Introduction

Although audiobooks and e-books are developing rapidly, there are still many people who are obsessed with the atmosphere in the library. Besides the normal readers，every day there are a lot of tourists who come to visit the famous public libraries in New York. New York has a lot of libraries so how do people choose the library they like? It will be interesting if I could create some Geomaps which could fit the new demand of the library.

Process and Result

The public library dataset I collected is provided on the Newyork open data. https://opendata.cityofnewyork.us/ It includes all the public library in New York City. As we can see here, New York’s libraries are evenly distributed, with almost a few of their own libraries in almost every district.

When people decide whether they want to go to a library one key element is the traffic. Most of the people will choose the subway to take them to the library. The first step I did was adding another subway layer under the library layer. New York has many subway lines. Simply use solid lines to show all the subway is kind of annoying to me. So I change to another way which is using animation to show each subway lines.

By watching the animation of different subway lines. People can easily tell which library near them is closer to the subway.

After mapping the foundational subway lines and the library map, I want my map could fit the new demand of people nowadays. So the yelp rating comes to my mind, a lot of people have the habit of checking the rating score of some places first and then decided whether to go or not to go. I want to try to input all the rating data on the Yelp and creating a public library rating map. However, I did not find a way to input or download all the rating data in the Yelp, so I input the TOP20 rating library manually.

Besides I observed people are more willing to have something to drink or eat while reading a book or after reading it. We can see many posts on Instagram combine the book and drinks together. It will be interesting if I could combine the Starbucks map and the TOP3 rating public library or public library map together.

There is no existing dataset of all the Starbucks store address. The first step I did is to collect all the address of each store and use Google sheet converted to latitude and longitude that Carto can recognize.

In this map, all the green points represent the Starbucks store and the red points are the TOP3 Library. We can see that The new york Public Library is closer to Starbuck stores and subway lines. Battery park city library has a better ocean view and has a Starbucks nearby. Kips Bay library is a little bit far away from subway.

Reflection

In this project, I try to combine something interesting and trending, like the Yelp rating. The problem in this project is that I failed to input all the rating information in this map so I could create a Yelp library rating map which will show the rating level from high to low visually.