To recap, a Series is a one-dimensional data structure, similar to a list or a column in a spreadsheet. It holds data of the same type, with each element labeled by an index.

In contrast, a DataFrame is a versatile two-dimensional structure in Pandas, similar to a table or spreadsheet, with rows and columns. It can hold data of different types, with each column functioning as a Series. Like a spreadsheet, a DataFrame includes both an index and column labels, making it ideal for handling large, structured datasets.

To create a DataFrame object, you'll need to use a dictionary in conjunction with the .DataFrame() constructor.

Note

If you want to explicitly indicate that the variable represents a DataFrame, you can include df in the variable name, as shown in this example (people_df).