ACCA · New at Strategic Professional level · 7 questions
Name: ____________________ Date: ____________
In SQL, which clause filters groups after aggregation?
Which SQL join keeps all rows from the left table and the matching rows from the right?
In Python, which library is most commonly used for working with tables of data?
The SQL statement SELECT region, SUM(sales) FROM orders GROUP BY region returns:
A join between a customer table and an orders table on the wrong column typically results in:
In Python, a list of values such as [10, 20, 30] can be used in a loop to:
A good practice when cleaning data in code is to:
1. B, 2. C, 3. C, 4. A, 5. B, 6. B, 7. A
WHERE filters rows before grouping, and HAVING filters the groups.
Rows without a match have empty values for the right table's columns.
pandas provides data frames for loading, cleaning and summarising data.
The aggregate is calculated for each group.
The key must identify matching records.
Loops carry out repeated steps for each item.
Repeatable, documented steps allow checking and re-running.