Hello and welcome! In today's lesson, we will focus on creating a new feature called volume in the diamonds dataset using Pandas. Feature engineering is a crucial skill for data scientists because it helps extract additional information and insights from the data. By the end of this lesson, you will be able to create a new feature by multiplying multiple columns together and understand why this is useful.

The diamonds dataset is a popular dataset in data science, commonly used for practice and experimentation. It contains data on the physical characteristics of diamonds such as carat, cut, color, clarity, depth, table, and the three dimensions (x, y, z). Feature engineering involves creating new features based on the existing ones to better capture the underlying patterns in the data.

Why is feature engineering important?

• It can improve the performance of machine learning models.
• It helps in uncovering hidden relationships between variables.
• It aids in the interpretability of data analyses.

In the diamonds dataset, the x, y, and z columns represent the length, width, and depth of the diamonds, respectively. These dimensions are crucial for calculating the volume of each diamond.