In this Power BI visualization project, I was able to illustrate the trends between how much income people in New York make in connection to the percentage of people who have obtained a college degree, and whether they are in rural or urban areas. The data that I used to create these visualizations was obtained from the USDA and the US Census Bureau. It provided statistics on county-level population, income, poverty level, college education, and rural vs urban status in the US states. Poverty level is defined as the “percent of county population living in families with income below their poverty threshold” (USDA 2021). For people that are not living in families, poverty is determined by comparing the individuals income to their poverty threshold. Urbanicity status in the US is determined by a nine-category county classification based on metropolitan, micropolitan, and noncore counties. The most urban are large metropolitan areas with atleast 1 million residents and adjacent counties. The second most urban is small metropolitan areas with fewer than 1 million resident and their adjacent counties. The most rural is micropolitan areas that are not adjacent to metropolitan counties that have populations between 5,000 and 19,999.

In the scatter plot, the median income line that we had to create is different than what the median Power BI tries to give because Power BI places a line at the median value of our data, which isn't the median value across the whole state. In the map, County-level poverty rates are shown across the state, with darker shades indicating higher rates of poverty. In the scatterplot visualization, a majority of the dots lie in the range of no college degree and below the median per capita income. All of the rural areas have below median income and have no college degree, and most of the urban dots also lie in this range, except for a few outliers. This means that there is poverty in a lot of New York, including major urban areas. Triumph of the City discusses trends that explain why some of the urban areas have high poverty levels: “Cities aren't full of poor people because cities make people poor, but because cities attract poor people with the prospect of improving their lot in life” (Glaeser 70). Thriving urban areas attract the rural poor, who tend to improve their fortunes and move up the socioeconomic ladder, however, they don't always rise above poverty. The great urban poverty paradox is that if a city improves life for poor people who are currently living there by way of improving public schools or mass transit, that city will attract more poor people and, in turn, the place will likely remain poor. This is a trend that is evident within the data that was given to us and illustrated through the visualizations.

The map visualization shows this trend of high poverty levels in a few big urban areas in New York, such as New York City. This city is very successful and attracts a lot of rural poor due to the economic opportunities it presents. In urban areas, the opportunity lies in people being able to sell their own labor to an employer who has capital in hopes of getting a job and making money (Glaeser). In the map, Long Island in particular is light blue for most of the geographical area, which illustrates low poverty levels, but in the most centralized, urban part of it, New York City, the color is dark blue, which correlates to high poverty levels. This agrees with the data we have been reading: the poor go to urban places in hopes of success, and the cities offer attractive qualities. In Kahn’s Unlocking the Potential of Post-Industrial Cities, he discusses the trends that new cities offer that draw in large populations. “Strong consumer city fundamentals” are things such as good restaurants, cultural amenities, beautiful architecture, and other enticing factors that a city has to offer its residents (Kahn). New York City is one of the six cities that Kahn talks about throughout the chapter, and it has all of the positive trends that make it an enticing city. The trends he discusses that New York City offers are things such as talent retention and attraction, where they focus on quality of life, and this maintains its competitive edge in a knowledge-based economy. They also concentrate their efforts on urban regeneration, repurposing old industrial sites into vibrant spaces for business, as well as sustainability and green initiatives. The visualizations show the effect that these trends can have by illustrating the high poverty in urban areas, which allows us to conclude the data that many people are being enticed into the city, even making a low income, and without college degrees.

The relationship between urbanicity, income, and education has been shown in the visualizations and is explained through our class discussions and readings. Between the scatterplot and the map, there are a lot of urban places that have high poverty levels, which was explained above, but there is also a large quantity of poverty in the rural areas. This makes sense because rural areas have limited access to markets, education, quality infrastructure, and employment opportunities. In class, we learned about why firms cluster in cities: to have access to resources more readily available, as well as to exploit external economies of scale in production, which occur when the activity of one firm decreases the production costs of nearby firms. Geographical isolation, therefore, is also a big factor in why rural areas are poorer. Urban areas become more productive when they work with other skilled people (Glaeser). The scatter plot shows this concept, with the smaller dots (rural) corresponding to smaller counties, that these smaller counties all had median incomes below the median income and had no college degrees. Glaeser tells us that human capital is why areas succeed, and when an area is educated, everyone benefits. Therefore, it makes sense that in small rural areas where there aren’t high populations of people or educated people, the areas are poor. The two visualizations, the scatterplot and the filled-in map, were able to illustrate all of these findings and data to help make a better picture of the concepts and show how they relate to real-world cities and areas.

Cairo, A. (2020). How charts lie: Getting smarter about visual information. W.W. Norton & Company. 

Glaeser, E. L. (2012). Triumph of the city: How our greatest invention makes us richer, smarter, Greener, healthier, and happier. Penguin Books. 

Kahn, M. E., & McComas, M. (2021). Unlocking the economic potential of post-industrial cities. Johns Hopkins University Press. 

U.S. Census Bureau quickfacts: United States. (n.d.-c). https://www.census.gov/quickfacts/fact/table/ 

USDA. (2021). Atlas of rural and small-town America - documentation. Atlas of Rural and Small-Town America - Documentation | Economic Research Service. (n.d.). https://www.ers.usda.gov/data-products/atlas-of-rural-and-small-town-america/documentation