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In this assignment, you will create a short data-driven article. In other words, you will create a report by interleaving short text segments and carefully designed visualizations as a cohesive story to communicate insights you found from analyzing a data set. You will start by analyzing the data set to find interesting insights to communicate, and then curate a selection of visualizations and combine them in a document that resembles a data-driven article.
See examples of data-driven articles:
What Happened to America’s Political Center of Gravity?Links to an external site. (New York Times)
How Music is RememberedLinks to an external site. (The Pudding)
Nike Says Its $250 Running Shoes Will Make You Run Much Faster. What if That’s Actually True?Links to an external site. (New York Times)
Brooklyn Greenway Case Study: Pedestrian and Bicycle Activity in Public SpacesLinks to an external site. (Numina)

BACKGROUND STORY
Every year, many cyclists report to the Toronto Police Service that their bike has been stolen. The Cycle Toronto AssociationLinks to an external site. would like to publish a data-driven article to provide the community with information regarding bicycle thefts in the city. The association hopes that this article can help inform the general cyclist community on personal decisions such as bike purchase, risk assessment, and more.

The Toronto Police Service keeps a record of crimes committed in the city on the Public Safety Data PortalLinks to an external site.. Among those is the Bicycle Thefts datasetLinks to an external site., which members of the Cycle Toronto Association hope will help them uncover patterns of bicycle thefts in the city. They also wish to uncover information on how bicycle thefts impacted different people, if and how bicycle thefts changed over time, and bike features and risk factors potentially associated to bike theft. You can consult different interactive visualization dashboards that the Toronto Police Service has already created on the Public Safety Data Portal.

DATA
You are provided with over 20,000 records from the Toronto Police Service Public Safety Data Portal as a csv file:"Bicycle_Thefts_Open_Data.csv Download Bicycle_Thefts_Open_Data.csv".
Additionally, you can also access the documentation Download documentationfor this data set, as well as the Bike Data Code Sheet Download Bike Data Code Sheetfrom the portalLinks to an external site.. These definitions will clarify the meaning of each data field.

ASSIGNMENT
1.Explore this data set with R and identify useful information about bicycle thefts in Toronto. Your task is to surprise the Toronto Cycle association with your discoveries!
2.Create a document in R Markdown, crafting a story of what you found and describing your findings through charts computationally generated with R. The story should be at least 1,000 words long and include at least 4 separate charts.

Data Analysis vs. Presentation
As you identify insights to report, think about the difference and relationship between data analysis and presentation. What are the most important goals in analysis? And what are the most important ones in presentation?
Note that not all charts you explore in R during your analysis will necessarily have to be in your final document. Analysis often leads you to some dead ends. Select only those charts that together tell a coherent story about your findings.

How to Write the Story
a. Come up with a meaningful title for your data-driven article. Include both author names below the title.
b. Write a short introduction explaining what the goal of your analysis is.
c. Structure the document as a sequence of visual content (images / visualizations) and text, visual content and text, visual content and text, etc.
d. Structure the document so that clear sections, with meaningful, informative section headers help the reader navigate your story.
e. For each visualization, consider including:
i) What question the visualization addresses;
ii) What the reader should see in the chart that is useful/interesting for the understanding the story;
iii) How its analysis leads to a new question and the visualization that follows.
f. Write a final section in which you summarize your main findings, and actionable insights in a few sentences.