This is a summary of the different property listings in the state of Texas. In this analysis, I make a hypothesis about the influence of School Performance on the property value indicated by listing price and sales velocity. I use visualizations to depict the qualitative differences based on the data.

In this mock project, we evaluate the weekly sales at a local bakery. Compared to other projects, this is the simplest analysis that can be used for small businesses to better understand which items are most popular.

In this project, I combine multiple datasets (some of which have different time units) into a single data frame. The result is that it contains multiple numerical columns and I use binning to categorize the data based on minutes of activity. These visualizations are created to understand the trends within the data.

This project analysis was performed by Anthony in the beginning of June from his Coursera Google Analytics Certification. The data is from Coursera and the study is performed to understand the properties of cyclists who purchase the membership. For clarity, a Customer is a person who purchases a single-day pass, whereas a Subscriber purchases an annual membership. For simplicity, the analysis was conducted in the first quarter (Q1) of 2019 and 2020. The process aims to develop better marketing strategies to convince Customers to enroll in the membership and become Subscribers by identifying trends within historical Cyclist data in Chicago.

This markdown file is created to showcase the capabilities of RStudio for data analysis including using ggplot2, dplyr, and corrplot. The dataset is imported from the library 'palmerpenguins' and consists of 344 observations and 8 features.