This assignment consists of the following deliverables:
Deliverable 1: Scraped titles and previewed text from Mars news articles.
Deliverable 2: Scraped and analyzed Mars weather data, which exists in a table.
Requirements
Part 1: Scraped Titles and Previewed Text from Mars News
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Automated browsing (with Splinter) was used to visit the Mars news site, and the HTML code was extracted (with Beautiful Soup).
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The titles and preview text of the news articles were scraped and extracted.
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The scraped information was stored in the specified Python data structure—specifically, a list of dictionaries.
Part 2: Scrape and Analyze Mars Weather Data
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The HTML table was extracted into a Pandas DataFrame. Either Pandas or Splinter and Beautiful Soup were used to scrape the data. The columns have the correct headings and data types.
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The data was analyzed to answer the following questions:
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How many months exist on Mars?
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How many Martian days' worth of data are there?
The data was analyzed to answer the following questions, and a data visualization was created to support each answer:
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Which month, on average, has the lowest temperature? The highest?
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Which month, on average, has the lowest atmospheric pressure? The highest?
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How many terrestrial days exist in a Martian year? A visual estimate within 25% was made.
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The DataFrame was exported into a CSV file.