Making the most out of Pandas

Pandas is arguably the most popular data analysis and manipulation library in the data science ecosystem. The user-friendly and intuitive Python syntax is a significant factor in the popularity of Pandas. However, it is not the only reason why Pandas is adapted by a vast majority of data scientists.

Pandas provides numerous functions and methods that expedite the data analysis and manipulation operations. In this article, we will go over 4 tricks for using these functions even more efficiently.

Let’s start with creating a data frame. We will use the Melbourne housing dataset available on Kaggle.

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