Anita Xin Chen, circularsquare.github.io
Throughout the semester, we will focus on transit-oriented development in New York City. In particular, we will analyze and visualize data for the neighborhoods adjacent to subway stations. The above image shows the number of people who live in the catchment area of each subway stop. The catchment areas are colored by the subway line (e.g. the IND 8th Avenue Express lines (A/C/E) are colored blue) and the size of the dot reflects the number of residents for whom that stop is the closest.
To begin, pick a subway line (i.e. choose one and sign up on Blackboard). Note that we have split the longer lines into pieces. Each subway line has an associated terminal stop. Create a single page summary of the neighborhood around the terminal that includes:
Upload a .pdf to the assignment HC 1 in the honors section of Gradescope.
Note: Unlike the Python code, it is not automatically graded.
Urban planner, Jeff Speck, argues that if a city succeeds at being walkable (and by extension, bikeable), it excels at having a high quality of life (see his TED talk).
What fraction of the neighborhoods along your subway line are walkable?
For each of the chosen neighborhoods:
Does your ranking concur with ranking the neighborhoods by walkability? Justify your answer.
Submit a .pdf file analyzing the your rankings and walkability of five neighborhoods chosen for the class. You should use complete sentences and justify your answers with data.
FiveThirtyEight analyzed the cost of commuting in terms of the extra New Yorkers were willing to pay to lessen their commute. StreetEasy did a similar analysis, measuring from given subway stops.
How does distance affect housing prices? To narrow down the analysis, we will focus on the distance to two landmarks: Empire State Building (as a proxy for midtown) and Federal Hall (for the financial district) and 3 locations. You may find WNYC Transit Time or Google Maps useful, as well as CityMapper. Pick, at random, a rentals in each of your terminal neighborhood, your least walkable neighborhood, and your most walkable neighborhood (if those coincide, choose another neighborhood, so you have a total of three neighborhoods). Make sure that your three rentals are comparable. That is, all have same number of bedrooms, same number of bathrooms, and similar features:
Using the analysis from FiveThirtyEight, analyze what the difference in rental prices should be. Is that difference reflected in the data you collected? Justify your answer.
Submit a .pdf file analyzing the time and cost of commuting of your neighborhoods. You should use complete sentences and justify your answers with data.
In Lectures 3 and 4, we introduced colors, specified by hex codes. Use matplotlib and numpy and hexcodes above, create a logo for your subway line.
Submit your Python code and .pdf file including your image to Gradescope.