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The goal of the project is to scrape the multiple web sources with information and images about Mars and NASA, store it in a database and finally display it in a customized web site.

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web-scraping-challenge

Jamie Tan submission on web scraping challenge

Background of the challenge:

This challenge requires us to build a web application that scrapes various websites for data related to the Mission to Mars and displays the information in a single HTML page.

  • Web scraping is performed using Jupyter Notebook, BeautifulSoup, Pandas and Requests/Splinter
  • Data visualisation via HTML using MongoDB and Flask application

Final application:

Fig2

Submission (within 'Mission to Mars' folder):

  1. Jupyter Notebook (filename: mission_to_mars.ipynb)
  2. Python scrape function (filename: scrape_mars.py)
  3. Flask app to query MongoDB and pass data into a HTML template (filename: app.py)
  4. HTML template (filename: index.html; in folder 'templates')
  5. Screenshots of HTML page and final application (in folder 'screenshots')

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The goal of the project is to scrape the multiple web sources with information and images about Mars and NASA, store it in a database and finally display it in a customized web site.

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