Citibike Map Data Visualization and Analysis

Posted on Nov 4, 2019
The skills the author demoed here can be learned through taking Data Science with Machine Learning bootcamp with NYC Data Science Academy.

Introduction

Bike-shares have become popular in major cities all across the US. Data shows Citibike in NYC is among one of the most popular. It's a convenient and fun alternative to taking the bus or subway.

For this Shiny project I was interested in utilizing Citibike's public database to bring this information to life through visualization. I was curious in bike station user activity with respect to a chosen hour via a heat map. Additionally I wondered what was the journey of a given bike throughout any chosen day.

 

Application and Data Results:

For this app there are 3 tabs to choose from; density map, trip map and data. The Density map tab contains two displays. On the left is a map of NYC and the right is a histogram. Additionally there are two selection boxes where you can choose the day and hour of interest. The map on the left displays the the number of users that checked out bikes from stations within the selected hour. This is displayed as purple clouds, the darker and larger the cloud relates to more users active at that station. On the right is a histogram displaying the number of users for any given hour of that selected day.

Density Map

Citibike Map Data Visualization and Analysis

Figure 1: Density map

From the histogram we can see there are two peaks. One in the morning and one in the evening. This is not such a surprise given that the date chosen is a typical weekday in the mild month of September. Also notice the hour chosen is 5 pm and the density map is saturated in Manhattan, but sparse in Brooklyn or Queens. This suggests most users are leaving work from Manhattan.

Trip Map

The next tab is the trip map. It contains a single map display and two selectors. The selectors allow you to choose a bike ID and date. With these inputs selected the map will display that bike's entire journey for that day from all users. The red marker is the starting point and blue is the final end point. The travel path gets darker for multiple trips over the same path and lighter for single trips. Also it's worth mentioning here that the path displayed is the suggested bicycling route via google directions. It is the most likely path taken, but not the true paths taken by all users.

Citibike Map Data Visualization and Analysis Figure 2: Trip map

 

Future work:

This app is convenient and easy to use, but there is far more room for expansion. For future editions the user will be able to graphically see the range traveled of a specific bike given a selected duration of time, not just a day. This can be displayed via a histogram or the trip map. This will give insight if bikes generally stay in one location or cycle through different boroughs.

Another feature to add is a play button to observe the user density map throughout the way.

Additionally this app can be scaled up to multiple bike-shares in other cities. This is very possible given most other bike-shares have public data sets with similar information and formatting.

 

Thanks for reading!

About Author

Leave a Comment

No comments found.

View Posts by Categories


Our Recent Popular Posts


View Posts by Tags

#python #trainwithnycdsa 2019 2020 Revenue 3-points agriculture air quality airbnb airline alcohol Alex Baransky algorithm alumni Alumni Interview Alumni Reviews Alumni Spotlight alumni story Alumnus ames dataset ames housing dataset apartment rent API Application artist aws bank loans beautiful soup Best Bootcamp Best Data Science 2019 Best Data Science Bootcamp Best Data Science Bootcamp 2020 Best Ranked Big Data Book Launch Book-Signing bootcamp Bootcamp Alumni Bootcamp Prep boston safety Bundles cake recipe California Cancer Research capstone car price Career Career Day citibike classic cars classpass clustering Coding Course Demo Course Report covid 19 credit credit card crime frequency crops D3.js data data analysis Data Analyst data analytics data for tripadvisor reviews data science Data Science Academy Data Science Bootcamp Data science jobs Data Science Reviews Data Scientist Data Scientist Jobs data visualization database Deep Learning Demo Day Discount disney dplyr drug data e-commerce economy employee employee burnout employer networking environment feature engineering Finance Financial Data Science fitness studio Flask flight delay gbm Get Hired ggplot2 googleVis H20 Hadoop hallmark holiday movie happiness healthcare frauds higgs boson Hiring hiring partner events Hiring Partners hotels housing housing data housing predictions housing price hy-vee Income Industry Experts Injuries Instructor Blog Instructor Interview insurance italki Job Job Placement Jobs Jon Krohn JP Morgan Chase Kaggle Kickstarter las vegas airport lasso regression Lead Data Scienctist Lead Data Scientist leaflet league linear regression Logistic Regression machine learning Maps market matplotlib Medical Research Meet the team meetup methal health miami beach movie music Napoli NBA netflix Networking neural network Neural networks New Courses NHL nlp NYC NYC Data Science nyc data science academy NYC Open Data nyc property NYCDSA NYCDSA Alumni Online Online Bootcamp Online Training Open Data painter pandas Part-time performance phoenix pollutants Portfolio Development precision measurement prediction Prework Programming public safety PwC python Python Data Analysis python machine learning python scrapy python web scraping python webscraping Python Workshop R R Data Analysis R language R Programming R Shiny r studio R Visualization R Workshop R-bloggers random forest Ranking recommendation recommendation system regression Remote remote data science bootcamp Scrapy scrapy visualization seaborn seafood type Selenium sentiment analysis sentiment classification Shiny Shiny Dashboard Spark Special Special Summer Sports statistics streaming Student Interview Student Showcase SVM Switchup Tableau teachers team team performance TensorFlow Testimonial tf-idf Top Data Science Bootcamp Top manufacturing companies Transfers tweets twitter videos visualization wallstreet wallstreetbets web scraping Weekend Course What to expect whiskey whiskeyadvocate wildfire word cloud word2vec XGBoost yelp youtube trending ZORI