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  1. Exploring-NYC-Public-School-Test-Result-Scores Exploring-NYC-Public-School-Test-Result-Scores Public

    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.

    Jupyter Notebook

  2. Investigating-Netflix-Movies Investigating-Netflix-Movies Public

    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.

    Jupyter Notebook

  3. Visualizing-the-History-of-Nobel-Prize-Winners Visualizing-the-History-of-Nobel-Prize-Winners Public

    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…

    Jupyter Notebook

  4. Analyzing-Crime-In-Los-Angeles Analyzing-Crime-In-Los-Angeles Public

    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…

    Jupyter Notebook

  5. Hypothesis-Testing-with-Men-s-and-Women-s-Soccer-Matches Hypothesis-Testing-with-Men-s-and-Women-s-Soccer-Matches Public

    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.

    Jupyter Notebook

  6. Cleaning-Bank-Marketing-Campagin-Data Cleaning-Bank-Marketing-Campagin-Data Public

    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 …

    Jupyter Notebook