In this assignment, we build a web application that scrapes various websites for data related to Mission to Mars and displays the information in a single HTML page. The following outlines what we did.
Web Scraping
We used Jupyter Notebook, BeautifulSoup, Pandas, and Requests/Splinter for initial scraping.Created a Jupyter Notebook file called mission_to_mars.ipynb and used this to complete all of scraping and analysis tasks.
1. NASA Mars News
We scraped the NASA Mars News Site and collected the latest News Title and Paragraph Text. Assigned the text to variables that one can reference later.
# Example:
news_title = "NASA's Next Mars Mission to Investigate Interior of Red Planet"
news_p = "Preparation of NASA's next spacecraft to Mars, InSight, has ramped up this summer, on course for launch next May from Vandenberg Air Force Base in central California -- the first interplanetary launch in history from America's West Coast."2. JPL Mars Space Images - Featured Image
We visited the url for JPL Featured Space Image here. Here we
used 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.
# Example:
featured_image_url = 'https://www.jpl.nasa.gov/spaceimages/images/largesize/PIA16225_hires.jpg'3. Mars Weather
Another important part of this assignment was to visit the Mars Weather twitter account here and scrape the latest Mars weather tweet from the page. We saved the tweet text for the weather report as a variable called mars_weather.
# Example:
mars_weather = 'Sol 1801 (Aug 30, 2017), Sunny, high -21C/-5F, low -80C/-112F, pressure at 8.82 hPa, daylight 06:09-17:55'