In 2022, the avocado market was valued at ~$14 billion, with estimates predicting a future valuation of ~$21 billion by the year 2028. As westerners continue to demand and consume this delicious fruit, the market correspondingly reacts to try to meet these demands.

The prices of such commodities are largely determined by the intersection of these forces of demand and supply. Thanks to technological advancements in the modern age, it has become increasingly easier to log, track, and analyze price and market data revolving around virtually any commodity, avocados included.

Being able to have access to these forms of data is advantageous for a variety of different reasons. Whether you are a commodities trader, a researcher looking for answers to a question, or simply want to be a more informed consumer, being able to analyze metrics such as price trends and volume of a good may be of great use.

Because of this, I wanted to create a (very) simple and straightforward dashboard that charts the average price and total volume of avocados sold across the state of California over three years of data.

The data used for this app/dashboard comes from a Kaggle dataset by user Justin Kiggins, which is originally sourced from the Hass Avocado Board.

To keep the app simple and less convoluted, I decided to only use the data limited to the state of California (California produces ~95% of the avocados grown in the US, and ~10% of the entire world’s production!). Additionally, I decided to focus only on the average price and total volume metrics to plot as charts.

Furthermore, each row/observation of the data is taken one week apart from one another.

The app is fairly straightforward to use, and has some documentation detailing everything you need to know to get started using it.

First, select which type of avocado data you would like to view (conventional vs. organic). Then, you can filter the data by regions of California (or view the entire state). Lastly, you can control what time frame you would like the view the charts in, giving the user control to investigate certain years or months of interest. As the user filters what data they would like to use/see, the charts react dynamically.

The charts are stacked on top of each other deliberately, so that users can easily observe corresponding changes or trends in volume with respect to the average price of any date.