Python-Data-Analysis

This repository contains an end-to-end sales data analysis project using Python (Pandas, Matplotlib, Seaborn) and Power BI. The dataset used is “Sample Sales Data: Denormalize Sales Data (Segmentation, Clustering, Shipping, etc.) by Gus Segura”, which contains retail sales transactions with order, product, customer, and geographical details.

📊 Sales Data Analysis Project

This project demonstrates end-to-end data analysis and visualization using Python and Power BI on a sample sales dataset.

📊 Dataset

The dataset used is:

• Sample Sales Data – Denormalize Sales Data (Segmentation, Clustering, Shipping, etc.)
• Contains ~2,800 rows and 25 columns
• Key columns:
  • ORDERNUMBER, ORDERDATE, PRODUCTLINE, SALES, QUANTITYORDERED, PRICEEACH
  • CUSTOMERNAME, COUNTRY, STATE, CITY
  • DEALSIZE, TERRITORY

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🛠️ Tools & Libraries

• Python: pandas, matplotlib, seaborn

  📈 Analysis & Visualizations

1. Data Cleaning

   • Handled missing values (STATE, POSTALCODE, TERRITORY)
   • Converted ORDERDATE to datetime
   • Extracted year and month for time-based analysis

2. Exploratory Analysis

   • Sales by product line
   • Deal size distribution
   • Sales trends over time
   • Pivot table summaries by country/product line

3. Visualizations

   • 📊 Bar chart: Sales by product line
   • 🥧 Pie chart: Deal size distribution
   • 📈 Line chart: Sales trend by month/year
   • 📋 Pivot tables: Country vs Product line sales