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:
- Set Up File Paths: Replace the placeholder paths in the
run_analysis
function call with the paths to your actual data files. - Run Analysis: Execute the
run_analysis
function to process the data and perform the analysis. - 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.