Mastering Google BigQuery: Creating a Pivot Table for User Activity скачать в хорошем качестве

Mastering Google BigQuery: Creating a Pivot Table for User Activity

Learn how to effectively use Google BigQuery to loop over multiple users and display daily counts in a pivot table format. --- This video is based on the question https://stackoverflow.com/q/68304307/ asked by the user 'user3163545' ( https://stackoverflow.com/u/3163545/ ) and on the answer https://stackoverflow.com/a/68304425/ provided by the user 'Mikhail Berlyant' ( https://stackoverflow.com/u/5221944/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions. Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: BigQuery - Query for each and set elements in column Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l... The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license. If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com. --- Mastering Google BigQuery: Creating a Pivot Table for User Activity When working with data analytics, especially with platforms like Google BigQuery, there are often questions about how to manipulate and present data effectively. A common challenge is querying data for multiple users and displaying results in a clear way. In this guide, we will explore how to transform your query results into a daily activity summary for each user in a pivot table format. This method allows you to see user activity across specific days in a single glance. The Scenario Imagine you have a dataset containing timestamps of user activities. You want to: Get the number of activities for each user within a specified date range. Present this information in a structured format where each user has their activity count listed under the respective date. Here’s an example of the desired output: [[See Video to Reveal this Text or Code Snippet]] The Solution To achieve this, we will use the PIVOT function in BigQuery. The following sections will guide you through the process step-by-step. Step 1: Basic Query Structure First, you need a query that counts activities based on the user and the date. The initial query would look like this: [[See Video to Reveal this Text or Code Snippet]] Step 2: Implementing the PIVOT Function Next, you will incorporate the PIVOT function to transform the query output from rows into columns. Here’s how you do it: [[See Video to Reveal this Text or Code Snippet]] Step 3: A Simplified Version If you want to simplify the query, you can even avoid the GROUP BY clause in your original count logic. Here’s a more streamlined version: [[See Video to Reveal this Text or Code Snippet]] Conclusion Using the PIVOT function in Google BigQuery allows you to easily transform and present data for multiple users in a clear, structured manner. By following these steps, you can efficiently summarize user activity over specific dates, giving you insightful visibility into user engagement. Feel free to adapt these queries for your own datasets and reporting requirements. Happy querying!