Python

1. Write a Python class calculating the mean value of numbers being passed one by one to the class. It should have a put(x) method that feeds it a number and a get() method returning the mean value of the numbers passed so far.
2. Write another class that calculates in the same way an estimate of the population variance. You can use the online algorithm, defined as follows. Given samples \(x_1,\ldots,x_n\), start with setting \(M_1 = 0\) and \(\overline x_1 = x_1\). For each \(x_k\) with \(k > 1\), set \[\overline x_k = \overline x_{k-1} + \frac{x_k - \overline x_{k - 1}}{k}\,,\] and \[M_k = M_{k-1} + (x_k - \overline x_{k-1})(x_k - \overline x_k)\,.\] The estimated population variance is then \(\sigma_k^2 = M_k/k\).
3. Advanced: Write a framework class that has an append(o) method that takes an object like the ones above (i.e. ones that have a put method to process data and a get method to retrieve a result). It should itself have a put(x) method, which will pass the x on to all the objects o passed to it via append and a get method which will return a list containing the results of the get calls of all the contained objects.

HTML

1. Write a simple HTML page containing
   • A number of headings.
   • A list.
   • One ore more paragraphs.
   • An image.
   • A table.
   • One or more links.

You can refer to w3's HTML tutorial for reference.

Web Scraping

1. Use the beautifulsoup python package to load your page. Write code to navigate it, extracting all the elements mentioned above.
2. Choose any web-site containing information of interest to you. Read its terms of service and robots.txt to inform yourself about its rules concerning scraping. Using the scrapy python package together with beautifulsoup, write a spider that navigates through a small number of pages on that site, extracting relevant information and saving it to a .csv file.