Utilizing webscraping tools, scrapped and analyzed information from two websites. This project consisted of two parts.
Part 1: Scraped Titles and Preview Text from Red Planet Science, cleaning the data and importing into a list.
Part 1 Notebook
Part 2 Scrapped and analyzed Mars Weather Data from an AWS Warehouse with the goal of finding the coldest Month on Mars, Average Atmospheric Pressure by Month, and Comparing how many Earth days is 1 Mars Year.
Part 2 Notebook
Plot 1 - Concluded on average the coldest tempature on Mars is in its third Month and the warmest month is the eight month.
Plot 2 - Verified the atmospheric pressure on Mars on average is lowest in the sixth month and highest in the ninth.
Plot 3 - The distance from peak to peak on Plot 3 is roughly 1425-750 Z(as shown on the graph), or 675 days. After reviewing on the internet 687 earth days are equal to 1 Mars year.
After compiling the data from the AWS Warehouse using beautiful soup it would be a more effective and quicker to read the dataframe using Pandas, we could skip steps 2-3 as the data would already be cleaned and in a dataframe.
Beautiful Soup - To scrape data from websites
Splinter - to establish and executable path within Jupyter
Jupyter Notebook
Matplotlib
Pandas