Tableau: A Basic Example with Volcanic Eruptions
In the previous post, I gave an introduction to Tableau, which is a powerful platform to create data visualizations and dashboards. I also mentioned that we would later take a look at some of the basics of Tableau. Well, here we are!
One of the best ways to get an idea of the basics is to go straight into an example. For those who are just learning about the different uses of Tableau, I would suggest taking a look at the some of the sample data sets that are available on the Tableau Public website. The easiest way to get there is through the Tableau Public App. When Tableau Public opens, one of the resource hyperlinks is to this sample data sets site.
From there, the computer will open the website in your preferred browser.
As you can see above, there are multiple areas of interest that have sample data sets such as Entertainment, Sports, Government, and Science. You will notice that each data set has three pieces of informations: the title, a description of the data set, and what type of file it is. For this example, we are going to be using the Significant Volcanic Eruptions data set in the Science section, which is an excel spreadsheet.
When you click the type of file you want to download, it will automatically start downloading to your computer.
The next step is to go back to the Tableau Public App Home Page and choose which type of connection you want to make. As mentioned above, the file is in the format of an excel spreadsheet, so we want to choose that connection.
It will open to your documents, and you navigate to your file to open the connection. The first page that opens when you create the connection is the Data Source Page.
There are a few options available. In some excel files, there are multiple sheets of data. You can choose from the sheets shown in the left column and bring up the data from that sheet. There is also an option to use “Data Interpretation”, which is a Tableau tool that can help clean up the data. In excel spreadsheets, there are times when the first few rows are empty, and the program would notice this and remove those rows.
In this excel file, there are two sheets: “metadata” and “volerup”, which is short for volcanic eruptions. All that is needed to load the data is to drag and drop the sheet to the center of the screen. When loaded, it will show the data set in a table and will mention the different fields or columns that can be found in the sheet.
This has a lot of good information, but this is still not too different from the original excel spreadsheet. To start working on visualizations, you have to change over to the “Sheet 1” tab.
Once clicked, it will take you over to a screen for creating visualizations.
There are a lot of different screens, so this might seem confusing at first. In the left column, there are two tabs: one for Data, which is the default tab, and one tab for Analytics. In the Data tab, it shows a list of fields from the table. These are organized into “dimensions” and “measures.” This is just Tableau’s way of separating the columns into categorical and numerical values respectively.
Within these two sections, there is a symbol on the left and the name of column on the right for each column in the data set. The symbol on the left represents what type of categorical or numerical value that column represents. A globe represents a geographical value, an “Abc” represents a string, and a hashtag represents an integer.
One other fun piece to notice is that some columns have “(generated)” at the end. This means that there is a column in the original data set that can be represented in another way and Tableau will automatically create these new fields. For example, the Country field can also be represented by longitude and latitude, which is why you see both a longitude and latitude set and a generated longitude and latitude set as well.
To start creating a visualization, all that is required is to drag and drop one of the fields. This field can be dragged to multiple points: there is a x and y axis and center field on the sheet, and above that are two rows, one for columns and another for rows. An interesting fact is that in the top right corner there is a “Show Me” tab. This will show the wide range of visualizations that can be created using Tableau and what their requirements may be in terms of categorical and numerical fields.
For this example, let’s start out by dragging and dropping the Countries field into the center of the sheet.
This is quite amazing. Tableau automatically creates a map visualization with the generated Longitude and Latitude already entered into the columns and rows field respectively. This allows for the creation of a world map with a dot for the countries that have had a historically large volcanic eruption. In the center column, there is a section for marks. This allows you to change parameters such as the color, size and label for the marks of the highlighted field.
Next, let’s find out a bit more about the size of the eruptions in each country. So let’s drag and drop the Volcano Explosivity Index (VOI) field onto the map.
Now this is quite interesting. The addition of the new field has added a new parameter to the Marks section and there is a legend in the top right corner to help explain the visualization. However, you might notice something odd in the legend: each level is in the hundreds range. But doesn’t the VOI field have smaller numbers like 7 or 8? The problem is that Tableau has automatically set the parameter for the SUM of the different indexes from each eruption. Instead, we might want to know the highest VOI for each country. To do this we can click the field in the Marks section and change the measure tab to the maximum setting instead of the sum.
A bit more interesting, right? Now we have a visualization that shows which countries had the worst volcanic eruptions in terms of the VOI. This was just a quick example of one visualization that could be made from this dataset. Don’t be afraid to explore the different options in the “Show Me” tab and discover what types of other visualizations you can make.To start fresh and clear the current visualization, there is a tool icon in the toolbar.
I hope this post helps your understanding of how easy it can be to create interesting visualizations from a data set. Have fun exploring the options and thanks for reading.
The original data used in this example came from the NOAA website and National Geophysical Data Center:
Citation:
National Geophysical Data Center / World Data Service (NGDC/WDS): NCEI/WDS Global Significant Volcanic Eruptions Database. NOAA National Centers for Environmental Information. doi:10.7289/V5JW8BSH
