataframe-like objects.
A Go library providing DataFrames, Series, and data wrangling operations for structured data manipulation.
An embeddable C++ storage engine for dense and sparse multi-dimensional arrays, dataframes, and key-value stores.
A connector that enables Apache Spark to read from and write to Apache Cassandra databases for distributed data processing.
A plotting and data visualization system for Julia, implementing the Grammar of Graphics.
A flexible and fast package for in-memory tabular data manipulation and analysis in the Julia programming language.
A Python framework for building real-time data pipelines and event-driven microservices on Apache Kafka using a Streaming DataFrame API.
A dedicated OCaml system for scientific and engineering computing, providing n-dimensional arrays, linear algebra, algorithmic differentiation, and neural networks.
A lightweight and intuitive Go library for data manipulation, statistics, and machine learning using DataFrames.
A DataFrame-based graph processing library for Apache Spark, enabling scalable graph analytics and algorithms.
TensorFlow binding for Apache Spark DataFrames, enabling TensorFlow program execution on Spark data.
Easy pipelines for pandas DataFrames.
A Python library for comparing Pandas, Polars, Spark, and Snowpark DataFrames with detailed reporting and flexible matching.
A Julia implementation of the scikit-learn API, providing a uniform interface for machine learning models from both Julia and Python ecosystems.
An engine for ML/data tracking, visualization, explainability, drift detection, and dashboards, integrated with Polyaxon.
A Julia package providing metaprogramming macros to simplify DataFrame manipulation with a more concise syntax.
Kotlin bindings and extensions for Apache Spark, enabling idiomatic Kotlin development with data classes, lambdas, and null safety.
A Python library for blazing-fast, memory-efficient genomics data operations using DataFrames.
Julia package providing easy access to 700+ standard R datasets for data analysis and statistical learning.
A Spark library for reading from and writing to Google BigQuery using DataFrames and SQL.
A high-performance, cache-oriented JSON library for D, optimized for transforming large volumes of JSON dataframes.
A CRDT-based merge library that guarantees mathematical convergence for DataFrames, JSON, ML models, and distributed agents.
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