The resulting visual gives us an annual total of exports, but we can go deeper.
In the column slot, click the “Date” cell and select “Month”. This provides a clearer representation of fluctuations in the cotton export value during the year.
In the “Marks” box select “Label”, and click the box next to “Show Mark Labels”. Now our data is effectively communicating the monthly totals of cotton exports. Now let’s incorporate each destination to further increase the accuracy of the data.
Drag and drop the “Country” cell into the Color box. Now we can see that a majority of the cotton exported every month was shipped to England.
Tableau is great for creating visualisations from your data, but it also is useful for data exploration. When we create data visualisations it is important to remember to keep graphics simple and self-explanatory. For independent data exploration, however, we can try simple as well as complex approaches. Experiment with your data in the software to not only create graphics, but to see how different visualisations help you think about your research.