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AWS Data Wrangler

Move pandas/spark dataframes across AWS services
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What is AWS Data Wrangler?

It is a utility belt to handle data on AWS. It aims to fill a gap between AWS Analytics Services (Glue, Athena, EMR, Redshift) and the most popular Python data libraries (Pandas, Apache Spark).
AWS Data Wrangler is a tool in the Data Science Tools category of a tech stack.
AWS Data Wrangler is an open source tool with 1.9K GitHub stars and 309 GitHub forks. Here’s a link to AWS Data Wrangler's open source repository on GitHub

Who uses AWS Data Wrangler?

AWS Data Wrangler's Features

  • Writes in Parquet and CSV file formats
  • Utility belt to handle data on AWS

AWS Data Wrangler Alternatives & Comparisons

What are some alternatives to AWS Data Wrangler?
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.
NumPy
Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
Anaconda
A free and open-source distribution of the Python and R programming languages for scientific computing, that aims to simplify package management and deployment. Package versions are managed by the package management system conda.
SciPy
Python-based ecosystem of open-source software for mathematics, science, and engineering. It contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.
PySpark
It is the collaboration of Apache Spark and Python. it is a Python API for Spark that lets you harness the simplicity of Python and the power of Apache Spark in order to tame Big Data.
See all alternatives

AWS Data Wrangler's Followers
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