Mission To Mars

Overview

The web-scraping-challenge project is a web application that scrapes various websites for data related to the Mission to Mars and displays the information in a single HTML page. The project involves two main steps: scraping the data using Jupyter Notebook, BeautifulSoup, Pandas, and Requests/Splinter, and then displaying the scraped data using MongoDB and Flask templating.

Features

• Scrapes the latest news title and paragraph text from the Mars News Site.
• Retrieves the URL of the current Featured Mars Image from the JPL Mars Space Images website.
• Scrapes facts about Mars, such as its diameter and mass, from the Mars Facts webpage and converts the data into an HTML table string using Pandas.
• Obtains full-resolution images for each of Mars' hemispheres from the Astrogeology site.
• Stores the scraped data in a MongoDB database using the scrape_mars.py script.
• Displays the scraped data on a single HTML page using the Flask application and the index.html template.

Summary

The web-scraping-challenge project is a web application that scrapes data from various websites related to Mars and displays the information in a single HTML page. It utilizes technologies like Jupyter Notebook, BeautifulSoup, Pandas, Requests/Splinter, MongoDB, and Flask. The application provides features such as retrieving the latest news about Mars, displaying the featured image, presenting facts about Mars in a table, and showcasing images of Mars' hemispheres. It offers a convenient way to access and view up-to-date information about Mars in one place.