Orchest vs Pandas: What are the differences?
Orchest: An open source tool for creating data science pipelines. It is a web-based data science tool that works on top of your filesystem allowing you to use your editor of choice. With Orchest you get to focus on visually building and iterating on your pipeline ideas. Under the hood Orchest runs a collection of containers to provide a scalable platform that can run on your laptop as well as on a large scale cloud cluster; 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.
Orchest and Pandas can be categorized as "Data Science" tools.
Some of the features offered by Orchest are:
- Visual pipeline editor
- Executable notebooks
- Open source
On the other hand, Pandas provides the following key features:
- 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
Pandas is an open source tool with 26.4K GitHub stars and 10.8K GitHub forks. Here's a link to Pandas's open source repository on GitHub.
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