updated all transform functions. I think this went well,

I would not have been able to come up with the scale math on
my own.  I didn't really get stuck on this one.  However, I did
need to iterate through a few times and correct errors through
testing.

transform.py

@@ -6,38 +6,78 @@
 
 def maximum(data):
     "Returns the largest number in data"
-    raise NotImplementedError
+    highest = None
+    for number in data:
+        if highest is None:
+            highest = number
+        if number > highest:
+            highest = number
+    return highest
+    
 
 def minimum(data):
     "Returns the smallest number in data"
-    raise NotImplementedError
+    lowest = None
+    for number in data:
+        if lowest is None:
+            lowest = number
+        if number < lowest:
+            lowest = number
+    return lowest
 
 def bounds(data):
     "Returns a list of the smallest and largest numbers in data"
-    raise NotImplementedError
+    highest = maximum(data)
+    lowest = minimum(data)
+    return [lowest, highest]
 
 def clamp(value, low, high):
     """Clamps a value to a range from low to high. 
     Returns value if it is between low and high.
     If value is lower than low, returns low. If value is higher than high, returns high.
     """
-    raise NotImplementedError
+       
+    if value < low:
+        return low
+    elif value > high:
+        return high
+    else:
+        return value
 
 def ratio(value, start, end):
     """Returns a number from 0.0 to 1.0, representing how far along value is from start to end.
     The return value is clamped to [0, 1], so even if value is lower than start, the return 
     value will not be lower than 0.0.
     """
-    raise NotImplementedError
+    number = (value-start)/(end-start)
+
+    number = clamp(number, 0.0, 1.0)
+    return number
+
 
 def scale(value, domain_min, domain_max, range_min, range_max):
     "Given a value within a domain, returns the scaled equivalent within range."
-    raise NotImplementedError
+    scale = range_min + ((ratio(value, domain_min, domain_max))*(range_max - range_min))
+    
+    return scale
 
 def get_x_values(points):
     "Returns the first value for each point in points."
-    raise NotImplementedError
+    x_list = []
+    for point in points:
+        
+        x = point[0]
+        x_list.append (x)
+    return x_list
+
 
 def get_y_values(points):
     "Returns the second value for each point in points."
-    raise NotImplementedError
+    y_list = []
+    for point in points:
+        
+        y = point[1]
+        y_list.append (y)
+    return y_list
+
+