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1. Exploring-NYC-Public-School-Test-Result-ScoresExploring-NYC-Public-School-Test-Result-ScoresPublic

   Analyze SAT performance of New York City public schools using Python and pandas. Identify top-performing schools, borough-level variability, and key insights from standardized test scores.

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2. Investigating-Netflix-MoviesInvestigating-Netflix-MoviesPublic

   Explore Netflix catalog to analyze movies from the 1990s using Python, pandas, and matplotlib. Identify short action films, compute duration trends, and visualize nostalgic content insights.

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3. Visualizing-the-History-of-Nobel-Prize-WinnersVisualizing-the-History-of-Nobel-Prize-WinnersPublic

   Explore Nobel Prize winners from 1901 to 2023 using Python, pandas, seaborn, and matplotlib. Analyze trends by decade, gender, country, and category, identify repeat laureates, and visualize histor…

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4. Analyzing-Crime-In-Los-AngelesAnalyzing-Crime-In-Los-AngelesPublic

   Analyze Los Angeles crime data using Python, Pandas, Seaborn, and Matplotlib. Explore hourly crime patterns, night-time hotspots by area, and victim age distributions to support LAPD resource alloc…

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5. Hypothesis-Testing-with-Men-s-and-Women-s-Soccer-MatchesHypothesis-Testing-with-Men-s-and-Women-s-Soccer-MatchesPublic

   Statistical analysis of FIFA World Cup matches (2002–present) to test if women's games have more goals than men's. Uses Python, Pandas, and Mann–Whitney U test at 10% significance level.

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6. Cleaning-Bank-Marketing-Campagin-DataCleaning-Bank-Marketing-Campagin-DataPublic

   Clean and standardize a bank marketing dataset into three PostgreSQL-ready CSVs (client, campaign, economics). Includes value normalization, boolean mappings (0/1), and a derived last_contact_date …

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