This project aims to analyze retail sales data to uncover patterns and insights that can drive business decisions. The analysis includes data cleaning, exploratory data analysis (EDA), feature engineering, and data visualization.
The dataset used in this project is a fictional retail sales dataset available on Kaggle. It includes information about sales transactions, store details, and product information.
- Handle missing values
- Convert data types
- Standardize categorical variables
- Summary statistics
- Data visualization
- Identify trends and patterns
- Create new features from existing data
- Transform categorical variables into dummy/indicator variables
- Visualize key insights using bar charts, histograms, scatter plots, etc.
To run this project, you need to have Python and the necessary libraries installed. You can install the required libraries using the following command:
pip install -r requirements.txt