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This video demonstrates the use of list comprehension to find all numeric columns in a stock exchange index data frame. By using the df.dtypes attribute, it is identified that the first two columns are not numeric while the rest are. The data types include object (commonly strings), int (whole numbers), and float (decimal numbers). By understanding attributes and methods in pandas, it becomes easier to differentiate between data types and identify numeric columns.