pandas
AWS Data Wrangler
pandas | AWS Data Wrangler | |
---|---|---|
1 | 9 | |
33,264 | 3,804 | |
- | 0.7% | |
10.0 | 9.4 | |
about 2 years ago | 7 days ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
pandas
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Does pandas iterrows have performance issues?
This discussion on GitHub led me to believe it is caused when mixing dtypes in the dataframe, however the simple example below shows it is there even when using one dtype (float64). This takes 36 seconds on my machine:
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?
pandas-datareader - Extract data from a wide range of Internet sources into a pandas DataFrame.
PyAthena - PyAthena is a Python DB API 2.0 (PEP 249) client for Amazon Athena.
gurobipy-pandas - Convenience wrapper for building optimization models from pandas data
Optimus - :truck: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
ga-extractor - Tool for extracting Google Analytics data suitable for migrating to other platforms/databases
datasloth - Natural language Pandas queries and data generation powered by GPT-3
python-mysql-replication - Pure Python Implementation of MySQL replication protocol build on top of PyMYSQL
pandas-chat - pandas-ai is a python library that uses ChatGPT prompts to analyze and process pandas data in a conversational way.
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
Redash - Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data.