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Pandas
Pandas

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18
PyXLL
PyXLL

2
8
+ 1
4
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Pandas vs PyXLL: 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 PyXLL? The Python Add-In for Microsoft Excel. Integrate Python into Microsoft Excel Use Excel as your user-facing front-end with calculations, business logic and data access powered by Python.

Works with all 3rd party and open source Python packages. No need to write any VBA!.

Pandas and PyXLL can be categorized as "Data Science" tools.

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, PyXLL provides the following key features:

  • User Defined Functions: Write Excel worksheet functions in Python - no VBA required
  • Ribbon Customization: Give your users a rich Excel native experience
  • Macros: No need for VBA, access to the full Excel Object Model in Python

Pandas is an open source tool with 20.7K GitHub stars and 8.16K GitHub forks. Here's a link to Pandas's open source repository on GitHub.

- No public GitHub repository available -

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.

What is PyXLL?

Integrate Python into Microsoft Excel. Use Excel as your user-facing front-end with calculations, business logic and data access powered by Python. Works with all 3rd party and open source Python packages. No need to write any VBA!
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      What are some alternatives to Pandas and PyXLL?
      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>
      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.
      R Language
      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.
      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.
      See all alternatives
      Decisions about Pandas and PyXLL
      Guillaume Simler
      Guillaume Simler
      at Velchanos.io | 4 upvotes 57.4K views
      Jupyter
      Jupyter
      Anaconda
      Anaconda
      Pandas
      Pandas
      IPython
      IPython

      Jupyter Anaconda Pandas IPython

      A great way to prototype your data analytic modules. The use of the package is simple and user-friendly and the migration from ipython to python is fairly simple: a lot of cleaning, but no more.

      The negative aspect comes when you want to streamline your productive system or does CI with your anaconda environment: - most tools don't accept conda environments (as smoothly as pip requirements) - the conda environments (even with miniconda) have quite an overhead

      See more
      Interest over time
      Reviews of Pandas and PyXLL
      No reviews found
      How developers use Pandas and PyXLL
      Avatar of Morris Clay
      Morris Clay uses PandasPandas

      Data wrangling, analysis and pre-processing

      Avatar of Eliana Abraham
      Eliana Abraham uses PandasPandas

      I used this a lot more than I used Jupyter.

      Avatar of GadgetSteve
      GadgetSteve uses PandasPandas

      Great data manipulation tool

      How much does Pandas cost?
      How much does PyXLL cost?
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