This project is a demonstration of using NumPy for data analysis and visualization. We analyzed the monthly revenue and expenses of a company over the past year by loading two CSV files containing the revenue and expenses data respectively. We performed various operations on the data, such as calculating the mean, maximum, and minimum values, as well as finding the months with the highest and lowest revenues and expenses.
To visualize the trend in revenue and expenses over the year, we plotted the data on a line graph. This helped us to identify any patterns or trends in the data, such as months with higher or lower revenues and expenses. We also plotted the revenue and expenses data on separate bar graphs with labeled axes and added a legend for easy identification. This allowed us to compare the revenue and expenses data side-by-side and to identify any discrepancies or changes in spending patterns.
We used a pie chart to compare the total revenue and expenses for the year. This showed us that the company spent more than it earned, indicating potential financial difficulties. This is an important finding as it highlights the need to monitor revenue and expenses regularly to ensure the financial health of a company.
Overall, this project demonstrated how NumPy can be used for data analysis and visualization in a practical setting. It also highlighted the importance of monitoring revenue and expenses for financial health and showed how different visualization techniques can be used to identify patterns and trends in the data.
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