Data Analyst Portfolio Project: Restaurant Order Analysis in SQL (with Solutions) 

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Glad to hear that! Here's where you can find all our guided projects, including the baby name analysis one: mavenanalytics.io/guided-projects#projects-list And if you're just looking for the data, you can find it here: mavenanalytics.io/data-playground?search=baby%20names Happy learning!

Hi Matthew - Thanks for the note! I reran the SQL query and got 20 again, and I created a PivotTable in Excel and got 23 just like you. When I looked into the discrepancy, I found that the three additional order IDs were 740, 3292 and 4623. I looked at those orders individually, and for each order, the final item ID was NULL. This is something that SQL was ignoring and that Excel was counting as an item. As for which one is correct, I think it could go both ways. This is a data set that we created, but in reality, rows with a NULL item ID could either mean that the item ID is missing but the item was actually purchased, or that the row was created in error and the item wasn't actually purchased. I do think that the former is more likely though! You bring up a great point here that the different tools return different results based on how they handle NULL values. Thanks for catching that and I'm glad the discussion can be documented here in the comments.

Glad you're enjoying our courses! We already have several Python guided projects available on our website at mavenanalytics.io/guided-projects. I would recommend checking out the AirBnB Listing Analysis in Python -- it's a basic project and it's free!

Here's our most recent Python guided project on RU-vid: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-fwOU0lfreu8.html

In the order details table, the order id provides the unique ID for each order that was placed. For example, order_id 2 represents a single order that was placed at 11:57 that included 5 menu items.

@MsGinnieG Yep! You have a couple options at this point. You can either reload the data sets into SQL and make sure both ID columns have the same data type, or when you're joining the tables, you can use the CAST function. For example, SELECT * FROM table1 JOIN table2 ON CAST(table1.item_id AS INT) = table2.menu_item_id. Good luck!