Day 4 saw us examine food waste. The data comes from OECD. From the OECD website:
The OECD food waste dataset is a compilation of available data related to food loss and food waste for 32 countries. The period covered may vary across different countries depending on data availability (globally ranging from 1993 to 2013).
We were told that the data would need cleaning, and if we were struggling to use the fully cleaned data set if we hadn't finished by 10:30. There was however an option to download the fully cleaned data set direct from the OECD site as a .csv, which was confusing! However after exploring this dataset (which was very patchy!) I decided I was going to focus on Japan as they seemed to have consistent data and it looked like there was a story within the data!
Even though I had the cleaned data I decided to download Japan's data and clean this up myself, my workflow is shown below:
The data didn't need too much cleaning, a few multi-row formulas in order to fill in some empty rows and some data shape manipulation using the transpose tool was the way I went about it.
In Tableau it took me a while to get my head around the data as there were various different units of measurement, I decided that food waste in "tonnes" made the most sense to me, so I placed a data source filter on to exclude all other measures.
I decided to break my analysis up by category over time using a circle timeline, and you can click on a category to filter an area chart and some big numbers opposite.
The bottom section of the dashboard shows yearly analysis where you can look at the breakdown of categories by selecting a year.
Lastly I noticed there was a breakdown of specific food waste conducted in 2009, so I included that as a bar chart! Here is my dashboard below:
Link to viz:
Day 4 - Simon Evans | Tableau Public
