Stop doing this in Excel. Tableau has a cleaner, more powerful way to count only the weekdays between any two dates. And once you see how it works,you'll use it everywhere.

In this tutorial, you'll learn how to build a dynamic date range selector  using parameter actions, then strip out Saturdays and Sundays using DATEPART weekday logic wrapped in a Level of Detail expression, so you always get an accurate weekday count, no matter the range.

This is one of the most common questions I get asked, and the solution is simpler than you think.

📥 Download the workbook + data: https://nlt.kit.com/weekdays

Are you looking to take your Tableau skills to the next level? Do you want to create dashboards that offer a dynamic and interactive experience? 

Look no further! 

This comprehensive tutorial will walk you through the process of creating a Year→Quarter→Month→Day Drilldown in Tableau.

🔹 What You'll Learn:

1. How to set up 2 parameters for drilldown functionality

2. How to perform 9 simple calculations that power your dashboard

3. How to implement 8 simple dashboard actions for enhanced interactivity

4. Introduction to dynamic zone visibility

🔹 Who Should Watch:

1. Data analysts looking to expand their Tableau toolkit

2. Business intelligence professionals aiming for dynamic reporting

3. Anyone who wants to unlock the full potential of Tableau

🔹 Why This Tutorial is Unique:

1. Step-by-step guide for each component: Parameters, Calculations, and Dashboard Actions

2. Introduction to advanced Tableau functionalities like dynamic zone visibility

3. Reusable examples to cement your understanding

4. Tips and tricks for maximizing the utility of your drilldowns

Don't miss out on upgrading your Tableau skills. 

Let's dive into the world of advanced Tableau functionalities and take your dashboards to the next level! 

Welcome to this comprehensive tutorial on creating a Yearly to Monthly Calendar Drill Down using Dynamic Zone Visibility in Tableau.

📌 What You Will Learn

🔑 Key Takeaways

🔗 Additional Resources

Welcome to my guide on mastering the 3-Level Drill Down in Tableau!

In this tutorial, I show you step-by-step how to make the most of using dynamic zone visibility to create this functionality. We'll go through both scatter plot drill downs from Region → State → Postal code and then replicate that as a bar chart. 

You can easily make this a map drill down by changing the chart type. That's it!

🔍 What you'll learn in this video: 

1. The basics of drill down functionality in Tableau
2. Hands-on demonstrations, tips, and best practices
3. How to interact with the data

💡 Why is this important?

Drill down capabilities allow analysts to explore data from a broad overview down to granular details. By mastering the 3-level drill down, you can uncover hidden patterns, insights, and trends that might be overlooked in higher-level analyses. 

📌 Prerequisites: 

A basic understanding of Tableau's interface and primary functions will be helpful, but beginners will be able to follow along as well!

If you are following along, be sure to pause the video along the way as you repeat the steps.

At the global level, how has crop production changed over the last fifty years? 

In this Watch Me Viz live stream, I analyzed how the yield and land use of producing cereal has changed over the last 50 years.

I really liked the original visualization, so I rebuilt it in Tableau. I learned how to use dynamic zone visibility, layout containers, and more. Check it out.

Resources:

1. Data - https://data.world/makeovermonday/2023w24

2. Final Dashboard - https://tabsoft.co/3P3Sdl3

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Watch Me Viz is a weekly live stream where I help people become better at #Tableau, #PowerBI and data analysis. I show how I take an existing visualization, critique it, analyze the data, and build several visualizations all the while looking for a "better" visualization than the original.

If you are considering participating in Makeover Monday, you can get started by downloading data sets from the Makeover Monday website. I promise you'll become better at data analysis and data visualization by practicing every week.

Data sets - https://www.makeovermonday.co.uk/data/

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LEARN FROM ME

Join my newsletter. Sign up at andykriebel.com. 

ARE YOU INTERVIEWING FOR A NEW JOB?

Contact me for more information about how I can help you prepare for that big interview.

coaching@makeovermonday.co.uk

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CONNECT WITH ME

https://linktr.ee/andykriebel

More Watch Me Viz - https://bit.ly/WatchMeViz2023

This week we explored the cost of 20g of protein in various foods. During Watch Me Viz, I showed how to create toggles to allow the user to filter by vegan and vegetarian foods. I did this with parameter actions; if you want to learn more, watch the video below.

In the end, though, my fancy filtering with parameter actions didn't quite work out. I hadn't account for the option when the user might want to look at all foods. So I ended up using basic filtering. I overcooked the whole process, but I bet you'll learn something anyway.

I then went through the entire dashboard design process using containers, padding, shading and more. Check that out if you're interested in learning how to use layout contains.

Here's the #WatchMeViz recording, followed by the interactive viz. Enjoy and thanks for watching!

During Watch Me Viz, I covered set actions, parameter actions, highlighting, boolean calculations, table calculation, dashboard layout, and I failed at a starburst chart (I couldn't get the years to sort properly; I'll post it when I figure it out).

Enjoy! Check out the viz below the video.

There are tons of ways to create a single level drill down, but if you’re having issues creating a second drill down, this video is a guaranteed way to help you fix this problem.

Additional video - Single Level Drill Down 

NOTE: The insights you see in this post are based on an article by The Upshot from September 2018. Some of the insights and use cases demonstrated are the same and are shown in Tableau for demonstration purposes.

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When I first saw the map that The Upshot created in How Connected Is Your Community to Everywhere Else in America? I was blow away by the simplicity of the map and how easy it is to understand the relationships of people in the United States via their Facebook friendships. The first thing you need to understand is the metric "Social Connectedness Index". You can access the data I used via the same link. 

Here's the formula Facebook uses to calculate the index:

From Facebook:

Social Connectednessi,j measures the relative probability of a Facebook friendship link between a given Facebook user in location i and a user in location j. Put differently, if this measure is twice as large, a Facebook user in i is about twice as likely to be connected with a given Facebook user in j.

In each dataset, we scale the measure to have a fixed maximum value (by dividing the original measure by the maximum and multiplying by 1,000,000,000) and the lowest possible value of 1. We also round the measure to the nearest integer.

I was not able to match the color scale in The Upshot exactly, so instead I used a table calculation that ranks each County in the U.S. compared to the County selected by the user.

The data has columns for the State/County of the user and for State/County of the friend. To ensure that I was only looking at friends for the County selected, I used Parameter Actions to filter the user to the County and State selected. The rank calculation then only uses the SCI for the friends.

Now let's look through some of the use cases as described in The Upshot.

DISTANCE IS MOST IMPORTANT

STATE LINES ARE BOUNDARIES

In some counties (like the four below, friendships drop significantly outside State borders.

MIGRATION PATTERNS

People from certain areas of the country have migrated to other areas in the country over the course of many decades. We can see these patterns by looking at Chicago and Milwaukee. The southern counties were typically related to the slave trade, and the people in the south gradually migrated north after they were freed.

Migration patterns aren't limited to history. Consider counties in the Northeast. Nearly all of them have a strong relationship with coastal areas in South Carolina and Georgia and all of Florida. These are called snowbirds, people that migrate south for the winter.

PHYSICAL BOUNDARIES

Friendships in some counties are limited by geographical boundaries. For example, friendships for people living in Belmont County, Ohio don't cross the Appalachian Mountains in West Virginia.

While people in Scott County, Arkansas don't have friends on the other side of the Mississippi River.

Have some fun with the interactive version below.