This project was created in fulfillment of the requirements for the Google Data Analytics Professional Certificate.
- Description: This project involves analyzing Bellabeat data to gain insights into user behavior and product performance. The analysis includes data cleaning, exploratory data analysis, and visualizations to uncover trends and patterns.
- The data used in this project is publicly available data from the FitBit Fitness Tracker dataset on Kaggle linked here.
- R Skills Used: Data Cleaning, Data Visualization, Statistical Analysis, ggplot2, dplyr.
- View R Markdown File
- View Markdown or HTML file.
- Data Cleaning: Preparing raw data for analysis by handling missing values, outliers, and inconsistencies.
- Data Visualization: Creating informative and aesthetically pleasing visualizations using ggplot2.
- Statistical Analysis: Performing statistical tests and modeling to draw insights from data.
- ggplot2: Utilizing the ggplot2 package for advanced data visualization.
- dplyr: Using dplyr for efficient data manipulation and transformation.
- Tidying Data: Structuring data in a tidy format for easier analysis and visualization.
- R Markdown: Documenting and presenting data analysis using R Markdown for reproducible research.
- Exploratory Data Analysis (EDA): Analyzing data to summarize its main characteristics, often with visual methods.
- Data Importing and Exporting: Reading data from various sources and writing results to files.
- Date Functions: Handling and manipulating date and time data.
Feel free to explore the projects and R scripts to see my work in action. If you have any questions or feedback, please don't hesitate to reach out!
Note: To view the R Markdown files, navigate to the respective file paths provided in each project description.
Author: Ruiz del Carmen