This Coursera Capstone Project focuses on analyzing the Fitabase dataset (03/12/2016–11/04/2016), which contains activity, sleep, and wellness data collected from Fitbit device users from the manufacturer Bellabeat. The goal of this project is to apply the full analytical workflow — data preparation, transformation, exploration, and visualization — to uncover meaningful trends and generate insights that can support Bellabeat, a company specializing in health-focused smart devices. This analysis forms the final practical assessment of the Google Data Analytics Certification.

Bellabeat, women’s wellness company
Fitabase dataset (03/12/2016–11/04/2016)

Exploratory Data Analysis

Data Quality / ROCCC

ETL

Analysis

Using the render_all.R

To streamline the automated build process of this analysis, the project includes a dedicated rendering script located at:

scripts/render_all.R

This script performs three key tasks:

  1. Builds the complete HTML website associated with all reports inside the reports/ folder.
  2. Generates English and French Jupyter Notebooks (.ipynb) based on the corresponding R Markdown files.
  3. Organizes all outputs into their appropriate directories.

The HTML site is produced in:

reports/output/

The Jupyter notebooks are generated in:

notebooks/

Generation of .ipynb Notebooks

As part of the build workflow, the script automatically converts each R Markdown file matching the naming pattern:

XX_ReportName.Rmd  
XX_ReportName_FR.Rmd

into structured Jupyter notebooks (.ipynb).

Process overview

  • Quarto is used to render each .Rmd file into .ipynb format.
  • Notebooks are first created temporarily inside reports/.
  • They are then moved into the main output directory:
notebooks/

separated into English and French versions depending on file naming conventions (_FR.Rmd vs non-FR).

These notebooks can be opened locally, reviewed in JupyterLab/Jupyter Notebook, or uploaded directly to Kaggle as public notebooks accompanying the HTML analytical reports.

How to execute the rendering script from RStudio

  1. Open the RStudio console.
  2. Run the following command:
source(here::here("scripts", "render_all.R"))

Executing this command triggers the full build process:

  • HTML site generation
  • .ipynb notebook generation
  • Output organization across both reports/output/ and notebooks/

After completion, the console displays a summary of all generated artifacts.