1. Navigating Tableau
Welcome back!
Now that we've connected our data sources, let's get comfortable with the Tableau interface.
2. Tableau interface
This is the interface for Tableau worksheets, where you will create your visualizations. You can see that there are different components that make up the interface. We'll explore them in the demo, but first there is some Tableau jargon to get familiar with.
3. Data
The data pane shows the data sources you've loaded. Here we have just one file, our Airbnb listings in San Francisco. You can see there's another pane, Analytics, which you will look into later on.
4. Dimensions and measures
The data pane also shows all available fields or columns of your data source. Notice the use of two different colors, green and blue.
5. Continuous
Green fields are continuous fields, treated as an infinite range. Examples are the number of reviews per month, room price, or the longitude of the location.
6. Discrete
Blue fields are discrete, or categorical fields, which means they have individually separate and distinct values. Examples include room type, neighborhood, and the ID number of the listing.
7. Dimensions
While the color of the fields indicate whether they are continuous or discrete, the position of the fields in the data pane indicate whether fields are treated as dimensions or measures.
Dimensions, positioned at the top, contain qualitative values, such as names or dates. Our dimensions include Neighborhood, Room Type, or number of reviews per month.
8. Measures
Measures (positioned under the dimensions) contain numeric quantitative values that you can, well, measure, and aggregate.
Examples of measures in this dataset include price, the number of minimum nights, and the total number of reviews.
Tableau assigns these so-called data roles to fields automatically. Again, it is good practice to review these and adapt where necessary.
9. Converting between dimensions and measures
For example, it makes sense to convert the number of reviews per month to a measure, as you might want to calculate the average of it, for example.
You can convert fields between measures and dimensions,
10. Converting between discrete and continuous
or between discrete and continuous. As any combination of data roles is possible in theory,
11. Data roles in Tableau
here is an overview. Discrete dimensions and continuous measures are the more common combinations of data roles. They include the classic examples of eye color and sex, and height and weight, respectively.
12. Data roles in Tableau
Less common combinations are discrete measures (for example, shoe size and age) and continuous dimensions (for example, date).
13. Segmenting with dimensions
Why are data roles so important in Tableau?
Note that changing the data role of a field will affect your visualization possibilities.
Dimensions allow you to group and segment data, while measures can be aggregated and add quantitative values to dimensions. Segmenting means grouping similar data for each category, for example calculating the average price for each room type.
14. Dragging dimensions and measures
Creating visualizations is done by dragging and dropping dimensions and measures on the canvas, shelves and cards.
15. Canvas
The canvas is where your visualizations will appear.
16. Columns
Columns correspond to the x axis of your view,
17. Rows
and rows to the y axis.
18. Pages
The Pages shelf lets you break a visualization into several pages; for example, one page for each neighborhood.
19. Filters
The filters shelf lets you filter your data, and you will learn more about this in a next chapter.
20. Marks
The marks field contains marks cards and marks types.
21. Marks cards
Marks cards encompass color, size, and shape: these let you add context and detail to your view.
22. Marks types
You can change the type of marks displayed in the view to fit your analysis better.
23. Toolbar
Finally, the tool bar lets you quickly access useful features, such as undoing, sorting, clearing the canvas, and so on.
24. Our business question
Alright, enough theory for now - let's start playing with some data in Tableau!
In the exercises, you'll look at the price of rooms in each New York neighborhood.
25. Let's practice!
But first, let's test your knowledge on dimensions and measures.