Chapter 3: Web Scraping and Interactive Visualizations

Activity 3: Web Scraping with Jupyter Notebooks

1. For this page, the data can be scraped using the following code snippet:

   data = []
   for i, row in enumerate(soup.find_all('tr')): row_data = row.find_all('td')
   try:
   d1, d2, d3 = row_data[1], row_data[5], row_data[6] d1 = d1.find('a').text
   d2 = float(d2.text)
   d3 = d3.find_all('span')[1].text.replace('+', '') data.append([d1, d2, d3])
   except:
   print('Ignoring row {}'.format(i)

2. In the lesson-3-workbook.ipynb Jupyter Notebook, scroll to Activity A: Web scraping with Python.
3. Set the url variable and load an IFrame of our page in the notebook by running the following code:

   url = 'http://www.worldometers.info/world-population/ population-by-country/'
   IFrame(url, height=300, width=800)

   The page should load in the notebook. Scrolling down, we can see the Countries in the world by population heading and...