what percentage of all suspects got arrested Be careful for some suspects there are more than 1 categories

INSTRUCTIONS TO CANDIDATES

ANSWER ALL QUESTIONS

1. Explore the following variables and write a short paragraph of what they mean and how they are connect to each other: participant_age, participant_gender,participant_type, and participant_status. Do you see any technical difficulties for how these variables are coded? If so, explain them.

2. What is the average of suspects and victims per incident?

3. Create a new data frame with just the suspects include the following variables:incident_id, participant_age, participant_gender. Just print the head() of this new data frame. (Hints: 1.Google what the function unnest does, is part of tidyr library, 2.review the tidy and joins materials)

4. Show the distribution of suspects age, crop your plot if you find any suspect over the age of 100

5. What percentage of suspects are male (exclude missing values)?

6. How many different status are there?

7. What percentage of all suspects got arrested? Be careful for some suspects there are more than 1 categories.5 Geographic variation (15 points) 1. What was the state with more incidents in 2017? Use a graph to answer this question. 2. Use your census API to get population by state, remember to also download the geometry we will use it later. Re-do your previous plot but adjusting by population, i.e incidents by a 100,000 inhabitants. 3. Show the results from your previous plot in a map 6 Mass shootings (20 points) 1. Create a new data frame of mass shootings. 2. Show the top 15 incidents by number of victims in a map as points. The points should be proportional to the number of victims. Follow the map slides to make the map. Here are the coordinates that will give you the continental US out of the world map. Extra credit if you add state lines and change the theme of the map.

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