May 16, 2024

Mars News and Weather Data Analysis with Web Scraping

Project Summary:

This project involves web scraping and data analysis to gather Mars-related news and weather data. The first part focuses on scraping titles and preview text from Mars news articles. The second part involves scraping Mars weather data from an HTML table, analyzing it using pandas, and creating visualizations to answer specific scientific questions about Mars, such as identifying temperature trends and atmospheric pressure variations. The project uses Python with libraries such as Splinter, BeautifulSoup, Pandas, and Matplotlib to automate browsing, scrape data, and perform analysis.

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May 9, 2024

Climate Data Analysis and Visualization with SQLAlchemy

Project Summary:

This project involves using SQLAlchemy to analyze climate data stored in a SQLite database, followed by the design of a Flask API to make the analysis accessible through web-based routes. The analysis focuses on Hawaii’s weather, including precipitation and temperature trends, with an exploration of various weather stations across the region. The project is divided into two parts: the first part analyzes and explores climate data using Python, SQLAlchemy, and Pandas, while the second part develops a Flask API to serve the analysis results through different endpoints.

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May 1, 2024

SQL Data Modeling, Engineering, and Analysis

Project Summary:

This project focuses on designing and engineering a relational database system for employee data, using SQL to query, analyze, and derive insights from the data. The project includes three key phases: Data Modeling, Data Engineering, and Data Analysis. In the Data Modeling phase, an Entity Relationship Diagram (ERD) is created to model the data structure. The Data Engineering phase involves creating and populating relational tables using PostgreSQL. Finally, in the Data Analysis phase, complex SQL queries are executed to analyze employee demographics, department structure, salary trends, and more.

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April 18, 2024

Temperature and Air Pollution Correlation Analysis

Project Summary:

This project explores the correlation between rising global temperatures and increased levels of PM2.5 air pollution across selected countries: the USA, Canada, Mexico, Chile, and Colombia. The analysis includes historical temperature and pollution data, population metrics, and additional factors such as humidity and wind speed. The study employs various visualization techniques, including scatterplots, line charts, and regression plots, to assess relationships between temperature and air pollution trends. A geographical component is also introduced by mapping countries with coal plants to evaluate the impact of coal-based energy production on pollution density.

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April 11, 2024

Weather and Vacation Data Analysis Using APIs

Project Summary:

This project uses weather data and location-based data from APIs to analyze weather trends across various global cities and identify ideal vacation spots based on specific weather conditions. The project is divided into two parts:

  • WeatherPy: A comprehensive analysis of weather variables, such as temperature, humidity, cloudiness, and wind speed, in relation to latitude. Using data from the OpenWeatherMap API, this analysis includes visualizations through scatter plots and linear regression models to compare weather trends between the Northern and Southern Hemispheres.
  • VacationPy: Utilizing weather data from WeatherPy, the project identifies ideal vacation destinations based on specific weather conditions, such as moderate temperature and low humidity. The Geoapify API is used to locate nearby hotels within a 10,000-meter radius of selected cities, and the results are plotted on an interactive map.

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GitHub Link: To see my project on GitHub please click GitHub Repository button below