Web scraping using Jupyter Notebook, Python, Pandas, Splinter and HTML parsing with Beautiful Soup.
I parsed the Mars News website by using Splinter and HTML parsing with Beautiful Soup. I then scraped the titles and preview texts of the 20 most recent Mars news articles and converted them into a Python data structure. The data is then stored into MongoDB.
The data was retrieved from the Mars Temperature Data site and the data was stored into a pandas DataFrame.
After that, I answered the following questions with related visualizations using Pandas:
- How many months exist on Mars?
- How many Martian (and not Earth) days worth of data exist in the scraped dataset?
- What are the coldest and the warmest months on Mars (at the location of Curiosity)?
- Which months have the lowest and the highest atmospheric pressure on Mars?
- About how many terrestrial (Earth) days exist in a Martian year? (using a visual estimate)