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AWS Data Wrangler vs Pandas

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AWS Data Wrangler
5
25
+ 1
0
Pandas
1.7K
1.2K
+ 1
22
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Pandas vs AWS Data Wrangler: What are the differences?

What is Pandas? High-performance, easy-to-use data structures and data analysis tools for the Python programming language. Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more.

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).

Pandas and AWS Data Wrangler belong to "Data Science Tools" category of the tech stack.

Pandas and AWS Data Wrangler are both open source tools. It seems that Pandas with 22.8K GitHub stars and 9.1K forks on GitHub has more adoption than AWS Data Wrangler with 378 GitHub stars and 35 GitHub forks.

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Pros of AWS Data Wrangler
Pros of Pandas
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    • 21
      Easy data frame management
    • 1
      Extensive file format compatibility

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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 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.

    Need advice about which tool to choose?Ask the StackShare community!

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    What companies use AWS Data Wrangler?
    What companies use Pandas?
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    What tools integrate with AWS Data Wrangler?
    What tools integrate with Pandas?

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    What are some alternatives to AWS Data Wrangler and Pandas?
    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.
    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.
    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.
    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.
    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

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