We can select/filter specific rows based on criteria (using the same Titanic data frame):

print(df[df.age < 5])  

This means that we look into the data frame and select the rows where the age of the person is below five years old. (Again, this is creating a new data frame that can be manipulated as needed.)

If you think about this, you can apply almost any filter to a data frame. Then you can do things like select part of one data frame and combine/join with parts of another data frame. Very quickly, you end up with SQL-like manipulations that can be performed on database tables. With that point of view, you are open to a much wider spectrum of data manipulation than would appear in the base data frame.