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Denodo

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22
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Pandas vs Denodo: 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 Denodo? Data virtualisation platform, allowing you to connect disparate data from any source. It is the leader in data virtualization providing data access, data governance and data delivery capabilities across the broadest range of enterprise, cloud, big data, and unstructured data sources without moving the data from their original repositories.

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

Some of the features offered by Pandas are:

  • Easy handling of missing data (represented as NaN) in floating point as well as non-floating point data
  • Size mutability: columns can be inserted and deleted from DataFrame and higher dimensional objects
  • Automatic and explicit data alignment: objects can be explicitly aligned to a set of labels, or the user can simply ignore the labels and let Series, DataFrame, etc. automatically align the data for you in computations

On the other hand, Denodo provides the following key features:

  • Data virtualization
  • Data query
  • Data views

Pandas is an open source tool with 21.2K GitHub stars and 8.38K GitHub forks. Here's a link to Pandas's open source repository on GitHub.

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Pros of Denodo
Pros of Pandas
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      Easy data frame management
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    What is Denodo?

    It is the leader in data virtualization providing data access, data governance and data delivery capabilities across the broadest range of enterprise, cloud, big data, and unstructured data sources without moving the data from their original repositories.

    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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