SQL Challenge: Weekly Orders Report

For each week, find the total number of orders. Include only the orders that are from the first quarter of 2023. The output should contain 'week' and 'quantity'.

Let's dive into an easy-level problem from Amazon that’s perfect for honing your time-based data manipulation skills. This question will walk you through extracting and summarizing order data from a specific period—an essential technique in many SQL interviews.

Approach Hints:?

1. Use EXTRACT function: This is key for extracting specific parts of a date, like the quarter and year. In this case, we are filtering to include only orders placed in the first quarter (EXTRACT(QUARTER FROM week::date) = 1) and in the year 2023 (EXTRACT(YEAR FROM week::date) = 2023).?
2. Truncating the date: Use DATE_TRUNC('week', week::date) to round down the dates to the start of the week. This ensures that all days within a week are grouped together.?
3. Aggregating data: Once you have the filtered data, use SUM(quantity) to aggregate the total quantity of orders for each week.?
4. Organize your results: Remember to group your data by the week (GROUP BY week_start) and order it chronologically (ORDER BY week_start) to make the output easier to understand.

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??? More Education Resources

1. Simplifying Data Preprocessing with ColumnTransformer in Python: A Step-by-Step Guide Learn how to streamline your data preprocessing pipeline using the powerful ColumnTransformer in Python. This article covers a step-by-step approach to simplifying feature transformations across multiple columns.
2. The Power of Pipelines Discover the advantages of using pipelines in machine learning. This guide explores how pipelines can help automate your workflow and ensure that all preprocessing steps are applied consistently during model training and testing.

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