Are you working with a huge dataset in Tableau, and bar charts aren’t enough to visualize the data efficiently or make out actionable insights from the chart visuals? You can go a step ahead and use histograms to visualize the insight you’ve been looking for.
Charts and graphs in business intelligence tools like Tableau enable you to visualize the underlying pattern in your business or general survey data. When the dataset is vast, and numbers are scattered in numerous individual data points, combining a few data points into a bucket and creating a few hundred buckets instead of visualizing individual data points is good.
That’s where the histogram steps in. And what could be a better BI tool to create intuitive and informative histograms than Tableau, as it comes with both automated and manual ways of making this statistically significant data visualization method?
Read this article until the end to learn everything you need to know to build awesome histograms in Tableau in a few minutes.
What Is a Histogram?
A histogram is a charting tool in statistics that displays data distribution in numbers on both the X and Y axis of the chart. It consists of bars that represent the frequency or count of values within specific ranges or “bins.”
You can arrange the bars horizontally or vertically depending on the input dataset and visualization needs. The height of each bar corresponds to how often data falls into the associated bin.
Histograms help visualize the shapes and patterns in data. Thus, it becomes easier for you to identify trends, outliers, and central tendencies.
You commonly use histograms in statistics and data analysis to explore data sets. That’s because every audience from different skill levels can easily understand and interpret the data visualization you present.
In a nutshell, histograms create a visual summary of data or enable data storytelling, making it a valuable tool for making informed decisions and drawing insights from data.
Importance of Histograms in Data Analytics and Visualization
Find below the importance of histograms in data analysis:
Histograms help you comprehend data distribution, revealing patterns, central tendencies, and potential outliers.
This statistical analysis tool also assists in identifying errors or anomalies in data by showing unexpected spikes or gaps in the distribution.
Histograms aid in deciding how to preprocess data, such as selecting appropriate bin sizes or identifying data transformations.
You can overlap different histograms of the same dataset or related datasets to create comparisons of different groups in the same dataset or different but related datasets.
In decision-making, histograms provide clear, visual evidence to support choices or actions based on data analysis.
Nontechnical audiences or business stakeholders can easily grasp the data storytelling made by histograms.
Now that you know what histograms are capable of, it comes down to one question when to use this powerful data visualization tool. Take a peak into the data analysis and visualization problem below:
The bar chart above plots product names along the X-axis and their corresponding sales values along the Y-axis. There are 1849 products in the sample dataset.
As you can see from the data visualization above, it’s not completely viewable on one screen and needs continuous scrolling to see what is happening to the other products that aren’t visible on the screen.
The golden rule of data visualization is you must show the whole data on one screen in a logical way. So, you can create buckets of products that fall within a category or group of sales values, say $10, $20, $30, and so on in increments of $10.
Therefore, create a histogram plot to put all the products on these sales buckets to make sense of the data shown in the histogram above. It significantly reduces the number of data points from 1849 to 279 and fits in one screen; no scrolling is needed.
Why Should You Choose Tableau to Create Histograms?
Tableau is an ideal choice for creating histograms for several compelling reasons. First, it offers a user-friendly interface that caters to both technical and non-technical users, ensuring ease of use. You can swiftly generate histograms and interact with your data dynamically. Tableau’s flexibility extends to its ability to connect with diverse data sources, making it suitable for a wide range of projects.
Moreover, Tableau allows for extensive customization, empowering you to tailor histograms to your needs and preferences. The visually appealing outputs produced by Tableau lend a professional touch to your data visualizations, enhancing their impact.
Sharing and collaboration are made seamless, fostering teamwork and knowledge exchange. With a robust and active user community, you’ll find ample support and resources readily available.
In summary, Tableau’s user-friendliness, data integration, customization, interactivity, and strong community backing make it a top choice for creating histograms.
Prerequisites of Creating Histograms in Tableau
Creating a histogram in Tableau requires at least one data field that contains the values you want to visualize as a distribution. Here are the basic data requirements:
You’ll need a data field that contains the values for the histogram. This field shall represent the variables you want to analyze. For example, if you’re creating a histogram of sales data, you’ll need an area that contains the sales figures of several products or from several years or months.
You’ll also need to create bins of a measure in your dataset. In Tableau, a measure is a metric you’re monitoring in your data. For example, if your dataset contains a column for sales data of different products, that’s a measure. You can create the Sales Bin component to put products with the same sales value into different bins.
Frequency or Count
Furthermore, you’ll need a field that indicates the frequency or count of each data point within the bin. You can often generate this using Tableau’s COUNTD or COUNT functions.
The bin of the measure should be continuous. Otherwise, the histogram will show like a bar graph where the columns are separated from each other. However, you can also use Tableau to convert discrete measures to continuous measures in a single click.
Your data should have sufficient context and metadata. Make sure you have relevant information about the data, such as date or time stamps, categories, or any other attributes that can help in the analysis.
How to Create a Histogram in Tableau
There are two ways to create Tableau histograms using external datasets. One is the Show Me, an automatic method, and the other is the manual method. Find instructions for both methods below:
#1. Create a Histogram in Tableau Using Show Me
Show Me is a Tableau tool that enables you to create various data visualizations in one click using the connected data. It only generates meaningful visualizations when the data structure is appropriate and clean.
Connect Data Source
There are three ways to get a data source for the current exercise. You can either use built-in data sets, connect to an external server or import data from Excel or CSV. Find below instructions:
Open the Tableau desktop app on your PC or Mac.
Click any of the Accelerators to import ready-made datasets into Tableau.
Alternatively, click Microsoft Excel, Microsoft Access, etc., below the To a File section to set up a connection.
Or, click on any of the connectors under the To a Server section to connect your Tableau workspace with an external dataset maintained on a cloud or onsite SQL server.
Select a Measure
After linking a dataset, you should see a new blank worksheet in Tableau.
If you’re practicing by using any of the Accelerators of Tableau app, click the New Worksheet button on the bottom menu bar of Tableau.
A blank worksheet will open.
From the left side navigation pane, drag and drop a measure into the Columns field on the top of the worksheet name.
Use Show Me to Populate the Histogram
Now, simply click the Show Me menu on the top-right corner of the Tableau desktop app. The data visualization menu of Tableau will show up.
There, click the Histogram option to quickly populate an automatic histogram visualization developed by Tableau.
#2. Create a Histogram in Tableau Manually
In unique cases, such automatic histograms may not be able to show you the data insight you’ve been looking for in your dataset. Also, to become a data science expert, you must know the manual ways of creating visualizations, including histograms. Follow the instructions below:
Link a Dataset to Tableau Workspace
You can follow the steps mentioned previously about connecting datasets to Tableau and then go to the next step.
Create a Bin Using a Measure
I suppose you’re using the Sample Superstore data of Tableau and using the Sames measure against the Product Name measure to create a histogram in a new worksheet.
Select the Sales measure from the Tables menu on the Tableau data pane.
Right-click and hover the cursor over Create.
On the Edit Bins dialog, enter a value into the Size of Bins field.
Click OK to complete the bin creation process.
Now, drag the Bin from the Data pane into the Columns.
Right-click on the Sales Bin and choose Continuous from the context menu.
Add Another Measure into the Rows of Field
Now, expand the Product relational hierarchy of the Data pane and find the Product Name measure. Drag and drop the measure into the Rows field on the blank worksheet.
Then, right-click the Product Name measure on the Rows pane and choose Measure > Count.
Congratulations! You’ve successfully created a basic histogram in Tableau.
Apply Logarithmic Scale
The histogram you get isn’t clear enough. You can apply Logarithmic scales to both the Y and X axes to make the histogram more user-friendly. Follow these steps:
Right-click on the Y-axis and click on Edit Axis.
Under the Scale section, checkmark the Logarithmic checkbox and close the Edit Axis dialog box.
Similarly, do this for the X-axis data.
On the top menu bar of Tableau, click the Show Mark Labels icon to visualize the number of items in each bin.
Now, you’ve got a functional histogram that clearly tells you about the sales vs. product name data visualization.
Add More Measures to Color
You can add multiple measures into the Marks buttons, like Color, Size, Label, Detail, and Tooltip, to use the histogram to visualize more data. Here’s how:
Drag and drop the Ship Status measure onto the Color tab.
The histogram now shows a three-color-segmented distribution of shipped orders.
Best Practices to Create Histograms in Tableau
You can consider these tips and tricks to make your Tableau histograms accurate, clean, and insightful:
You must start with a bar chart in Tableau before creating a histogram. Chart selection is highly essential as other chart types like line charts or scatter plots aren’t suitable for histograming.
Also, you should start with a logical and appropriate bin size for the histogram. In Tableau, you’ll get default suggestions from the tool, and in most cases, these are accurate. However, you can also go through trial and error to find the best bin size for your dataset.
You should label both the x-axis (bins) and y-axis (frequency or count) clearly. Also, ensure units and titles are informative.
If your data is highly skewed or has outliers, consider using the logarithmic scale or other transformations to better represent the distribution.
Use colors and styling to make the histogram visually appealing. Consider color-coding to highlight specific data points or categories.
Create a bin control to introduce a slider to the bin size property. You can just slide it to change the bin size quickly and see if a different bin size reveals anything special about the dataset.
Add annotations or reference lines to emphasize important data points or thresholds.
Document your visualization with comments or descriptions to make it understandable to others who may use or modify it.
So, now you know how to create a histogram using Tableau. You’ve learned both the automatic and manual methods of Tableau histogram generation. Give the above methods a try using your own dataset and experience powerful data analytics and visualization capabilities on Tableau.
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