Government Expenditure Data Exploration & Analysis Using Python

Abstract

The goal of improving cost efficiencies is a constant endeavor of all organizations. This is especially true for governments, where public perception often has the ability to affect budget allocations. The data used in this analysis consisted of publically available state expenditures from 2018 and 2019 for the state of Idaho. The dataset contains the record of over 2 million state expenditures across all state agencies. The data analysis was performed using Python and the Pandas library. Visualizations were created using the Matplotlib package. The data exploration showed that Idaho’s Departments of Health and Welfare, Education and Transportation spent the most in this time period. The analysis also determined which Summary Objects, Sub-Object and Vendors experienced the greatest changes between the two years. Comparisons were also done using publicly available data on reported budget allocations by the states of Arkansas, California, Texas and Montana to see how spending differs between Idaho and these states based on percentage and per capita. Finally, suggestions for improvement in the areas of health care and employee transportation were given. These include methods of improving competition in health care, reducing travel through expanded teleconferencing and providing incentives to employees for reduced travel cost. Keywords: data science, budget analysis, python, pandas, government spending