Panda vs Pandas: What are the differences?
Developers describe Panda 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.
. On the other hand, Pandas is detailed as "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.
Panda belongs to "Media Transcoding" category of the tech stack, while Pandas can be primarily classified under "Data Science Tools".
Some of the features offered by Panda are:
- 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.
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 20.2K GitHub stars and 8K GitHub forks. Here's a link to Pandas's open source repository on GitHub.