Although I considered adapting ‘Hungry, Hungry Hippos’ for Turtle, I decided that analyzing data would be more useful for me. I went to https://www.kaggle.com and downloaded a dataset of the most backed projects from Kickstarter. I’ve been working on cleaning up the data so that I can break down the success stories by category, study the relationship between goals and amount pledged, and how much each backer pledged on average. I will have to think of other ways to use the data and create a user interface, but I am just getting started:

Right now, I have a piece of code that calculates and displays the percentages of each category over 0%.

categories=set(categories)
for category in categories:
  count=0
  for line in mb_list:
    if line[1] == category:
      count+=1
    else:
      continue
    percentage = int(100*count/len(mb_list))
  if percentage>0:
    print(category + "\t" + str(percentage) + "%")
  else:
    continue

It is based off the final part of the CSV 1 homework. That code works for both the domestic and foreign datasets.

Before I go any further, I need to decide whether to include the titles of the projects. They certainly won’t make a neat table, but it seems that ship might have sailed anyways. It might be nice to have a function that allows the user to search through the title for keywords. After that, I will work to design a bunch of different ways to use the data.

Milestones

• Gather data
• Clean data
• Decide whether to use data with titles
• Create main menu
• Re-read chapter on regular expressions
• Think of different data manipulations
• Compile a dictionary
• Create functions that use the dictionary
• Code data functions
• Make sure data functions pass into main
• Figure out a good application for histograms