Learning to differentiate Pandas and Koalas

The Pandas project is a very popular data transformation library in Python that is widely used for data analytics and data science purposes. Put simply, it's the bread and butter of data science for the majority of data scientists. But there are some limitations with the Pandas project. It is not really built for working with big data and distributed datasets. Pandas code, when executed in Databricks, only runs on the driver. This creates a performance bottleneck when the data size increases.

On the other hand, when data analysts and data scientists start working with Spark, they need to be using PySpark as an alternative. Due to this challenge, the creators of Databricks came up with another project and named it Koalas. This project has been built to allow data scientists working with Pandas to become productive with Apache Spark. It is nothing but a Pandas DataFrame API built on top of Apache Spark. Therefore, it leverages very...