Group 9: District 7
Claudia L., Emmett B., & Teng L.
image extracted from BU Today
image extracted from BU Today
To accomplish this goal, the project utilized Analyze Boston, a platform that provides comprehensive data on various neighborhood demographics, including poverty rates, per capita income, labor force, school enrollment, age distribution, and race. Specifically, the project focused on analyzing the subsets of poverty rates and per capita income.
Using the collected data, the project team plans to create a series of comparative analytic visualizations that will help to identify key areas of need in Roxbury and highlight opportunities for targeted interventions. The hope is that these visualizations will not only raise awareness about the revitalization efforts in Roxbury but also encourage stakeholders to take action towards supporting the community's revival process.
The data collected for this project is diverse and includes both quantitative and qualitative data types. This means that we were able to gain a comprehensive understanding of the challenges faced by the community of Roxbury.
The quantitative data in the dataset includes columns such as per capita income, poverty rate, and demographic population numbers, which provide a numerical representation of the economic and social conditions of the area. The qualitative data, such as the 311 call type column, provides insight into the specific issues and concerns of the residents.
Fortunately, the data collected was relatively clean and required minimal cleaning, limited to some index manipulation. This means that we were able to focus on analyzing the data rather than spending a significant amount of time cleaning and preparing it.
Overall, the data dictionary provides a clear understanding of the dataset's columns and their respective data types. By utilizing this information, we were able to create a detailed picture of the circumstances faced by the community of Roxbury, which will help to inform future initiatives and support efforts towards revitalization.
The first analytic task involves comparing the per capita income of different demographic groups. This requires a comparative analysis to identify patterns and differences in the data. In addition, a search task is needed to find relevant data sources to gather the necessary information. Finally, the analyze task involves presenting the findings in a clear and understandable way.
The second analytic task involves comparing different poverty metrics between Roxbury and other neighborhoods. This requires a comparative analysis to identify similarities and differences in the data. A search task is also needed to find relevant data sources to gather the necessary information. Finally, the analyze task involves presenting the findings in a clear and understandable way.
The third analytic task involves analyzing the frequency of 311 calls across various neighborhoods. This requires a comparative analysis to identify trends and patterns in the data. A search task is needed to find relevant data sources to gather the necessary information. Finally, the analyze task involves presenting the findings in a clear and understandable way.
In all three tasks, the analytic task involves performing a comparative analysis to identify patterns, similarities, and differences in the data. The search task involves looking up relevant data sources to gather the necessary information, and the analyze task involves presenting the findings in a clear and understandable way. These tasks highlight the importance of performing thorough analyses to gain insights and understanding from data, and the need for clear communication of the findings to ensure their usefulness and impact.
| Domain Task | Analytic Task | Search Task | Analyze Task |
|---|---|---|---|
| Compare the per capita income of different demographic groups. | Comparative Analysis | Lookup | Present |
| Compare different poverty metrics between Roxbury and other neighborhoods. | Comparative Analysis | Lookup | Present |
| Analyze the frequency of 311 calls across various neighborhoods. | Comparative Analysis | Lookup | Present |
The data analysis conducted reveals that Roxbury is facing significant economic challenges compared to other neighborhoods in Boston. The high poverty rate and lower per capita income in Roxbury indicate that many individuals and families in this neighborhood are experiencing financial difficulties and struggling to make ends meet. This situation can lead to a range of negative consequences, including limited access to healthcare, education, healthy food, and other basic needs that are essential for well-being and a decent quality of life.
Furthermore, poverty and income disparities can negatively impact the community's economic growth and development. A high poverty rate can result in reduced spending power, lower tax revenue, and limited investment in the local economy, making it challenging for businesses to thrive in the area. This, in turn, can lead to fewer job opportunities and hinder economic growth.
Given the severity of the economic challenges in Roxbury, there is a pressing need for targeted interventions and support to address poverty and income disparities. This can involve initiatives such as providing job training and employment opportunities, improving access to affordable housing, healthcare, and education, and increasing investment in the local economy. By addressing these challenges, Roxbury can achieve more equitable economic growth, improve the well-being of its residents, and contribute to a more prosperous future for the community as a whole.
In order to support the revitalization efforts in District 7 and increase its exposure, we are planning to create three primary visualizations. Our aim is to contribute to these efforts by providing insightful and informative data visualizations. Our first proposed visualization is a Sankey diagram, which will depict the relationship between racial demographics and average per capita income for each neighborhood in Boston, using Plotly.
Our second visualization will consist of a series of small multiple bar charts created using Altair. These bar charts will represent the frequency and types of specific 311 requests made in different districts of Boston. This visualization will provide a clear and comprehensive overview of the nature of requests made, thereby enabling better decision-making and resource allocation.
Our final visualization will be a simple and straightforward grouped bar chart that will display the poverty rates in each neighborhood. This visualization, created using Plotly, will enable the audience to easily identify and compare poverty rates across neighborhoods, allowing for more informed discussions and policy decisions. Overall, these visualizations aim to contribute to the revitalization process in District 7 and enhance understanding of key socioeconomic factors across Boston neighborhoods.
First Visualization
The Sankey diagram we have created visualizes the relationship between income, neighborhood, and demographics. By mapping income to neighborhood to demographic, the diagram demonstrates how certain neighborhoods and demographics are marginalized. We chose to use a Sankey diagram because it effectively encodes multiple variables related to the same inner variable, without requiring a confusing dual axis. This type of visualization also allows for easy comparisons within a group, as it utilizes the length of the bars for each node. Additionally, the Sankey diagram permits straightforward filtering of a specific neighborhood, which is useful in our specific domain for users to focus on Roxbury's data. Overall, the Sankey diagram is a highly visual way of showcasing the disparities within neighborhoods and their demographics, highlighting the need for focused intervention to address these issues.
Second Visualization
The primary objective of this small multiple chart is to provide a more comprehensive understanding of the challenges facing communities, which may not be captured by traditional surveys. The chart will focus on issues such as needle pickup, pests, safety concerns in residential areas, and utility-related concerns. These metrics can provide insights into the overall health of a community, which may not be measured in larger-scale surveys, such as the census. Moreover, the chart enables us to compare the metrics of other districts to those of District 7, our area of interest, facilitating better decision-making and targeted interventions. By using this small multiple chart, we aim to capture a more nuanced understanding of the challenges facing communities and identify areas where focused efforts are needed to improve the well-being of residents.
311 is a non-emergency phone number that people can call in many cities to find information about services, make complaints, or report problems like graffiti or road damage. Even in cities where a different phone number is used, 311 is the generally recognized moniker for non-emergency phone systems.
Third Visualization
The third visualization is a combined grouped bar chart and line chart, aimed at providing insights into the poverty distribution and how poverty is distributed across different age groups in Boston neighborhoods. The grouped bar chart displays the poverty rate for each neighborhood and includes an additional bar that shows the percentage of individuals living in poverty in Boston as a whole, facilitating easy comparisons between the poverty rates of individual neighborhoods and the citywide average. The line chart provides a breakdown of the poverty distribution within each neighborhood across six age groups, allowing for a more nuanced understanding of the economic challenges faced by different segments of the population in each neighborhood. By identifying age groups that are particularly vulnerable to poverty in each neighborhood and evaluating how poverty rates vary across different age groups in different neighborhoods, we can gain insights into the factors that contribute to poverty and inform targeted interventions to address these challenges. Overall, this visualization provides a clear and informative representation of poverty rates and poverty distribution across different age groups in Boston neighborhoods.
From the sankey, it can be seen that Roxbury compared to every other neighborhood is in the lowest income bracket and the highest proportion of minority demographics. The sankey diagram illustrates the intersectionality between race and income among all the neighborhoods in Boston, but especially District 7 in which the racial makeup has an unfortunate relationship of income and equality. The 311 data shows Roxbury is the second most affected community on health-related issues such as needle pickup and residential issues. The only neighborhood that shows greater need then Roxbury is district 2, a much more densely populated area that receives more calls than those of fewer residents. Roxbury has many fewer tenants than district 2, yet performs equal, if not higher, in metrics of drug use and health-related parameters. Lastly, our third visualization reveals that Roxbury has a poverty rate that is relatively high compared to other neighborhoods, ranking third in overall poverty rate and second in percentage of Boston's total poverty. Additionally, the age distribution of poverty in Roxbury shows that the majority of those living in poverty are either 0 to 4 years old, 5 to 17 years old, or 65 years old and above. It is worth noting that most of Roxbury's poverty are vulnerability aged populations.