In addition to querying and referencing raw column data with SQL, you can also use expressions to write more complex logic on column values in a query. These expressions can use mathematical and string functions along with basic arithmetic to transform values when the query is executed, as shown in this physics example.
SELECT particle_speed / 2.0 AS half_particle_speed FROM physics_data WHERE ABS(particle_position) * 10.0 > 500;
Each database has its own supported set of mathematical, string, and date functions that can be used in a query, which you can find in their own respective docs.
The use of expressions can save time and extra post-processing of the result data, but can also make
the query harder to read, so we recommend that when expressions are used in the
SELECT part of the
query, that they are also given a descriptive alias using the
SELECT col_expression AS expr_description, … FROM mytable;
In addition to expressions, regular columns and even tables can also have aliases to make them easier to reference in the output and as a part of simplifying more complex queries.
SELECT column AS better_column_name, … FROM a_long_widgets_table_name AS mywidgets INNER JOIN widget_sales ON mywidgets.id = widget_sales.widget_id;
You are going to have to use expressions to transform the BoxOffice data into something easier to understand for the tasks below.