Tableau Scatter Plots: 6 Easy Steps to Build Scatter Plot [Tips Included]

Tableau is a powerful Data Visualization application that data analysts, scientists, statisticians, and others may use to visualize data and form unambiguous conclusions based on Data Analysis. Tableau is famous for its ability to process data fast and provide the desired Data Visualization output.

In this Tableau Scatter Plot tutorial, you will learn what Scatter Plots are and how to create them in Tableau Software.

Table Of Contents

• What is Tableau?
  • Key Features of Tableau
• What is A Tableau Scatter Plot?
• Creating Tableau Scatter Plot
  • Creating Tableau Scatter Plot: Selecting a Measure
  • Creating Tableau Scatter Plot: Dragging the Measure to the Rows Section
  • Creating Tableau Scatter Plot: Selecting Two Dimension Fields
  • Creating Tableau Scatter Plot: Customizing Your Scatter Plot 
  • Creating Tableau Scatter Plot: Increasing the Details of the Scatter Plot
  • Creating Tableau Scatter Plot: Finalizing the Scatter Plot
• Making a Dynamic Tableau Scatter Plot
• Adding Segments to your Tableau Scatter Plot
• Tips to Create Better Tableau Scatter Plots
  • Tip 1: A Formatting Trick
  • Tip 2: Maximizing Data-Ink Ratio
  • Tip 3: Adding a Segmentation Calculated Field
• Conclusion

What is Tableau?

Tableau is a strong and fastly developing Data Visualization software. It helps in the simplification of raw data into a format that is simple to understand. Tableau helps in the creation of data that can be understood by experts at all levels of a company. Even people without much technical knowledge can easily develop customized dashboards.

In Tableau, Data Analysis happens quite quickly, and visuals are created in the form of dashboards and workbooks.

Key Features of Tableau

• Usability: It is simple to use and requires no prior technical or programming experience. It has a quick response time when it comes to creating a dashboard. Tableau is available for download on mobile devices and desktops, making it simple to access and analyze. It supports multilingual data representation and Real-time Data Exploration.
• Connection and Sharing: It includes several advanced capabilities, including collaboration and data distribution.
• Security: Multiple data sources are connected in a highly secure manner. It’s simple to import and export large amounts of data.
• Advanced Visualization: In Tableau, you can make a variety of visualizations ranging from ones as simple as Pie Charts or Bar Graphs to very complex ones like Histograms and Gantt Charts.
• Maps: Tableau has a lot of pre-installed information on maps like cities, postal codes, etc which makes it very detailed and informative.
• Mobile View: Tableau also offers a mobile version of the app in which you can create dashboards and charts that are compatible with the mobile.

What is Tableau Scatter Plot?

A Scatter Plot is a group of dotted points in the horizontal and vertical axes that represent distinct pieces of data. The pattern of the resulting points demonstrates a correlation between two variables when their values are plotted along the X-axis and Y-axis.

In Tableau Scatter Plot, you place at least one measure on the Columns shelf and at least one measure on the Rows shelf. Tableau places the measures as the innermost fields if these shelves contain both dimensions and measurements, which implies that measures are always to the right of whatever dimensions you’ve also placed on these shelves. In this context, “innermost” refers to the table structure.

Creating Tableau Scatter Plot 

Scatter plots are commonly used to represent two measure values or similar field values on a graph as a single dot. It’s a two-dimensional graph in which two measure values, one on the x-axis and the other on the y-axis, determine the position of a data point or dot. To see and evaluate the trends buried in our data, you can use Tableau to add trend lines alongside the dots of the scatter plot.

To make a scatter plot in Tableau Desktop, follow the instructions below. There is a set of sales data from an electronic retailer for demonstration purposes. You’ll use this data to make a scatter plot so you can see how the process works. You can generate a scatter plot using your data source and according to your specifications.

Creating Tableau Scatter Plot: Selecting a Measure

Connect to your data source and open the Tableau worksheet where you want to make a scatter plot. Select a measure from the Measures area and drag it to the Columns section. Here the Sales Data metric is used.

Creating Tableau Scatter Plot: Dragging the Measure to the Rows Section

Drag a different measure from the Measures section to the Rows section. The Profit metric was used here.

Tableau should automatically recognize the style of the chart you should use based on the metrics and dimensions you choose. Select Scatter plots from the Show Me visualization pane on the right if it hasn’t already.

Creating Tableau Scatter Plot: Select Two Dimension Fields

The next step in creating a Tableau Scatter Plot is to choose two dimensions for which values should be shown on the x and y axes. You use two-dimension fields for this: Sub-category, which you need to put in the Marks card’s Color box, and Category, which needs to be put in the Details box.

This creates a rough scatter plot with hollow circle shapes which represent the value points for each brand. The color scheme for each brand is on the left i.e. the value of the sub-category field you are using.

Creating Tableau Scatter Plot: Customizing Your Scatter Plot

You can now modify the color, shape, size, detail, and other attributes of the chart point to suit your preferences. By clicking on the corresponding boxes in the Marks card, you can configure such a setup.

Additionally, by right-clicking on the visualization and selecting the Format option from the drop-down list, you can alter the entire visualization as well as format the worksheet.

Creating Tableau Scatter Plot: Increasing the Details of the Scatter Plot

Tableau also gives you the option of increasing the scatter plot’s detail. To demonstrate data trends, you can use reference lines and trend lines. Go to the Analytics tab to add a trend line to your scatter plot. Select the Trend Line option, keep it down, and drag it towards the scatter plot.

You will see a hovering pane with four available options of a trend line. You need to select the Linear option.

Creating Tableau Scatter Plot: Finalizing the Scatter Plot 

This will generate a trend line for each of the categories in our Category field. You can infer the performance of a parameter using trend lines in a matter of seconds.

As you can see in the Tableau Scatter Plot, the blue trend line indicates that as sales for the category Mobile Phones rise, profit rises as well. However, in the case of Cameras (orange trend line), profit does not increase significantly as sales increase.

Making a Dynamic Tableau Scatter Plot

Dynamic scatter plots are a simple method to add interactivity to your charts by allowing your viewers to compare different data without having to redraw the chart.

This is how you can do it in Tableau:

• Step 1: Create a new parameter using the values listed below.
  • Name: Metric 1
  • Data Type: String
  • Allowed Values: List
  • In the list of values, type all the measures that you want to compare.
• Step 2: Now duplicate the parameter and rename the new value to Metric 2. Now you have two identical parameters.
• Step 3: You can Right-click on the parameters to see the values.
• Step 4: To match the list of values you just added to your input, create a calculated field called Selected Metric 1 with a case statement.

Here are the Selected Metric 1 fields based on the World Indicators data set that comes with Tableau:

// Checks the value of the Metric 1 parameter and returns the corresponding measure field. 
 
case [Metric 1]
when "CO2 Emissions" then [CO2 Emissions]
when "Energy Usage" then [Energy Usage]
when "GDP" then [GDP]
when "Internet Usage" then [Internet Usage]
when "Mobile Phone Usage" then [Mobile Phone Usage]
when "Tourism Inbound" then [Tourism Inbound]
when "Tourism Outbound" then [Tourism Outbound]
end

Adding Segments to your Tableau Scatter Plot

Color coding individual data points into segments or groups is another technique to acquire insights from your Tableau scatter plot. You can do this by using above or below average segmentation logic.

Here are the steps to get this done:

• Step 1: Create a new calculated field and name it Metric 1 Segments.
• Step 2: Add your segmentation logic. For example:

if [Selected Metric 1] >=
{ FIXED : AVG([Selected Metric 1]) }
then ‘Segment 1’
else ‘Segment 2’
END

The above code will put each data point into a segment. The decision will depend on whether it is above or below the global average.

• Step 3: Create a duplicate field and rename it to Metric 2 Segments and change the code logic to select Selected Metric 2 instead of Selected Metric 1.
• Step 4: Select the new segment fields formed and drag them to the marks card’s color section. The legend should automatically display four different colors, one for each of the above and below average parts in the scatter plot. 

Tips to Create Better Tableau Scatter Plots

Here are a few tips on how to make your Tableau Scatter Plot even better:

• Tip 1: A Formatting Trick
• Tip 2: Maximizing Data-Ink Ratio
• Tip 3: Adding a Segmentation Calculated Field

Tip 1: A Formatting Trick 

One of the advantages of scatter plots is that they allow you to analyze a large number of marks in a little amount of area. This, however, frequently results in overlapping marks. It’s simple to fix this by going to the Color Marks Card and lowering the opacity of the marks, but this doesn’t work well with mark borders.

The following method gives you complete control over the marks and their boundaries, giving you a lot of formatting versatility.

• Step 1: Place the dependent measure on the Rows Shelf next to itself a second time to format marks and their borders independently. This will result in two rows of the same chart. By clicking on the second occurrence of the measure on the Rows Shelf and selecting Dual Axis, you may convert the two rows to a dual-axis scatter plot.

• Step 2: Finally, right-click on either y-axis and select Synchronize Axis to guarantee the dual axes are synced. Both scatter plots have now been stacked on top of one another.

• Step 3: The second y-axis is not needed anymore so you can hide that by right-clicking on it and deselecting Show Header.

Tip 2: Maximizing the Data-Ink Ratio

One of the Data-ink ratio’s tenets is to eliminate duplicate data, which, often manifests itself in the form of too many axis tick marks. Cleaning up an axis in Tableau is as simple as right-clicking on it, selecting “Edit Axis…”, and selecting “Fixed” on the “Tick Marks” tab.

• Step 1: Delete any unnecessary lines, including borders and zero lines (optional depending on your analysis). You may do this by right-clicking anywhere on the chart, selecting “Format…”, and editing the “Borders” and “Lines” tabs (the fourth and fifth icons at the top of the Formatting pane, respectively). After removing the Row Dividers, Column Dividers, and Zero Lines, the scatter plot looks like this.

• Step 2: Modify the Grid Lines’ Formatting to make them dotted and thicker in weight. After making this edit and placing the fonts in the brand. Here’s how it will look:

Tip 3: Adding a Segmentation Calculated Field

A natural four-quadrant segmentation is created by adding reference lines for the average of each axis. By using a calculated field to make that segmentation permanent, you’ll be able to separate the four parts and analyze and act on them independently based on their behavior.

• Step 1: Go to the Analytics pane and drag Average Line into the view to add an average reference line to each axis. You may also create reference lines by right-clicking on each axis and selecting “Add Reference Line” if you prefer.
• Step 2: To isolate each group, using the WINDOW AVG table calculation, build a calculated field. The formula for the four-quadrant segmentation is as follows:

IF [Profit Ratio] > WINDOW_AVG([Profit Ratio]) AND SUM([Sales]) < WINDOW_AVG(SUM([Sales])) THEN “High Profit Ratio & Low Sales”
ELSEIF [Profit Ratio] > WINDOW_AVG([Profit Ratio]) AND SUM([Sales]) > WINDOW_AVG(SUM([Sales])) THEN “High Profit Ratio & High Sales”
ELSEIF [Profit Ratio] < WINDOW_AVG([Profit Ratio]) AND SUM([Sales]) > WINDOW_AVG(SUM([Sales])) THEN “Low Profit Ratio & High Sales”
ELSE “Low Profit Ratio & Low Sales”
END

• Step 3: Place the computation on the Color Marks Card once you’ve completed it.

As you can see, all of the marks are the same color so far. Because table computations (including WINDOW AVG) are performed from left to right by default, this is the case. You need to alter the default Table (across) addressing of the table calculation to the level of detail you’re segmenting: Sub-Category. This can be done by hovering over “Compute Using” and selecting “Sub-Category” after clicking on the measure with the delta symbol ().

Here’s how it looks after changing all four colors:

To isolate the segments, follow the steps given below:

• Step 1: Right-click on the segment of interest on the color legend and select “Keep Only” to filter the display.

• Step 2: Create a set by dragging a box around the marks, right-clicking any of them, and selecting “Create Set…”

• Step 3: You’ll have an isolated set of the dimension members in your segment in the Sets area of the Data pane after giving it a name and clicking “OK.”

Conclusion

This concludes the tutorial on how to create Tableau Scatter plots. You learned about Tableau, its key features and what scatter plots are, and how to create them in 6 steps.

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