Dataframes
Showing 22 of 22 projects
A powerful Python library for data manipulation and analysis, providing fast, flexible data structures.
A powerful Python library for data analysis and manipulation, 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.
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.
Julia package providing easy access to 700+ standard R datasets for data analysis and statistical learning.
A Python library for blazing-fast, memory-efficient genomics data operations using DataFrames.
A Spark library for reading from and writing to Google BigQuery using DataFrames and SQL.
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