Welcome to my Data Analysis Projects repository! Here, I explore and analyze various datasets to gain insights and draw meaningful conclusions. Below, you'll find details about one of my projects:
This project is my first venture into data analysis, where I delve into the world of Netflix movies. I aim to uncover trends, patterns, and interesting information about the movies available on the platform.
- The project and Dataset: Netflix Movies Dataset
- Tools: Python, Jupyter Notebooks, Pandas, Matplotlib, Seaborn , sklearn
- Data Cleaning: I cleaned the dataset to ensure accurate and reliable analysis.
- Exploratory Data Analysis (EDA): Utilized visualizations to understand the distribution and relationships within the data.
- Insights and Findings: Documented interesting findings and insights gained from the analysis.
In my second project, I explore the intriguing relationship between weather conditions and policing activities in Rhode Island. By merging datasets on traffic stops and weather information, I aim to uncover patterns and insights that may provide a nuanced understanding of law enforcement practices.
- The project and Dataset: Policing and Weather Analysis
- Tools: Python, Jupyter Notebooks, Pandas, Matplotlib, Seaborn
- Integration of Datasets: Merged the policing dataset with weather data to enable a comprehensive analysis.
- Correlation Exploration: Investigated the correlation between weather elements and the frequency of traffic stops.
- Temporal Patterns and Extreme Weather Impact: Analyzed temporal patterns and the influence of extreme weather on policing outcomes.
- Visualizations: Incorporated visualizations to communicate findings effectively.
Repository: (Link_to_Repository)
Feel free to explore the projects and provide feedback or contributions. I'm continually working to enhance my data analysis skills and welcome collaboration and insights from the community!