aws / aws-sdk-pandasLinks
pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).
☆4,073Updated last week
Alternatives and similar repositories for aws-sdk-pandas
Users that are interested in aws-sdk-pandas are comparing it to the libraries listed below
Sorting:
- AWS Glue code samples☆1,522Updated this week
- AWS Glue Libraries are additions and enhancements to Spark for ETL operations.☆688Updated last year
- PyAthena is a Python DB API 2.0 (PEP 249) client for Amazon Athena.☆485Updated 2 weeks ago
- This repository provides a command line interface (CLI) utility that replicates an Amazon Managed Workflows for Apache Airflow (MWAA) env…☆797Updated last month
- Amazon Redshift Utils contains utilities, scripts and view which are useful in a Redshift environment☆2,804Updated 2 months ago
- A developer toolkit to implement Serverless best practices and increase developer velocity.☆3,177Updated this week
- Python API for Deequ☆801Updated 7 months ago
- Enterprise-grade, production-hardened, serverless data lake on AWS☆473Updated last month
- A collection of sample scripts to customize Amazon SageMaker Notebook Instances using Lifecycle Configurations☆431Updated last year
- Data quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io☆2,216Updated last week
- Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.☆3,536Updated this week
- Redshift Python Connector. It supports Python Database API Specification v2.0.☆216Updated 3 weeks ago
- Train machine learning models within a 🐳 Docker container using 🧠 Amazon SageMaker.☆519Updated last month
- A library for training and deploying machine learning models on Amazon SageMaker☆2,201Updated last week
- The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️☆3,605Updated 5 months ago
- AWS Deep Learning Containers are pre-built Docker images that make it easier to run popular deep learning frameworks and tools on AWS.☆1,113Updated last week
- Step Functions Data Science SDK for building machine learning (ML) workflows and pipelines on AWS☆292Updated 6 months ago
- Airflow Deployment on AWS ECS Fargate Using Cloudformation☆205Updated 3 years ago
- data load tool (dlt) is an open source Python library that makes data loading easy 🛠️☆4,356Updated last week
- AI and Machine Learning with Kubeflow, Amazon EKS, and SageMaker☆3,417Updated last year
- re_data - fix data issues before your users & CEO would discover them 😊☆1,571Updated last year
- The Amazon Athena Query Federation SDK allows you to customize Amazon Athena with your own data sources and code.☆592Updated this week
- Utility functions for dbt projects.☆1,640Updated this week
- Turbine: the bare metals that gets you Airflow☆379Updated 4 years ago
- Always know what to expect from your data.☆10,898Updated this week
- S3 Filesystem☆977Updated last week
- Serve machine learning models within a 🐳 Docker container using 🧠 Amazon SageMaker.☆408Updated last year
- Notebooks and examples on how to onboard and use various features of Amazon Forecast.☆526Updated 2 years ago
- Support code for building and running Amazon SageMaker compatible Docker containers based on the open source framework Scikit-learn (http…☆182Updated 2 weeks ago
- A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rew…☆2,117Updated this week