# Chicago Crime Visualization Analysis
## Introduction
### Chicago, City of Wonder and Crime
Chicago, one of the greatest city in the U.S, located in northeastern Illinois on the southwestern shores of freshwater Lake Michigan. With a population of 2,746,388 in the 2020 census, it is also the most populous city in the Midwestern United States and the fifth most populous city in North America. However, due to various factors, for decades, this city is bothered by non-negligible high crime rate, which puts it into the array of most unsafe U.S cities.
Chicago had a murder rate of 18.5 per 100,000 residents in 2012, ranking 16th among US cities with 100,000 people or more, higher than in New York City and Los Angeles. Violent crime rates vary significantly by area of the city, with more economically developed areas having low rates, but other sections have much higher rates of crime. In 2013, the violent crime rate was 910 per 100,000 people;the murder rate was 10.4, while high crime districts saw 38.9, low crime districts saw 2.5 murders per 100,000.
In 2012, Chicago ranked 21st in the United States in numbers of homicides per person, and in the first half of 2013 there was a significant drop per-person, in all categories of violent crime, including homicide. As of 2021, Chicago has become the American city with the highest number of carjackings. Chicago began experiencing a massive surge in carjackings after 2019, and at least 1,415 such crimes took place in the city in 2020.
Statistics Sourced From Chicago-Wikipedia
### Innocent People are Victims
On November 9, 2021, Shaoxiong Zheng, a 24-year-old graduate at the University of Chicago, was robbed and fatally shot by a 19-year-old Chicago resident on the sidewalk near Chicago University. The victim is the second international student from China to be killed in Chicago in 2021. After murdering this young student, the murder kept fleeing across the city and assaulted other 6 people randomly, causing extra 2 deaths and 3 wounded.
The death of Zheng caused great concern across international students, Chicago University. However, he is just one of the thousands of victims suffered from violent crimes in Chicago. There are hundreds of violent crimes happening daily in Chicago.
### We Want to Help Using Data Science!
If we could portray crime patterns in Chicago, for instance, the dynamic danger level of blocks over time, it might help protect Chicago residents from crimes. To address this challenge, this project proposes building data visualizations that allow Chicago residents, to visually explore Chicago crime data in the past 5 years. The visualizations will show the geographical distribution of crimes over time dynamically and allow citizens to explore crime distribution within one day by radar graph. The Chicago PD might also benefit from the network graph of crime descriptions and crime types analysis of this project by allocating more resources to high-frequency crime types.
## Data Source
## Time-related Analysis
## Geo-related Analysis
## Sub-types Analysis
## Conclusion
6.1 Describe how your project has developed from your initial proposal, through your first submission, to your final product. How have your visualization goals changed?
As a data visualization project, the goal is always to tell a clear and logical story with meaningful, interpretable and fascinating plots. The topic of this program is about the severe situation of crimes in Chicago, so the story revolves around the type, time and geography related patterns of Chicago crimes.
Initially, the objective was to protect the citizens in Chicago from crimes, hence, more emphasis was put on time basis and geographic basis evidences. With the development of the whole program, more features were recognized that some specific types of crime have a higher rate of arrest and different types of crime are inclined to happen in different time periods of a day. Therefore, more visualizations and analysis have been made about crime types.
Accordingly, a complete story was presented in the final website along with many fruitful conclusions for the citizens and even the police department.
6.2 How have your technical goals changed?
It is universally acknowledged that data visualization plays an irreplaceable role in the whole data analysis ecosystem, so more and more tools and methods of visualizations are developed.
Originally, static plots played as a main character in the project, but after diving deeper into the world of data visualizations, more interactive plots were added into the website. In final version, all the plots were created in an interactive way, using tools including plotly, altair and D3. And techniques including panning, zooming, brushing, selectors, etc. were utilized to draw attention to particular items of interest and provide additional context.
6.3 How realistic was your original proposal in terms of what is technically possible in D3?
Generally, all of the plots displayed in the project were in an interactive way. As is known to us all, most of these interactive plot tools are built on the basis of D3, including plotly and altair, in that it allows you to bind arbitrary data to a Document Object Model, and then apply data-driven transformations to the document.
D3 is not a monolithic framework that seeks to provide every conceivable feature. Instead, it solves the crux of the problem: efficient manipulation of documents based on data. This avoids proprietary representation and affords extraordinary flexibility, exposing the full capabilities of web standards such as HTML, SVG, and CSS. All of these techniques used here like selector, dynamic properties, etc. are all achievable in D3.
6.4 Was there anything you wanted to implement that you ultimately couldn't figure out how to do? If so, then what workarounds did you employ, or did you abandon your original idea?
6.5 If you were to make the project again from scratch (or any other interactive visualization), what would you do differently?
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