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1

AWS SDK for pandas

Easy integration with Athena, Glue, Redshift, Timestream, Neptune

aws-sdk-pandas (formerly AWS Data Wrangler) bridges pandas with the AWS analytics stack so DataFrames flow seamlessly to and from cloud services. With a few lines of code, you can read from and write to Amazon S3 in Parquet/CSV/JSON/ORC, register tables in the AWS Glue Data Catalog, and query with Amazon Athena directly into pandas. The library abstracts efficient patterns like partitioning, compression, and vectorized I/O so you get performant data lake operations without hand-rolling boilerplate. ...

Downloads: 0 This Week

Last Update: 2026-04-08
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2

AWS Step Functions Data Science SDK

For building machine learning (ML) workflows and pipelines on AWS

...The best way to quickly review how the AWS Step Functions Data Science SDK works is to review the related example notebooks. These notebooks provide code and descriptions for creating and running workflows in AWS Step Functions Using the AWS Step Functions Data Science SDK. In Amazon SageMaker, example Jupyter notebooks are available in the example notebooks portion of a notebook instance. To run the AWS Step Functions Data Science SDK example notebooks locally, download the sample notebooks and open them in a working Jupyter instance.

Downloads: 0 This Week

Last Update: 2022-07-07
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3

Amazon SageMaker Examples

Jupyter notebooks that demonstrate how to build models using SageMaker

...They have the familiar Jupyter and JuypterLab interfaces that work well for single users, or small teams where users are also administrators. Advanced users also use SageMaker solely with the AWS CLI and Python scripts using boto3 and/or the SageMaker Python SDK.

Downloads: 0 This Week

Last Update: 2021-09-14
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