This project is a part of an assignment aimed at improving skills in working with MongoDB and utilizing the NASA Near Earth Objects (NEOs) API. The primary goal of this project is to retrieve and analyze data related to asteroids from NASA's NEOs API and perform various data analysis tasks using PyMongo.
- Objective: The main objective of this project is to gain practical experience in working with real-world data using the PyMongo library to interact with MongoDB and the NASA NEOs API.
The project includes the following components:
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Data Retrieval: The project retrieves data from NASA's Near Earth Objects API. This data contains information about asteroids, including their attributes such as absolute magnitude (H), diameter, velocity, orbital parameters, and more.
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Data Storage: The data retrieved from the NASA API is stored in a MongoDB database using PyMongo, providing a structured and efficient way to manage and analyze the data.
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Data Analysis: The project performs various data analysis tasks, including:
- Categorizing by risk level
- Analyzing the relationship between asteroid diameter absolute error and absolute magnitude (H).
- Clustering asteroids
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Data Visualization: Data analysis results are visualized using Python libraries such as Matplotlib to create meaningful plots and visual representations.
- The project uses data from NASA's Near Earth Objects API, and we would like to thank NASA for providing access to this valuable resource.