/Google_Capstone_Project_01

Small case study about a fictional bike sharing company (data was real). Made following what I learned on my Google Data Analytics Certificate course

Primary LanguageJupyter Notebook

Google Data Analytics Certificate - Capstone Project


Bike Sharing - Case Study

This is the first project done for the Google certificate course. The approached to work on this project was guided in 3 different ways:

  • Using Spreadsheet (Excel or Google Sheet)
  • Using Structure Query Language (SQL)
  • Using R and R Studio

But I decided to make my analysis using Python and Jupyter Notebooks as is the tool I have more experience with and Try a little bit of Tableu to share the visualizations.

A little about the company:

Cyclistic (a fictional company), is a bike-sharing company in Chicago. The director of marketing believes the company’s future success depends on maximizing the number of annual memberships.

Goals of this project

  • Apply everything learn about the data analysis process (Ask, Prepare, Process, Analyze, Share, and Act).
  • Demonstrate my knowledge and skills to potential employers.

Disclaimer: The data has been made available by Motivate International Inc. The dataset was used solely for educationanl purposes.

Data Preparation

Key tasks

• Download data and store it appropriately (last 12 months).

Data was downloaded and rename appropiately

• Identify how it’s organized.

• Sort and filter the data.

Data was place in a subfolder called "Archive"

• Determine the credibility of the data.

The data has been made available by Motivate International Inc. This is public data that can be use to explore how diferent customer types are using the service.
License: https://www.divvybikes.com/data-license-agreement

Data Processing

Key tasks

• Aggregate the data so it’s useful and accessible.
• Organize and format the data.
• Perform calculations.
• Identify trends and relationships.

Data Analysis

Key tasks

• Aggregate your data so it’s useful and accessible.
• Organize and format your data.
• Perform calculations.
• Identify trends and relationships.