Let's start with the basics. What exactly is a DataFrame?

To recap, a pandas DataFrame is a two-dimensional, size-mutable, tabular data structure with labeled rows and columns. It is similar to a spreadsheet, an SQL table, or the data.frame in R. A DataFrame consists of a collection of Series, each of which is a one-dimensional labeled array.

You can think of a DataFrame as a group of Series objects that share an index (the column names). For example:

The code above produces a pandas DataFrame with exactly three columns and three rows. Note that the first number for every row corresponds to the index. What if we need to access a cell in a specific position?

In pandas, loc() and iloc() are two methods to access rows and columns of a DataFrame. They are both attributes of the DataFrame object and allow you to access and manipulate the data in various ways.

The main difference between loc and iloc is that loc uses label-based indexing, while iloc uses integer-based indexing.

There are many other ways to create a DataFrame, such as from a list of dictionaries, from a NumPy array, or by loading data from a file.

We have already spent so many words on this. Let's practice these concepts!