This is the capstone project of my Google Data Analytics Professional Certificate course, centered on the analysis of a dataset from a fictional bike-sharing company called Cyclistic, based out of Chicago.

The dataset comprises Cyclistic’s own historical trip data, spanning the second, third, and fourth quarters of 2019, along with the first quarter of 2020, providing a comprehensive 12-month period for analysis.

Formatted as comma-delimited (.CSV) files, the data consists of four datasets: 'Divvy_Trips_2019_Q2' with 12 columns and 1,048,575 rows; 'Divvy_Trips_2019_Q3' with the same structure; 'Divvy_Trips_2019_Q4' with 12 columns and 704,054 rows; and 'Divvy_Trips_2020_Q1' with 13 columns and 426,887 rows.

This publicly available data is generously provided by Motivate International Inc. under a license. The dataset can be accessed here.

For this analysis, I will be using the R programming language and the RStudio IDE. The choice of R and RStudio was made for their robust ability to integrate effective statistical analysis tools with some compelling data visualizations.