This repository contains data and code associated with the manuscript "Analysis of Fixture Efficiency and Behavioral Factors of Indoor Residential Water Use of Single-Family Households." The repository is organized into three main folders: Data, Code, and Results, as detailed below.

## Data

### 1. City_shapefile
- Contains metropolitan statistical area (MSA) shapefiles

### 2. Flume
- Contains two Excel files with aggregated city-level data:
  - User behavior factors
  - Fixture efficiency factors
- **Flume_Inc_&_Mayer_2022.pdf**: Technical report describing Flume's data analysis methodology (Flume Inc., & Mayer, P., 2022). This report is cited in the Supplementary Information section of the manuscript

### 3. PRISM
- Contains raster weather data from PRISM (Parameter-elevation Regressions on Independent Slopes Model)
- Includes both raw and processed weather data
- Processed (tabular format) weather data are available in `weather_vars_process.csv`. Each weather variable in this file represents the average of pixels for each day within each city

## Code

### R Scripts
1. **ME.R**
   - Runs the mixed effects models for research questions two and three
   - Note: The dataframes used to run this code are not included due to privacy reasons. Refer to the Data Availability Statement in the manuscript for details

2. **GEE.R**
   - Runs the generalized estimating equation models for research questions two and three
   - Note: The dataframes used to run this code are not included due to privacy reasons. Refer to the Data Availability Statement in the manuscript for details

### Python Jupyter Notebooks
1. **Prism_&_ACS_data.ipynb**
   - Used to access and/or process the PRISM and US Census data

2. **Clustering.ipynb**
   - Conducts the kmeans and functional kmeans clustering
   - Visualizes clustering results

3. **Statistical_tests.ipynb**
   - Visualizes the statistical tests results used to answer research question one

4. **ME_models_visuals.ipynb**
   - Visualizes the results of the Mixed Effects models for research questions two and three

5. **GEE_models_visual.ipynb**
   - Visualizes the results of the Generalized Estimating Equation models for research questions two and three

## Results

### 1. statistical_test_results_and_descriptive_stats
- Contains detailed results from Chi-square tests of independence (for categorical variables)
- Contains detailed results from Kruskal-Wallis tests (for continuous variables)
- Includes descriptive statistics for both categorical and continuous variables across household categories
- Used to answer research question one in the manuscript

### 2. linear_modeling_results
- Contains detailed results of GEE (Generalized Estimating Equation) models
- Contains detailed results of ME (Mixed Effects) models
- Includes parameter estimates and level of uncertainty
- Includes model diagnostics (e.g., variance inflation factors) for each model described in the manuscript