Performed exploratory data analysis on Netflix titles using Python to identify trends in content,...Performed exploratory data analysis on Netflix titles using Python to identify trends in content,...
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Performed exploratory data analysis on Netflix titles using Python to identify trends in content, genres, release years, countries, and ratings. Used Pandas and visualization libraries to clean, analyze, and present insights.
Client had raw sales data (14 rows across UK/USA, split by quarter) and needed it turned into something actually usable. I cleaned it up and built a PivotTable that breaks total sales down by rep and country, with grand totals for both.
What I did:
Structured the raw data into a proper table (consistent headers, currency formatting)
Built a PivotTable summarizing Sum of Sales by Last Name and Country
Used SUMIFS so the totals update automatically if the source data changes — nothing hardcoded
Checked every formula for errors before delivery
Delivered as a working .xlsx file, ready to plug into a bigger report or dashboard.
If you've got messy sales/ops data sitting in a spreadsheet and need it turned into something you can actually read at a glance, this is exactly the kind of thing I can help with.
Developed AI-generated character content for an AI Companion Platform, exploring social media trends through cinematic visuals, storytelling, and character-driven formats.
Healthcare Data Analysis — UCI Heart Disease Dataset
Exploratory data analysis of 303 clinical records using Python, Pandas, NumPy, and Matplotlib.
The project included data cleaning, missing-value handling, descriptive analysis, healthcare data visualization, and responsible interpretation of clinical patterns.