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NumPy
NumPy

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Panda
Panda

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0
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NumPy vs Panda: What are the differences?

Developers describe NumPy as "Fundamental package for scientific computing with Python". 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. On the other hand, Panda is detailed as "Dedicated video encoding in the cloud". Panda is a cloud-based platform that provides video and audio encoding infrastructure. It features lightning fast encoding, and broad support for a huge number of video and audio codecs. You can upload to Panda either from your own web application using our REST API, or by utilizing our easy to use web interface.
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NumPy belongs to "Data Science Tools" category of the tech stack, while Panda can be primarily classified under "Media Transcoding".

Some of the features offered by NumPy are:

  • a powerful N-dimensional array object
  • sophisticated (broadcasting) functions
  • tools for integrating C/C++ and Fortran code

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

  • Unlimited encoding- When we say unlimited we mean unlimited. With your own dedicated resources, you can upload as much media as you like with no per-minute charge.
  • Deliver everywhere- Encode your videos to be viewable in any browser, with any player, on any device.
  • High definition- From the cellphone to the big screen, your video will always look gorgeous with 1080p HD video.

NumPy is an open source tool with 11.1K GitHub stars and 3.67K GitHub forks. Here's a link to NumPy's open source repository on GitHub.

- No public GitHub repository available -

What is 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.

What is Panda?

Panda is a cloud-based platform that provides video and audio encoding infrastructure. It features lightning fast encoding, and broad support for a huge number of video and audio codecs. You can upload to Panda either from your own web application using our REST API, or by utilizing our easy to use web interface.<br>
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        What are some alternatives to NumPy and Panda?
        MATLAB
        Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java.
        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.
        R
        R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible.
        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.
        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.
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        Decisions about NumPy and Panda
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        How developers use NumPy and Panda
        Avatar of Vital Labs, Inc.
        Vital Labs, Inc. uses NumPyNumPy

        We utilize NumPy, SciPy, Pandas, and iPython Notebooks to power our analysis and analytics tools.

        Avatar of Eliana Abraham
        Eliana Abraham uses NumPyNumPy

        EECS 445 and All of Linear Algebra

        Nuff said

        Avatar of GadgetSteve
        GadgetSteve uses NumPyNumPy

        Fast Numeric Processing

        Avatar of Nough You
        Nough You uses NumPyNumPy

        Fast array operations.

        Avatar of BobStein
        BobStein uses NumPyNumPy

        big data analysis

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