Using data from USDA we designed a dashboard regarding the most commonly consumed vegetables by Americans.

We were required to design our dashboard before looking into the data.

This was my initial plan:

We were then required to do all data prep in Tableau Prep.

The first stage was to bring in all sheets with a wildcard union.

When the data was initially inputted column headers were in the rows rather than as headers.

This was easily fixed using the data interpreter that is built into Tableau Prep.

I did rename some fields manually after the data interpreter but this was minimal. I then also removed some fields that I knew immediately wouldn't be useful.

Next I pivoted the Veg Name column, this reduced the number of columns and gave me a better format for my data.

Next I merged 2 columns that contained the same data but had different titles. This reduced nulls. Then I looked through the data and removed the remaining unnecessary fields, changed the data type of the date field to a date. I also removed some rows that were not relevant.

Finally I outputted the file as an excel document and connected this to tableau.

Creating the dashboard involved calculations to show the change year to year of consumption.

I included filters to show the differences over time and an overview of each type of vegetable.

Final Dashboard:

Challenges:

Renaming column headers. This actually had a very simple solution in this instance. Since we were using an excel file. It was possible to simply use Tableau Prep's data interpreter.

The data contained numerous null rows. Deciding whether to keep or remove the columns that had large amounts of null data was difficult. I decided whether the column would be useful and if not I simply removed it from the data source.

I also found that data was being skewed by generic vegetable fields so I removed these rows from the data source.

Some of the calculations took a bit of time to figure out so working to a time limit became a struggle.