E-Commerce Sales Data Secrets You Never Knew!

📊 Unlocking Ecommerce Sales Insights Using Python | Data Analytics Tutorial Are you sitting on a goldmine of ecommerce sales data but not sure how to turn it into actionable insights? In this video, we'll walk you through a real-world ecommerce transactions dataset and show you how to analyze it step-by-step using Python. 🔍 What You’ll Learn: ✅ How to load and explore ecommerce sales data ✅ Identify top-selling products, categories, and time periods ✅ Use rolling averages and trend analysis for customer behavior ✅ Discover patterns in discounts, ratings, and customer sentiment ✅ Visualize key metrics using Seaborn and Matplotlib ✅ Learn techniques you can apply to your own ecommerce business or project This video is perfect for: Aspiring data analysts and data scientists Ecommerce business owners Students working on data projects Anyone curious about using Python for real-world business insights 📁 Dataset Used: We use a sample ecommerce sales dataset with fields like product details, prices, discounts, customer reviews, and transaction dates. 🧠 Tools & Libraries: Pandas Seaborn Matplotlib NumPy 👉 Don't forget to Like, Comment, and Subscribe if you find this helpful! 📢 Share this with someone trying to break into Data Analytics or Ecommerce AI. Download Notebook : https://colab.research.google.com/drive/1Ippk-rUFh_QQPEjAGjdkG8B4OI--f_Dp?usp=sharing Download DataSet : https://drive.google.com/file/d/1ENyT3eOQC3pOmodvWdslEdwqydJ-SFXd/view?usp=sharing