This is the Pythonic Accountant and for you today we’re going to take a look at the data analysis tool or Advanced Data Analysis Tool in GPT 4 and explore some interesting data from the state of Florida. We will be focusing on the Statewide Municipal expenditures by major category. The data is organized in different tabs for each fiscal year, allowing us to analyze trends over time.
Our goal is to gain insights from the data and identify any unusual spending ratios or trends. We will start by organizing the data and then perform a comprehensive analysis across all fiscal years. We will analyze the total spending by category for each municipality and look at the year-over-year percentage change in spending. Additionally, we will flag any unusual ratios in spending categories.
To visualize the data, we will create trend lines with the fiscal year on the x-axis and the percentage change on the y-axis. Each category will be represented by a different color line. This will allow us to easily identify trends and patterns in the data.
Unfortunately, we encountered some issues with the fiscal year column in the data. Despite multiple attempts to correct it, the issue persisted. However, we were still able to generate a correlation heat map of the consolidated data, which provided an initial idea of the relationship between different categories of expenditures.
In conclusion, although we were not able to fully analyze the data due to the technical issues, we explored the data analysis tool in GPT 4 and demonstrated its capabilities. The tool showed great potential in analyzing and visualizing data, and we look forward to further exploring its features in future videos.
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