Mission to Mars

built 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 following outlines what you need to do.

Scraping

Completed initial scraping using Jupyter Notebook, BeautifulSoup, Pandas, and Requests/Splinter.

• Created a Jupyter Notebook file called mission_to_mars.ipynb and used this to complete all of your scraping and analysis tasks. The following outlines what you need to scrape.

NASA Mars News

• Scraped the NASA Mars News Site and collected the latest News Title and Paragraph Text.

JPL Mars Space Images - Featured Image

• Visited the url for JPL Featured Space Image (https://www.jpl.nasa.gov/spaceimages/?search=&category=Mars).

• Used splinter to navigate the site

Mars Weather

• Visited the Mars Weather twitter account(https://twitter.com/marswxreport?lang=en) and scraped the latest Mars weather tweet from the page.

Mars Facts

• Visited the Mars Facts webpage (http://space-facts.com/mars/) and used Pandas to scrape the table containing facts about the planet including Diameter, Mass, etc.

• Used Pandas to convert the data to a HTML table string.

Mars Hemispheres

• Visited the USGS Astrogeology site (https://astrogeology.usgs.gov/search/results?q=hemisphere+enhanced&k1=target&v1=Mars) to obtain high resolution images for each of Mar's hemispheres.

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Step 2 - MongoDB and Flask Application

Used MongoDB with Flask templating to create a new HTML page that displays all of the information that was scraped from the URLs above.

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