1)  The average number of sentences per word over time

Do this two ways:

First, using a simple regex that splits on puntuation. Second, using the natural language toolkit's sentence tokenizer.
2)  The average number of unique words per 100 words over time

    - remove common words ( see the lecture slide for a list )

Do this two ways:

First: assume that different words are all unique, even if they share suffixes ( like run and running )

Second: using the stemming code from the NLTK.

Make sure that you sort the speeches by their date, and write the data into a text file with two columns: date and statistic.

EC) Build a word cloud, as seen in the slides from lectures 11 and 12

Part 2: Collect an interesting web statistic.

Use urlweb and a website of your choice to collect a statistic. Write a one paragraph description of your statistic at the top of the code
file.

Examples include sports game data, weather statistics, name statistics, etc.