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AWS Data Wrangler

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SciPy vs AWS Data Wrangler: What are the differences?

What is SciPy? Scientific Computing Tools for Python. 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.

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

SciPy and AWS Data Wrangler can be categorized as "Data Science" tools.

SciPy and AWS Data Wrangler are both open source tools. It seems that SciPy with 6.63K GitHub stars and 3.06K forks on GitHub has more adoption than AWS Data Wrangler with 378 GitHub stars and 35 GitHub forks.

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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).

What is 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.

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Jobs that mention AWS Data Wrangler and SciPy as a desired skillset
CBRE
Philippines National Capital Region Makati City
CBRE
United States of America Texas Houston
CBRE
Philippines National Capital Region Makati City
CBRE
Philippines National Capital Region Makati City
What companies use AWS Data Wrangler?
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What tools integrate with AWS Data Wrangler?
What tools integrate with SciPy?
What are some alternatives to AWS Data Wrangler and SciPy?
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.
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.
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.
Dataform
Dataform helps you manage all data processes in your cloud data warehouse. Publish tables, write data tests and automate complex SQL workflows in a few minutes, so you can spend more time on analytics and less time managing infrastructure.
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