Introduction of data Analysis Framework Ibis in Python

According to the data analysis framework Ibis in Python, I believe that many inexperienced people are at a loss about this. Therefore, this paper summarizes the causes and solutions of the problem. Through this article, I hope you can solve this problem.

Preface

Ibis is a new Python data analysis framework that aims to enable data scientists and data engineers to deal with large data as efficiently as small and medium-sized data. To achieve this goal, we will enable Python as the first-level language of Apache Hadoop without compromising functionality, usability, or performance. Over the past decade, a lot of time has been spent improving the usability of the single-node Python experience (as well as projects such as pandas). Currently, we are working to achieve:

Workflow for 100% Python end-to-end users

Give local hardware speed (Native hardware speeds for a broad set of use cases) to a wide range of use cases

Fully fidelity data analysis without extractions and sampling.

Big data scalability

Integration with existing Python data ecosystems (pandas, scikit-learn, NumPy, etc.)

After reading the above, have you mastered the methods introduced by Ibis, the data analysis framework in Python? If you want to learn more skills or want to know more about it, you are welcome to follow the industry information channel, thank you for reading!