Activity 25 - Stocks 📈

Create a new file activity25-stocks.py to save to your cs100/ch5 folder.

1. Copy and paste the following code to your file, just underneath your answers to the previous questions.

   import math
   import turtle
   import urllib.request
      
   # compute and return the mean of a given list
   def mean(alist):
       mean = sum(alist) / len(alist)
       return mean
      
   # compute and return the standard deviation of a given list
   def standardDev(alist):
       theMean = mean(alist)    
       sum = 0
       for item in alist:
           difference = item - theMean
           diffsq = difference ** 2
           sum = sum + diffsq
              
       sdev = math.sqrt(sum/(len(alist)-1))
       return sdev
      
   # compute and return the Pearson's correlation coefficient between two lists
   def correlation(xlist, ylist):
       xbar = mean(xlist)
       ybar = mean(ylist)
       xstd = standardDev(xlist)
       ystd = standardDev(ylist)
       num = 0.0
       for i in range(len(xlist)):
           num = num + (xlist[i]-xbar) * (ylist[i]-ybar)
       corr = num / ((len(xlist)-1) * xstd * ystd) 
       return corr
      
   # given two lists, plot the correlation between them
   def plotCorrelation(xlist, ylist):
       wn = turtle.Screen()
       minX = min(xlist)
       minY = min(ylist)
       maxX = max(xlist)
       maxY = max(ylist)
       wn.setworldcoordinates(minX, minY, maxX, maxY)
          
       t = turtle.Turtle()
       t.speed('fastest')
       turtle.tracer(0, 0)
          
       for i in range(0, len(xlist)-1):
           t.up()
           t.goto(xlist[i], ylist[i])
           t.down()
           t.dot()
              
       wn.exitonclick()
     
   # open two CSV files from the internet to read them (without downloading them locally)
   url1 = urllib.request.urlopen("http://csweb.wooster.edu/hguarnera/cs100/assignments/AMZN.csv")
   url2 = urllib.request.urlopen("http://csweb.wooster.edu/hguarnera/cs100/assignments/AAPL.csv")
      
   # get rid of header rows from CSV files
   amazonTable = url1.readlines()
   appleTable = url2.readlines()
      
   # use list comprehension to parse file from website as bytestring into a list of list of strings
   amazonStocks = [line.decode("utf-8").split(',') for line in amazonTable[1:] ]
   appleStocks = [line.decode("utf-8").split(',') for line in appleTable[1:] ]
      
   # use list comprehension to form a list of just closing price as a floating point number
   amazonClose = [ float(amazonStocks[i][4]) for i in range( len(amazonStocks) )]
   appleClose = [ float(appleStocks[i][4]) for i in range( len(appleStocks) )]
      
   # TODO: add code here to answer next questions (hint: you only need 2-3 lines total!)
   

2. Add code to print out Pearson’s correlation coefficient between amazonClose (the closing price of Amazon’s stock over the last 10 years), and appleClose (the closing price of Apple’s stock over the last 10 years).

3. Add code to plot the correlation between amazonClose and appleClose

4. What does the correlation mean? If Apple’s stock price goes up, is it likely that Amazon’s stock price will go up? Or down? Write your answer as a comment.

If you finish early

1. Add code to read data from http://csweb.wooster.edu/hguarnera/cs100/assignments/NYT.csv which has the last 10 years worth of stock information for the New York Time’s. How does NYT correlate with Apple and Amazon?

2. Here is list a=["1", "2", "3", "4", "5"]. Use list comprehension to create list b consisting of the integers [1, 2, 3, 4, 5]. Print the list.

3. Use list comprehension to create the list c consisting of all odd numbers within the range [0,20]. Print the list.

4. Use list comprehension to create the list d consisting of all numbers divisible by 3 within the range [0, 100]. Print the list.

How to submit

Submit your working python file to Moodle.