Welcome to the Sales Data Analysis & Forecasting project! 🚀 This repository showcases my data analysis skills through exploratory data analysis (EDA), data cleaning, and visualization of sales and customer feedback data. The goal is to extract actionable insights to drive business decisions.
This project demonstrates my expertise as a Data Analyst by focusing on:
📈 Exploratory Data Analysis (EDA): Detecting patterns and trends in sales data.
🛠 Data Cleaning & Transformation: Ensuring the quality and reliability of the dataset.
📊 Visualizations: Creating engaging and informative charts for decision-makers.
🐼 Pandas: For data manipulation and cleaning.
🧮 NumPy: For numerical computations.
🎨 Matplotlib and Seaborn: For visualization.
** IDE: PyCharm**
The dataset includes the following columns:
🆔 product_id: Unique identifier for each product.
🏷️ product_name: Name of the product.
📦 category: Product category.
💰 discounted_price and actual_price: Pricing details.
🔢 discount_percentage: Discount percentage offered.
⭐ rating and rating_count: Product rating and number of ratings.
🗒️ about_product: Short description of the product.
🎯Product Ratings Distribution: Analyzed how customers rate products across various categories. Insight: Certain categories consistently outperform others in terms of average ratings.
📊 Category-Wise Discount Analysis: Average discount percentages by category to identify pricing strategies. Insight: Categories with optimal discounts tend to have better sales performance.
💹 Sales and Ratings Trends: Identified correlations between ratings, rating counts, and sales trends to understand customer preferences.
Histogram: Distribution of product ratings to identify customer satisfaction trends.
Bar Charts: Average discount percentage across categories.
Average rating counts by product category.
Clone the repository to your local machine: git clone https://github.com/your-repo/sales-data-analysis.git Install the required Python libraries: pip install -r requirements.txt Run the main.py file: python main.py View the generated visualizations and insights in your terminal or saved output files.
This project demonstrates how effective data analysis can uncover hidden trends and provide actionable business recommendations. As a Data Analyst, I utilized my skills in data cleaning, analysis, and visualization to draw insights from a real-world dataset.
✍️ Contact Me
Feel free to reach out if you’d like to know more or collaborate on data projects: 📧 Email: bethusreeja22@gmail.com 🌐 LinkedIn: https://www.linkedin.com/in/sreejabethu/