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. Each time the page is visited, here is what's happening:

1. Scraping

Using Jupyter Notebook, BeautifulSoup, Pandas, and Requests/Splinter.

NASA Mars News

• Scrapes the NASA Mars News Site and collects the latest News Title and Paragragh Text.

JPL Mars Space Images - Featured Image

• Visits the url for JPL's Featured Space Image here.

• Uses splinter to navigate the site and find the image url for the current Featured Mars Image and assign the url string to a variable called featured_image_url.

Mars Weather

• Visits the Mars Weather twitter account here and scrapes the latest Mars weather tweet from the page. Saves the tweet text for the weather report as a variable called mars_weather.

Mars Facts

• Visits the Mars Facts webpage here and use Pandas to scrape the table containing facts about the planet including Diameter, Mass, etc.

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

Mars Hemisperes

• Visits the USGS Astrogeology site here to obtain high resolution images for each of Mar's hemispheres.

• Saves both the image url string for the full resolution hemipshere image, and the Hemisphere title containing the hemisphere name. Use a Python dictionary to store the data using the keys img_url and title.

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2. MongoDB and Flask Application

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