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:
- How many months there are in a Mars year
- The Mars months with the hottest and coldest temperatures on average
- The Mars months with the highest and lowest atmospheric pressures on average
- 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.