Requirements (Please Read Carefully):

  1. Submit a knitted RPub link or pdf file along with an .rmd file.

  2. Organize your report clearly by tasks, questions using different level of headers. Please refer to the example uploaded to Canvas for the last lab homework.

  3. For each question, include the question itself, the code/result/graph to answer the question, and your answer in plain language.

  4. You need to polish your graph details to reasonable visual comfort.

  5. You are not allowed to use AI in any means.


1. who data set in the tidyr package

  1. Read the lecture notebook that tidies the who data set, understand all steps needed, then reproduce the whole tidying steps by yourself without referring to my notebook.

  2. Using the tidied data, explore one question of your interest and answer it with visualization or summary table.


2. Tidy and visualize the US_average_tuition data set (attached on Canvas)

This data set is the average 4-year college tuition for each states in the US over year.

  1. Tidy the data following what we learned in class.

  2. Make an informative visualization of the data to show the average tuition across all years in the data set for each state. Which state has the highest tuition? Which state has the lowest?

  3. Make an informative visualization of the data to show the increasing rate of average tuition from 2004-2005 to 2015-2016 in each state. Which state’s tuition increased at the fastest rate? Which one the slowest?


3. Analyze flights and weather data sets in nycflights13 (relational data)

Study the class examples in relational data, explore the flights and weather data set to fulfill the given task or answer the given questions:

  1. Finish the lab exercise - Create a airport map with each airport location marked on the map and colored by the number of flights per day from NYC to each airport.

  2. What weather conditions make it more likely to see a departure delay? hot or cold weather? windy weather? rainy or snowy? foggy? Create a proper data frame and use proper visualization or summary table to answer the question.

  3. Display the spatial pattern of arrival delays on June 13, 2013 using a map, and then use Google to cross-reference with the weather. Explain how the weather condition might have affected the spatial pattern of arrival delays.