Developing Intimacy With Your Data Subject: Police Killings ✓ Solved

DEVELOPING INTIMACY WITH YOUR DATA SUBJECT: Police Killings

This exercise involves you working with an already acquired dataset to undertake the remaining three key steps of examining, transforming and exploring your data to develop a deep familiarisation with its properties and qualities. This spreadsheet provides you with two contrasting worksheets showing snapshot details of recorded deaths caused by US law enforcement agencies, from The Guardian (“The Counted”) and the Washington Post (“Fatal Force”). For each dataset:

Examination: Articulate the meaning of the data (its representativeness and phenomenon) and thoroughly examine the physical properties (type, size, condition) noting down your descriptions in each case. Compare what the two datasets offer and contrast their differences.

Transformation: What could you do/would you need to do to clean or modify the existing data? What other data could you imagine would be valuable to consolidate the existing data?

Exploration: Use a tool of your choice (common recommendations would be Excel, Tableau, R) to visually explore the two datasets separately in order to deepen your appreciation of their physical properties and their discoverable qualities (insights) to help you cement your understanding of their respective value.

ALTERNATIVE SUBJECT: Olympic Medallists. You can, of course, repeat this exercise on any subject of your choice but here is an additional dataset about some contrasting Olympic medallist data.

Paper For Above Instructions

Analyzing data related to police killings is a critical step in understanding the complexities surrounding law enforcement and its impacts on communities. This paper focuses on two datasets provided by The Guardian and The Washington Post, which document deaths caused by US law enforcement agencies. The objective is to examine, transform, and explore the data to gain deeper insights.

Examination of the Datasets

The datasets chosen for examination reflect the representativeness and phenomenon of police killings in the United States. The Guardian’s “The Counted” and The Washington Post’s “Fatal Force” provide differing perspectives on the same issue, which can lead to valuable comparisons.

The Guardian's “The Counted” offers an interactive database that tracks police-related fatalities, highlighting the identities of victims, circumstances of their deaths, and demographic information. In contrast, The Washington Post’s “Fatal Force” focuses on unarmed shootings and aggregates data that includes both fatal and non-fatal incidents.

In terms of physical properties, The Guardian dataset tends to be more comprehensive, encompassing a variety of data types such as text, categorical, and numerical. On the other hand, the Washington Post dataset often comprises numerical data primarily focused on fatal incidents. Furthermore, the size of The Guardian's dataset is extensive, recording nearly 1,000 incidents over the course of a year, while the Washington Post typically publishes figures that focus on yearly summaries, which can vary from 600 to 800 cases annually. The condition of both datasets appears reliable, although the Guardian may provide more consistent updates as it is an ongoing project, while the Post data may experience lag in updates.

Comparative Analysis

Comparing the two datasets reveals significant differences. For instance, while both datasets aim to document police killings, differences in their methodologies influence the breadth of their findings. The Guardian accounts for all police-related fatalities, while The Washington Post emphasizes on-duty fatalities from police officers, revealing discrepancies in reporting standards.

Moreover, while both datasets collect demographic information, The Guardian may provide a more qualitative insight by including narratives or details surrounding specific incidents, whereas The Washington Post is more quantitative, focusing on clear statistics regarding the number of incidents in specific demographics over time.

Transformation of the Data

In cleaning and modifying the existing data, it is essential to identify gaps or inconsistencies within the datasets. For example, some entries may be missing demographic information or lack context about the incidents. For The Guardian dataset, a potential transformation could include merging similar categories, such as the classification of incidents (e.g., justified vs. unjustified shootings), to enable better analytical comparisons.

Additionally, integrating external datasets – such as socioeconomic factors of the communities where these incidents occurred – might provide context to the analysis and enhance the understanding of trends in police killings. For instance, augmenting data with information from the Bureau of Justice Statistics on crime rates, poverty levels, and community demographics could yield deeper insights.

Exploratory Data Analysis

Using software such as R, Tableau, or even Excel, one can conduct a robust exploratory data analysis (EDA) on both datasets. EDA allows for visualizations that highlight patterns or anomalies within the data. For instance, visualizing the number of fatalities by race, gender, and age using bar graphs or histograms can reveal troubling trends or disparities. Furthermore, creating scatter plots to correlate community demographics with the frequency of police killings can provide insights into the social fabric surrounding these incidents.

Another useful technique could be time series analysis to observe changes in police killings over the years or to assess spikes in fatal police shootings during specific social movements. Utilizing visualizations effectively presents the comparative data from both sources, while also solidifying one’s understanding of the strengths and limitations inherent in each dataset.

Conclusion

Ultimately, this exercise of developing intimacy with data through examination, transformation, and exploration is vital for forming a comprehensive understanding of the datasets related to police killings. By engaging deeply with the data, contrasting findings from The Guardian and The Washington Post, making necessary transformations, and visually exploring the datasets, a nuanced knowledge about the nature of police violence and its implications emerges.

References

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