Assignment 4

Part1

I had some issues using feedparser and python for the code in the book. Even when I used the code from the book I got an error which was not able to parse.

Part2

As a group we have decided to present certain data which will show us those who died or survived the titanic! The X axis is sex of the passenger, the Y axis is the class of the passenger (1st, 2nd, 3rd, and crew), and blue is survived and red is did not survive. The data shows something that most people already know, but it is still interesting seeing the clustering of the data proving the point. That being, most men died and almost all of women 1st class passengers survived.

Another way we decided to cluster the data was by age and sex of the passenger, and whether or not they survived. What makes this more interesting is the fact that a fair amount of female children did not survive. The upper-right area is female child passengers, and red (did not survive) is the dominant color in that area. You can manipulate the visualizations in many ways, in order to discover interesting trends in the data set.

Part 3

For this part I decided to look up the number of deaths in Iraq by month. This is what I found.

I was also able to determine if they were from other coalition forces. Here are the number of UK military that died as a result of combat related deaths.

Assignment 3

In creating a recommendation system with python we began by taking some of the recommender we compiled a program that will recommend an artist based on the band name entered.
This is a portion of the recommender:

import pylastkey = 'b8a9a83c0e60d30d237eea0dcdcf055a'secret = 'a0a206e56d580a78e8715155106371fa'sk = ''bandName=input('Please enter band name:')
artist = pylast.Artist(bandName, key, secret, sk)
similar = artist.get_similar()print similar

tracks = artist.get_top_tracks()
print "\n"print "\n"print "\n"print tracks