Data Analysis with Polars in Python

Who Should Take This Course. Aspiring Data Analysts seeking to learn data discovery practices Beginner Data Engineers looking to improve data manipulation skillsData Engineers looking to utilize polars in their data pipelinesPandas users looking to make the switch to PolarsWhy Learn PolarsOver the last decade Python has become more utilized in Data Pipelines. However, most pipelines faced performance issues when processing large datasets in Python.

This limitation hindered Python's ability to manage "Big Data". But in recent years, Polars unlocked the door to processing large datasets with its high performance data structures. It uses parallel processing to quickly read data into DataFrames and Series.

And its performance doesn't stop there. Not only can Polars read and write data quickly, it can also manipulate vast amounts data faster than Pandas. After Finishing the Course, you'll be able to: Read CSV files into Polars DataFramesKnow how to push data directly from Polars into a databaseExport DataFrames to ExcelAggregate complex datasetsJoin DataFrames togetherUtilize Polars' superior processing speedFAQsQ: Is the switch from Pandas difficult.

A: No. The basic concepts are the same. There are definitely differences between the two libraries, but functionality between the two are very similar.