sherirosalia / tableau-for-the-city

Tableau Citi Bike Visualization

Tableau-for-the-Citi-

Webscraping and data cleaning AWS s3 files using Python libraries: Splinter and Urllib.

Visualization with Tableau.

Link to Tableau Public

File structure

• Root folder contains readme and the following folders:
• "python" folder contains the script "data_extract" which Selenium to automate a browser to download the Amazon SW3 files used for the project. The file citibikeClean normalizes and selects datapoints to be used in the visualizations.
• "tableau_package" has the Tableau data extract and workbook.
• "citi_data_files" stores embed code for HTML
• "images" house screenshots for readme

Deployment

Open the files from the folder named python with Colab, Jupyter Notebook or the like. Tableau is needed to open the package.

This interactive map allows the user to interact with Citi Bike activity for the last month of 2018.

Some obervations:

• The visualizations highlight that men and subscribers far outweigh the alternative in regular use.

• Very few bikes were returned on New Years Eve.

• Is celebratory biking on the rise, or did people fail to return them?

• Popular start stations and ending stations are not the same.

• The majority of the activity seems to take place in redevelopment and commercial areas of lower Manhattan, Brooklyn near the bridges and Long Island City, Queens.

• The most popular starting times seem to mimic a 9-5 work schedule. It's not conclusive for several reasons, the most obvious being that I did not pull weekends out of the data. Perhaps if I did, the peaks would have been more extreme.

This project illustrates how multiple modalities can combine to grab, clean and visualize data. The data comes from the Citibike program is held in Amazon Web Servers and was extracted and cleaned using the Python programming language. Analysis and visualizations were created using Tableau.

Screenshots:

from bs4 import BeautifulSoup
import pandas as pd
from selenium import webdriver
from io import BytesIO
from zipfile import ZipFile
from urllib.request import urlopen
import os
import csv
from datetime import datetime

Dashboard

Nonsubscribers vs Subscribers

Ride Map

Starting Times

Top Pick Up Stations

Top Drop Off Stations

New Years Eve