This R Markdown project is designed for conducting a comprehensive weather analysis related to sales data. The script encompasses various data processing steps, including sales and weather data manipulation, trend analysis, and correlations between weather conditions and sales performance.

• Sales Data Processing: Functions to clean and prepare sales data for analysis.
• Weather Data Integration: Tools for loading and processing weather data, and aligning it with sales data.
• Analytical Functions: Custom functions for systemwide sales analysis and weather trend analysis.
• Modular Design: Each major step is encapsulated in a function for better organization and reusability.
• Data Exporting: Capabilities to output processed data and analysis results.

The following R packages should be installed for the script to function correctly:

• tidyr
• dplyr
• reshape2
• lubridate
• geosphere
• zipcode
• RCurl
• RJSONIO
• corrplot

To use the script, follow these steps:

1. Set Up File Paths: Replace the placeholder paths in the run_analysis function call with the paths to your actual data files.
2. Run Analysis: Execute the run_analysis function to process the data and perform the analysis.
3. Review Results: Check the output files for insights and data visualizations.

run_analysis("path/to/Flash Sales by Order Date.csv", 
             "path/to/store list.csv", 
             "path/to/weather_2018.csv", 
             "path/to/weather_2019.csv", 
             "path/to/weather_station.csv")

Contributions to enhance the script's functionality or to extend its capabilities are welcome. Please ensure to follow coding standards and add appropriate documentation for new features.

• Lisa Li - Initial work

This project is licensed under the MIT License.

Special thanks to all contributors and collaborators who have provided data, insights, and expertise to the project.