Time and efficiency matters

Pandas is one of the most commonly used data analysis and manipulation libraries in data science ecosystem. It offers plenty of functions and methods to perform efficient operations.

What I like most about Pandas is that there are almost always multiple ways to accomplish a given task. However, we should consider time and computational complexity when selection a method from available options.

It is not enough just to complete a given task. We should make it as efficient as possible. Thus, having a comprehensive understanding of how functions and methods work is of crucial importance.

In this article, we will do examples to compare the apply and applymap functions of pandas to vectorized operations. The apply and applymap functions come in hand for many tasks. However, as the size of data increases, time becomes an issue.

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