Air Quality Analysis Project

This repository contains a reproducible pipeline for analyzing air quality data collected in an Italian city from March 2004 to February 2005. The dataset includes hourly measurements of air pollutants and meteorological conditions. The analysis focuses on cleaning the data, summarizing key variables, visualizing patterns, and building regression models to predict benzene levels.

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Project Overview

This project performs the following steps:

1. Data Cleaning (code/00_clean_data.R)
2. Descriptive Summary Table (code/01_make_table.R)
3. Visualizations (code/02_make_plot.R)
4. Modeling (code/03_make_model.R)
5. Final Report Rendering (code/04_render_report.R)

All scripts save their outputs in the output/ directory. The final report is rendered as final_report.html in the final_report/ directory.

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How to Reproduce the Report Locally

This project uses renv to ensure package reproducibility.

1. Before building the project, confirm that you has the renv package installed, run the following code in Console:

"renv" %in% row.names(installed.packages())

If the above command returns FALSE, install the renv package using install.packages("renv") in Console.

2. Install necessary R packages (if needed):

install.packages(c("here", "tidyverse", "yaml", "kableExtra", "gtsummary", "ggcorrplot", "gt", "broom.helpers", "cardx", "car", "parameters"))

3. Restore package environment using the renv.lock file:

make install

4. Clean previous outputs (optional):

make clean

5. Build the full project and generate final_report/final_report.html:

make

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Docker Instructions

This project includes a Dockerfile that builds an image to fully reproduce the analysis inside a containerized environment.

1. Using the Pre-Built DockerHub Image (Recommended for Reproducibility)

You can pull the image directly from DockerHub:

docker pull youweihu/final_project_image

DockerHub link

Run the pipeline inside a container with:

make docker_run

This will:

• Mount your local final_report/ directory
• Execute the full workflow inside the container
• Output final_report.html into your local final_report/ folder

2. Building the Image Locally (for Developers Only)

If you'd like to rebuild the image yourself instead of using DockerHub (you must have Docker installed):

docker build -t final_project_image .

or simply:

make build_image