17. Student ideas

Project 1: Washington Post police shootings data

Flintoff Arul Daniel Roby: Could climate be one of the reasons which made them more prone to violence? Because as you may know that hotter climate does make people prone to more violence. So maybe I think I need to find out if hotter regions have more fatality count than cooler regions.

I had come up with a second question…

I would like to learn about gun laws across different counties and states. For example, what is the age requirement to own a gun in a particular state? Is open carry legal there? How about Permits and background checks? Are gun laws stricter in some states and more lenient in others?

If some states have more lenient laws, that could mean more people running around with guns, potentially leading to an increase in police shootings, right? To analyze this, I would need to categorize states into two groups: strict and lenient. By comparing these groups, I could find out whether stricter gun laws correlate with lower violence and fewer shootings.

But, how should I define “strict” versus “lenient” gun laws? What criteria should I use to make this distinction?

Ryan Berry:

My primary direction at the moment is to utilize the state attribute and outside data referencing each state’s population.

I’ve been focusing on locational statistics. Using the longitude and latitude, I plotted each data point on a US map. I am also making a heatmap by county and state since that will be easier for me to read than my current plot.

I’ve found an external dataset containing educational data for each county in the US. This information may correlate to some of the features of the victims such as race or mental disability status. I also found Hugo’s idea of political affiliation to be very interesting and want to see if red states or states with concealed carry laws have a higher rate of police shootings involving victims armed with some kind of firearm.

Hugo Mosso:

Which day/month/year had the most casualties?
Which age group had the most casualties?
How does the age distribution of female casualties differ from the male ones?
How many of the victims were armed/unarmed?
Which race had the most casualties?
Which city/state had the most casualties?
How many fled the scene? How did they flee?
How many victims presented signs of mental illnesses?
Which police department had the most casualties?
It is worth noting that some columns contain null values which could potentially disrupt the data analysis process and other machine learning techniques.
What percentage of cops had their body cameras off?
Is there a pattern between the casualty rates and factors such as race, gender, mental health status of the victims?
I’ve noticed that whenever a casualty was deemed mental illness-related, most of the time, the police officers also had their body cameras off. Is there a correlation?
Depending on the state and the police station, some cops can turn their body cameras off in certain instances. Are they taking advantage of this law’s flexibility? If they claim the person they shot had a mental illness, we have no choice but to believe them, considering there’s no body cam footage to prove them otherwise.
Based on the data provided, is it possible to determine if blue states/counties are more violent than red ones, as some people claim?

Chibuike Odibeli:

I chose to investigate what state had the most frequent shootings and found that it was California. There are further questions this poses, like :

a.) What race of people were most frequently shot by police in California?

b.) What police department in California was involved in the most shootings?

c.) What percentage of people shot by police departments in California were armed?

Black men with mental illness have been historically mistreated in the United States and I have been investigating if there is any evidence of that in the dataset. To do this I am checking if black men with mental illness are being disproportionately represented in the dataset, when compared with the total population of the United States.

I am also looking at the “threat_type” variable compared with the “armed_with” variable. If a person is threatening a policeman by pointing at them, but they are only armed with a blunt weapon, that is not a valid reason to use lethal force and if this happens repeatedly, then it is a problem that should be recorded/reported.

Syed Ahsan:

Questions:
1. It is observed that States like California, Texas, and New York which are high in Population size and Economic disparities encountered higher Crime rates this might be due to population size, urban crime, gang activity, gun policies, and policing issues.

2. It is also seen the States with fewer Counties encountered more Shootings, this might be due to Political and Social Factors. States like California & New York have bail reform and early release programs, which some argue lead to more repeat offenders.

Chandrakanth:

Few questions that I have in my mind based on the analysis are:

– This focuses on whether body cameras affect the legal or public consequences for officers involved in shootings.

What are the most common circumstances leading to fatal police shootings?

– For example, were the shootings tied to a specific crime, resisting arrest or mental illness issues?

How do fatal police shootings vary by urban vs. rural areas?

– Are there more shootings in densely populated urban areas or in rural areas with smaller police departments?

Sai Gomatham:

I explored the dataset and came across the following questions while trying to understand it better:

Which state had the highest number of shootings, and which had the least?
Which age group was most targeted?
Which race was most targeted, and which was least targeted?
What is the male-to-female ratio in fatal police shootings?
Are there specific months or years where incidents peak?

In the coming week, I plan to delve deeper into the dataset, discuss insights with my teammate, and gain a better understanding.

Nina Herrera & Lavanya Murugesan:

We organized the data by gender and immediately noticed that out of the 10,389 shootings only 4.4% of those were women. In class we made other observations such as how there was missing data and that it seemed like TX and CA had the most data. We also asked ourselves how old was the youngest victims were amongst the women and male victims. This past week while reviewing the data alone I noticed that out of the 10,389 shootings only 1,792 were recorded by police body cameras. With a quick custom short I was able to notice that none of those shootings recorded via body cams were associated with women.

This week we really zeroed in on our questions and narrowed down exactly what we wanted to report about. Our questions are:

What is the rate of women killed with mental illness vs men with mental illness?
Is there a time of the year where people are shot more than other times?
Where are the body cameras used more? (which state)
Were there any mentally ill people shot near the locations where body cameras are used?

We decided that we would use python to answer the first two questions and Mathamatica or ArcGIS to answer the bottom two questions.

Ayobami Kolawole:

What is the difference in percentages of shootings of the different races (how are the numbers changing for the races with time in the different regions)
What is the cause for the different killings?
Why were the individuals killed instead of contained, even in situations that may not have been dangerous for the officers.

Mahnoor:

I want to do a comparison of % age of races being shot vs %age of races present in each county of the US.
I want to identify counties where a particular racial group experiences a disproportionate number of shootings despite not being the majority of the population
For this analysis, I need the population by race and year. I have found out a site https://data.census.gov/, that provides data on different topics.

Ahmed Rao:

Why do some people have body cameras on?
What’s the racial composition based off of the zip code and location?
How often is the killings talked about in the news?
How does the data for people with mental illness adds value to this report?

Sri Upadhyayula:

I was analyzing the data, using a bunch of filters, and I noticed that more than 82.75 % of the cops had their body cams off. I also had some questions.

Yashwanth Yerraginnela:

Some of the questions I thought of, are

How has the racial distribution of shooting victims changed over time?
How many people were armed or unarmed in a given state or county, and which state or county had the most armed or unarmed individuals ?
Which state or county has the fewest body cams turned on?
How does the list of shootings in the U.S. compare to that of another country?

Ngoc Dinh:

I have some questions as below:

What was the immigration status of the victims? How many of those shot were illegal immigrants?
Is mental illness related to the temperature of the area?
Do states with stronger mental health crisis response systems such as healthcare, mental health services and mental health funding have fewer fatal police shootings involving individuals with mental illness?

Tai Nguyen:

I engaged in a discussion with my teammate regarding the analysis of the fatal police shootings dataset:

We identified the following research questions for our analysis:

Which agency IDs are associated with the highest number of fatal shooting incidents?
What are the predominant race, age group, and threat type characteristics within these agency IDs that report the most fatal shooting incidents?

We determined that it would be better to list all agencies, ranked by the number of shooting incidents attributed to each agency.

We implemented Python scripts to load the dataset and perform preliminary descriptive analyses. Specifically, we:

Extracted key columns, including state, threat_type, race, and agency_ids.
Assessed the dataset by determining the number of unique values within each column.
Calculated the frequency distribution of values within each column

Sushanth Keerthipati:

Objectives :

1. Which police department has the highest number of shootings, and among those incidents, what is the ratio of Black and White individuals, including minors and those with mental illnesses?

2. I have checked some records which looks uncommon , some victims were shot by the different state police departments . And in some cases the victims are minor . I’m trying to analyze more on this objective.

3 .Which county has the highest number of recorded shootings, and which race, particularly among minors, has been affected the most?