What are Bins in Tableau?

Introduction to Bins in Tableau

Tableau has a feature called Bins, one of its more helpful features. Analyzing and visualizing the data is simpler when you can divide numerical data into certain ranges or categories using bins. Dealing with continuous data, such as ages, prices, or quantities, calls for this capability in particular.

Consider you have a Tableau dataset with customer age information. You can use the Bins function to arrange the ages into ranges rather than viewing each age individually.  

For example, divide the years into 10-year bins, such as 0–10, 11–20, 21–30, and so on. Using this grouping, you can easily analyze the distribution of the various age groups. You can analyze any patterns or trends in the data. Bins help to organize the data and make it easier to work with for analysis and visualization.

Alright!! Let us look at the uses of Bins in Tableau.

Uses of Bins

The following are the uses of bins:

• Data Grouping and Categorization: Tableau improves the study and visualization of these essential factors by grouping data into specific bins, allowing insights into consumer behavior, inventory management, and income distribution.
   
• Enhancing Data Visualisation: By giving patterns and distributions a clearer representation, binning data can significantly improve data visualization. Binned data can be used to produce visualizations like histograms, bar charts, and heat maps to reveal insights that wouldn't be clear with individual data points.
   
• Simplifying Complex Data: Bins in Tableau allow simplifying complex data by dividing it into specified ranges or categories. They reduce data granularity by combining individual data points into larger bins, making it easier to analyze and visualize trends and patterns without overloading the audience with too much information.
   
• Supporting Statistical Analysis: Preprocessing for statistical analysis can include using bins. When you divide data into bins, you may use statistics to calculate averages, medians, or proportions within each bin, giving you a deeper understanding of the data.
   
• Dealing with Big Datasets: Bins can be very helpful when working with big data. Grouping the data into bins instead of analyzing each data point minimizes the number of distinct values, making the analysis easier to handle and more effective.
   

Alright!! Let us look at how to create a bin in Tableau.

Creating a Bin in Tableau

Following are the steps for creating a bin in Tableau:
 

1. Select the desired field or dimension from which you want to retrieve the data in the Data panel by right-clicking it.
 

2. Click on Bins after choosing the Create option. As you can see in the image below, we used the Discount field.

3. Enter a number in the Size of Bins field. In addition, by selecting the Suggest Bin Size button, Tableau will provide a Bin Size recommendation for your selected data set. Tableau uses the following formula to determine the ideal Bin size:

Number of Bins = 3 + log2(n) * log(n)

n = the number of different rows in the table, and the size of each bin is calculated by dividing the difference between the smallest and greatest values by the number of bins.

In the lower section of Create dialogue box, you will see 4 read-only fields:

Min: It stands for the field's lowest possible value.

Max: It stands for the field's highest possible value.

Diff: It acts as a representation of how the Min and Max fields differ.

CntD: It stands for the total number of distinct values in the data.

As it is showing Edit Bins because we are using Tableau on Web.
 

4. Now, your Discount bin is created in Tableau. You can see it on the Data Panel.
 

5. Now, you can follow the same steps to create the bin of your desired wish.

How to edit a Bin in Tableau?

Follow these steps to edit a bin in Tableau:
 

1. Click right on the bin you’ve created. 

2. You will see the Edit option there. Click on that.

3. Now, you can change any parameter as per your requirement.

Best Practices for Binning

For optimal data analysis and visualization while working with bins in Tableau. These various best practices must be followed.

• Choosing the Correct Bin Size and Range: Choosing the correct bin size and range is critical. A few bins may simplify the data, while too many can introduce noise and make it difficult to find trends. Experiment with various bin sizes to find the best balance.
   
• Labelling and Formatting Bins: Provide clear labels and formatting for your bins to improve comprehension. Use significant bin labels to represent the range of values included within each bin. To avoid misunderstanding, format the labels consistently and clearly.
   
• Regularly Reviewing and Updating Bins: As data changes over time, it's critical to check and update your bins on a regular basis. This guarantees that they remain current and represent the most recent data attributes. Monitor changes in your data distribution and alter bin sizes or ranges accordingly.

Alright!! Let us look at the limitations and considerations of bins in Tableau.

Limitations and Considerations

Some of the limitations and considerations are discussed below:
 

Granularity loss: Binning is the process of arranging data into preset ranges or categories. As individual data points are combined into bins, granularity may be lost. Consider whether this level of transparency is appropriate for your analytical and visualization goals.

Impact on Insights: Binning might change the distribution and patterns of your data. Be aware of how binning influences the insights and conclusions gained from your study. Considering the trade-off between simplifying the data and perhaps masking key information is critical.

Bin Size Sensitivity: The size of the bins may affect how the data is processed. Small bin size modifications might result in various patterns or trends in the visualizations. Testing and experimenting with different bin sizes is critical to provide meaningful data representations.

Consider Data Characteristics: Binning may be more appropriate for continuous numerical data. Binding may not be beneficial for categorical or ordinal data. Before using binning techniques, consider the type and properties of your data.

Frequently Asked Question

Why use bins in Tableau?

Using bins in Tableau simplifies complex numerical data by grouping it into categories or ranges, aiding analysis and visualization. It helps identify patterns, facilitates comparison, enhances data visualization, and supports statistical analysis, making it easier to understand.

What is the formula for bins in Tableau?

The formula for creating bins in Tableau involves selecting a numerical field, defining the bin size or range, and assigning data points to their corresponding bins.

Number of Bins = 3 + log2(n) * log(n).

What is customized bins in Tableau?

Customized bins in Tableau refer to the ability to define specific ranges or categories for grouping data based on user preferences. Instead of using a fixed bin size, users can manually set the bin ranges according to their analysis requirements.

Conclusion

In this article, you have learned about what Bins are in Tableau, the uses of Bins, the steps of creating a Bin in Tableau, and editing a bin in Tableau.

We hope this article briefly helped you learn about what Bins are in Tableau.

If you want to learn more, refer to these articles:

• Tableau and Big Data
   
• Tableau Interview Questions
   
• What are Aliases in Tableau?
   

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