在使用 aws data-wrangler 的過程中，覺得這個 package 還滿好趣的，將看到的資料加以收集
在 cmd 中使用 aws data wrangler 的注意事項
- After version 1.0.0 Wrangler absolutely relies on Boto3.Session() to manage AWS credentials and configurations.
In [10]: boto3.setup_default_session(region_name="us-west-2")- aws-data-wrangler/002 - Sessions.ipynb at main · awslabs/aws-data-wrangler
目前有用到，覺得重要的 aws-data-wrangler tutorials 文章
- aws-data-wrangler/003 - Amazon S3.ipynb at main · awslabs/aws-data-wrangler
- aws-data-wrangler/004 - Parquet Datasets.ipynb at main · awslabs/aws-data-wrangler
- aws-data-wrangler/005 - Glue Catalog.ipynb at main · awslabs/aws-data-wrangler
- aws-data-wrangler/006 - Amazon Athena.ipynb at main · awslabs/aws-data-wrangler
- aws-data-wrangler/010 - Parquet Crawler.ipynb at main · awslabs/aws-data-wrangler
- aws-data-wrangler/014 - Schema Evolution.ipynb at main · awslabs/aws-data-wrangler ** 這篇要來試試看
Reference
- awslabs/aws-data-wrangler: Pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).
- What is AWS Data Wrangler? — AWS Data Wrangler 2.13.0 documentation data wrangler 說明頁
- aws-data-wrangler/tutorials at main · awslabs/aws-data-wrangler 建議這份 tutorial 要整份看過一次
- Optimize Python ETL by extending Pandas with AWS Data Wrangler | AWS Big Data Blog