Tag: Tableau tutorial

Tableau Heat Map Tutorial: 3 examples

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What is a Tableau Heat Map?

Heat map in Tableau is a data visualization type for which you need to have one or more dimensions and 1 or 2 measures. In these heat maps, Tableau is displaying a table consisting of many squares. Tableau can represent these squares in different sizes and colors. You can choose measures that will reveal data by size, color, or both.
 
Tableau heat map

How do you create a Heat map?

To create a heat map, you need to have a data set with at least in dimension and one measure. Ideally, you must have two dimensions, of which one should be a date and one or two measures. When you select your data source, follow these steps:

  1. Select your dimensions and measures when holding a CRTL button.
  2. Press Show Me button in the top-right corner and select Heat Maps to create our Tableau heat map.

What are the best practices to use heat maps?

To use a heat map in Tableau is a go-to practice when you have some measure that you can analyze by timeline or sub-categorical dimensions that divides the sum of that measure. If you have too many rows and columns in your heat map, then you can add filters to make finding insights easier.

Example 1. Determining which region has the most sales

 
We will use Superstore Sales data for this first example. Firstly, connect to our data by selecting the Orders sheet as our data source. Then we immediately go to our Tableau Sheet 1 and renaming it to what we want to find in it. In this instance, change Sheet 1 to Product Subcategory Sales by Region. As a result, we now see the modified sheet header and can go to the next steps that will create a heat map.
As you can see in the following video, we are selecting Product Subcategory, Region, and Sales. Then, we choose Heat Maps from Show Me list. As a result, we have our first heat map that can be formatted to look better. We switch column with header because instantly, Tableau put it in alphabetical order. Then, change Region header alignment to vertical.
 

Tweaking the heat map

Even though a Tableau heat map is intact, we still not have the best version of the chart in front of us. Indeed, there are a few things that we can improve here. First, increase the size of a heat map so it would look more appealing. Second, switch SUM(Sales) pill in the marks field from Size to Color and choose whatever color palette you like.

Now we can see that most sales were in Ontario, Prairie, and West regions. Also, it’s clear there were no Office Machines sales in the Nunavut region as it’s rectangle is white.
Moreover, we can use the second measure in the heat map to display both different sizes and colors for rectangles. Let’s change SUM(Sales) pill to size and drag Profit measure to colors field. As a result, we can understand which subcategories by region have the most sales (width of rectangles) and profit (color of boxes). With this addition, we can recognize negative profit cases. For example, we can see that Bookcases our store sold with negative profit in Yukon, Northwest Territories, Ontario, and Quebec.
 

Example 2. Best App Store games 2008-2019

Let’s open the 17k app store games database from Kaggle. Steps that I use to create a Tableau heat map are in this video:

Using various filters, you can determine multiple app store games that have the biggest User Rating Count. As we know that the best games get rated more, the big User Rating count can indicate the best seller games in the Apple app store. If you want to know the best Role-Playing games, filter this genre and set the minimum User Rating count such that optimal number games could appear in a worksheet. For example, after placing the minimum User Rating to 20.000, you can see a Tableau heat map consisting of probably the best Role Playing Games in App Store history. Tableau Public worksheet is shared below.

Example 3. CO2 Emissions By country in the Tableau Heat Map

This example is meant to show countries with the most significant CO2 emission and also changes in the emission numbers in the timeline. You can download the CO2 Emission data here. I am not going into further aspects of what steps I am taking to build a heat map in this case. Just watch the video below and digest it. 

Conclusion

To summarize, a Tableau heat map is an excellent alternative over traditional excel tables with numbers. In numerous circumstances, it is easier to find patterns using the size and color of cells over numbers.

  
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Tableau bar chart tutorial

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The fastest way to compare your data is creating Tableau bar chart. In this tutorial, I choose to open Superstore Sales file that I’ve mentioned in my datasets for analysis page. After opening excel file, I choose Orders sheet and drag to data source field.

Selecting measures and dimensions

After connecting with the Super Store Sales file, we see these measures and dimensions: –>

Let’s think what we want to see in our bar chart.

Profit is one of the main KPI’s in business, we are choosing that measure and dragging to rows field. Furthermore, to see what product categories and sub-categories are generating most profit, we need to drag those dimensions to the columns field.

 

tableau bar chart
tableau bar chart

tableau bar chart

Polishing the Tableau Bar Chart

The bar chart is made now, but we have to make it more beautiful and easier to read. Here are the steps that we follow to upgrade our chart:
  1.  Move Office supplies category to the left, because it has most sub-categories. Also move technology category in front of the office supplies, because technology bars are much higher. This way it will look better.tableau bar chart
  2.  Add profit numbers to bars by dragging Profit measure to label field
  3. Now we see that Telephones and Communication category label is not there. Number that would be used for a label is too big, so we decrease text size from 9 to 8.  tableau bar chart
  4. Sort sub-categories by profit (descending).
  5. Add colors to Tableau bar chart to make things further clear. Drag Profit measure to color field. I chose to use red-green diverging for this example. Also, I have marked Use Full Color Range box so that the worst sub-category will be visualized with the richest red in the range. tableau color selection

Final chart view

After finishing our bar chart we can see which categories and sub-categories makes good profit numbers. We see that “the Store” loses money by selling Bookcases and Tables. In a real-world situation, middle managers would be required to report what were the reasons for that. Additionally, as analysts, we can drill-down into subcategories and try to find those reasons in our data.

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