💻 Completed Full Data Analysis Process Using Python (Pandas) 📊
I’m happy to share that I’ve successfully completed all 5 Phases of the Data Analysis workflow step by step:
🧩 Phase 1: Data Understanding
Loaded dataset, reviewed column types, and understood the meaning of each field.
🧹 Phase 2: Data Cleaning
Handled missing values, removed duplicates, corrected data types, and formatted dates properly.
⚙️ Phase 3: Data Preparation
Created new calculated columns such as Total Sales Value, Profit Margin %, and Month from Date to enrich the dataset.
🔍 Phase 4: Data Exploration
Explored key insights like total profit by region, top-performing salespersons, and product discounts.
📈 Phase 5: Aggregation & Insights
Compared sales and profits across regions, analyzed discount impact, and identified top 5 profitable products.
This hands-on exercise helped me understand how data cleaning and exploration lead to valuable business insights.
Excited to move towards Data Visualization next using Power BI / Tableau! 🚀
Git Hub Link - https://lnkd.in/eyUQrcgu
hashtag#DataAnalytics hashtag#Python hashtag#Pandas hashtag#DataCleaning hashtag#DataExploration hashtag#DataScience hashtag#LearningJourney
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