Pandas or Polars? Which Python library is right for you?

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At a Glance

Data scientists require DataFrame libraries for their projects that are efficient, flexible, compatible with various data formats, and easy to use. In this project, we compare the performance of two popular Pandas and Polars in Python.

In this project, we will examine the strengths and limitations of Pandas and Polars, as well as the scenarios in which they are most useful.

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The project will provide insights into the different use cases for each library and highlight their strengths and weaknesses. Ultimately, this project will help data scientists, engineers, and analysts determine which library is the best fit for their specific data visualization and analysis needs.

A Look at the Project Ahead

In this project, we will do the following content to compare Polars and Panda:

Provide an overview of the basic functions of Pandas and Polars
Demonstrate how they can be used to visualize and analyze different types of data
Compare the features and performance of Polars and Pandas when working with large datasets
Explore how they can be combined to effectively preprocess and visualize data.

If you are looking to conduct a real project in Jupyter notebook or continue to improve your skills in data science, give the IBM Skill Network Labs a try at no charge!

You can try to manage your own data in Watson Studio! With Watson Studio, you can easily collect, clean, and analyze your data to make informed decisions. Whether you’re a data scientist or a business analyst, Watson Studio provides an intuitive and collaborative environment to streamline your workflow and accelerate your projects.

What You’ll Need

This is a very simple project, beginners are welcome. We are using Python code in the Jupyter notebook in this project.

Remember that the IBM Skills Network Labs environment comes with many things pre-installed (e.g. Docker) to save you the hassle of setting everything up. Also note that this platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer or Safari.

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