Communicate Data Findings
This project was completed as part of the course requirements of Udacity's Data Analyst Nanodegree certification.
Overview
In this project we will explore open data from Bay Wheels. A bike sharing program located within the bay area of California. First we will explore the data visually then present our findings in a Jupyter notebook slide show.
The Project Involved:
- Exploring and wrangling Bay Wheel data.
- Assessing data for quality and tidiness
- Cleaning, analysis and visualization.
Tech Used
- Jupyter Notebook (Data Science work book)
- SQLite3 (Database and querying)
- Pandas (very robust library for data analysis)
- Numpy (library for scientific computing)
- Matplotlib (library for robust plotting visualizations)
- Seaborn (statistical data visualization)
- OS (Provides function for interacting with the operating system)
- Geopandas (Goegraphical Mapping)
- CSV (Reading csv Files)
- Gmaps (Connecting to the google maps API)
- Shapely(A Library for working with geo data)
Key Findings:
- Our users are predominantly male.
- We have over a 160,000 subscribers and over 40,000 customers.
- Our most popular start stations vs least popular start stations differ vastly.
- There are areas and cities where the program is unavailable.
- There is a station in Canada based on the data
More Questions:
- How can we gain more female subscribers?
- Can we turn our customers into subscribers?
- Are the low traffic stations viable?
- How do we add more stations in high traffic areas for cities where the bike share program is unavailable?
- Why is there a station in Canada?