Business Problem: A Retail store is required to analyze the day-to-day transactions and keep a track of its customers spread across various locations along with their purchases/returns across various categories.
After data munging and merging, I've done descriptive analysis:
- Analyze which product categories are more popular region wise, gender-wise.
- Analyze customer percentage across cities.
- Understand the behaviour of store, products.
- Customer total spend (product, gender, period, store wise, etc.)
- Customer spend analysis based on different age groups.
- Profit & loss on product and it's categories
Matplotlib · pandas · NumPy · Python
I'm an aspiring Data Analyst with a strong foundation in data manipulation and statistical analysis. I thrive on uncovering insights that drive decisions and am passionate about learning.
As a Data Analyst, I specialize in transforming raw data into clear, impactful insights using Python, SQL, and visualization tools like Matplotlib and Power BI. My educational background includes a Post Graduate Diploma in Business Administration in Finance, and I'm currently pursuing a Data Science program at AnalytixLabs.
My technical skills encompass Python, SQL, Statsmodel, and various statistical techniques, with a focus on machine learning libraries like Scikit-Learn and TensorFlow. I'm dedicated to turning data into compelling stories that influence business outcomes.
