Astronomia
AWS Data Wrangler
| Astronomia | AWS Data Wrangler | |
|---|---|---|
| 3 | 9 | |
| 11 | 3,811 | |
| - | 0.8% | |
| 3.5 | 9.4 | |
| 11 months ago | 8 days ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Astronomia
AWS Data Wrangler
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Read files from s3 using Pandas/s3fs or AWS Data Wrangler?
I had no problem with awswrangler (https://github.com/aws/aws-sdk-pandas) and it supports reading and writing partitions which was really helpful and a few other optimizations that made it a great tool
- I agree that Arrow Tables are great, but we decided to keep the library focused on the Pandas interface. [wont implement]
- Automate some wrangling and data visualization in Python
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Redshift API vs. other ways to connect?
awslabs has developed their own package for this and given it's for their product, seem likely to maintain it. https://github.com/awslabs/aws-data-wrangler
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Parquet files
AWS data wrangler works well. it's a wrapper on pandas: https://github.com/awslabs/aws-data-wrangler
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Reading s3 file data with Python lambda function
you'll find pre-made zips here: https://github.com/awslabs/aws-data-wrangler/releases
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A guide to load (almost) anything into a DataFrame
Don't forget about https://aws-data-wrangler.readthedocs.io/
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Go+: Go designed for data science
Yep, agreed. Go is a great language for AWS Lambda type workflows.
Python isn't as great (Python Lambda Layers built on Macs don't always work). AWS Data Wrangler (https://github.com/awslabs/aws-data-wrangler) provides pre-built layers, which is a work around, but something that's as portable as Go would be the best solution.
- Best way to install pandas and bumpy to AWS Lanbda
What are some alternatives?
sqlglot - Python SQL Parser and Transpiler
PyAthena - PyAthena is a Python DB API 2.0 (PEP 249) client for Amazon Athena.
mycli - A Terminal Client for MySQL with AutoCompletion and Syntax Highlighting.
Optimus - :truck: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark
PyMySQL - MySQL client library for Python
ga-extractor - Tool for extracting Google Analytics data suitable for migrating to other platforms/databases
dev-setup - macOS development environment setup: Easy-to-understand instructions with automated setup scripts for developer tools like Vim, Sublime Text, Bash, iTerm, Python data analysis, Spark, Hadoop MapReduce, AWS, Heroku, JavaScript web development, Android development, common data stores, and dev-based OS X defaults.
python-mysql-replication - Pure Python Implementation of MySQL replication protocol build on top of PyMYSQL
Redash - Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.
gonum - Gonum is a set of numeric libraries for the Go programming language. It contains libraries for matrices, statistics, optimization, and more
zef - Toolkit for graph-relational data across space and time