Hello! Today we're diving into Indexing and Selecting Data in pandas, a crucial part of data manipulation and analysis. Indexing helps us locate data in specific rows while selecting focuses on picking specific columns or cells.

We'll delve into how to select and index data using pandas by walking you through some hands-on examples. Let's begin!

In pandas, an index is more or less the address of your data. By default, pandas assigns integer labels to the rows, but we can set any column as the index. This effectively turns it into an identifier for the rows.

Here's a basic example using pandas DataFrame's set_index(), reset_index(), and rename() methods:

Accessing data using the index is performed with pandas method for label-based indexing and method for integer-based indexing, which we will investigate later.