Analysis of Young Adult Male Inmates in NYC Jails

Charts & Graphs, Lab Reports


Young adults aged 18 to 24 comprise 10 percent of the United States population but are 21 percent of the prison population; additionally, among this population, young men of color are represented 7 to 9 times more than white young adults (Frank, 2017). Incarceration is an incredibly traumatizing experience that has known impacts on the psychopathology of individuals who have been through the prison system (Lovell et al., 2020). Young people are the future, and it is important to analyze the demographics of current prison populations to draw conclusions surrounding systemic racism and classism.

Research Questions:

1. What are the demographic patterns in NYC prisons?

2. What is the distribution of custody level (security level) among inmates, and is there a pattern of age/race?

Dataset / R

I acquired my dataset from the NYC OpenData tool, specifically the Daily Inmates in Custody dataset, which describes important demographics and attributes such as security risk group and top charge. I utilized several attributes from the Daily Inmates in Custody dataset, such as age, race, security risk group, and gender. I then loaded the dataset into R, a software specializing in data analysis and statistical computations. I used R to render visualizations using the dataset I acquired from NYC OpenData.


I first explored the data by examining the data frame’s dimensions, structure, and categories.

Data Exploration

I then cleaned the data by recoding variables, changing data types to factors rather than characters for easy analysis, and then dropping NULL values. I then selected the specific categories of data to prepare for analysis.

Data Cleaning

I finished my analysis by creating a boxplot data visualization and a lollipop plot.

Data Visualization


What are the demographic patterns in NYC prisons?

I created this Lollipop plot to visualize the occurrences of daily inmates by age and race, and we can see that Black Men (“B”) and Hispanic Men (“O”) have the most data occurrences out of all other races, and have the widest distribution over age. Additionally, we can see that young Black Men are disproportionately represented in the under-20 attribute.

Lollipop Plot of Age and Race in NYC Jails

What is the distribution of custody level (security level) among inmates, and is there a pattern of age/race?

I created this boxplot to represent the distribution of Male inmates over varying security risk levels. We can see from the boxplot that those held in Maximum security are the youngest out of all other security risk levels. Knowing that young Black Men are disproportionately represented, we can use this data visualization to add more context using the security level attribute.

Boxplot of Age and Custody Level (Security Risk Level)

Conclusion / Reflection

Based upon the two visualizations that represent the relationship between race/age and security risk level, we can determine that the age distribution in maximum security risk level holding lean towards younger adults; based upon the Lollipop plot, we can see that younger Black and Hispanic men (Ages 18-24) have more occurrences.

Adults aged 18-24 make up a quarter of arrests in NYS (New York State) despite only comprising 10% of the total population in NYS; additionally, arrests in NYS disproportionately occur to young Black and Hispanic men (over 70% of total arrests) (Fitzgerald, 2020). Essentially, Black and brown young adults are overrepresented in the incarcerated population in New York. There needs to be an overhaul in how the legal system disproportionately impacts young adults in New York City.


Using R was a learning experience, as I have only used it a handful of times. I had a hard time getting the graphs to visualize properly, but I was able to make it work in the end to a certain extent. I wish I had more numerical variables so that I was able to make more robust visualizations, but the dataset I used was not descriptive in many numerical categories. I can tell from completing this lab that learning R will take a lot of experience. Otherwise, learning to do more advanced visualizations was rewarding and fun.

I am very interested in incarceration data, especially in New York City, so this project opened up many ideas for future ventures.


David Lovell, R. Tublitz, K. Reiter, K. Chesnut & N. Pifer (2020) Opening the Black Box of Solitary Confinement Through Researcher–Practitioner Collaboration: A Longitudinal Analysis of Prisoner and Solitary Populations in Washington state, 2002–2017, Justice Quarterly, 37:7, 1303-1321, DOI: 10.1080/07418825.2020.1853800

(DOC), D. of C. (2023, March 21). Daily inmates in custody: NYC open data. Daily Inmates In Custody | NYC Open Data. Retrieved March 21, 2023, from

Fitzgerald, M. (2020, October 16). Justice Reformers in New York look to help 18- to 25-year-olds. The Imprint. Retrieved March 21, 2023, from

Frank, A. (n.d.). Why reimagining prison for young adults matters. Vera Institute of Justice. Retrieved March 21, 2023, from