We scraped the title and preview text from the latest news articles on the landing page of https://redplanetscience.com/, and stored this data in a python dictionary.

We scraped the data table on Mars weather from https://data-class-mars-challenge.s3.amazonaws.com/Mars/index.html and stored it in a Pandas dataframe.

Then we analyzed this data, determining:

1. How many months there are in a Mars year
2. The Mars months with the hottest and coldest temperatures on average
3. The Mars months with the highest and lowest atmospheric pressures on average
4. An estimate for the length of a Mars year in Earth days

We produced visualizations to accompany these analyses, and finally exported the data into a csv file.