I made the functions in the transform.py file.

Checkpoint 2:
It went alright.  It definitely felt like a different type of thinking as before we focused on using the turtle in functions.  When I got stuck I made sure to take a break and come back to it.

transform.py

@@ -6,38 +6,69 @@
 
 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
+    return [minimum(data),maximum(data)]
 
 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:
+        number = low
+    elif high < value:
+        number = high
+    else:
+        number = value
+    return number
 
 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
+    num = (value-start)/(end-start)
+    out = clamp(num,0,1)
+    return out 
 
 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
+    r = ratio(value, domain_min, domain_max)
+    return range_min + r *(range_max - range_min)
 
 def get_x_values(points):
     "Returns the first value for each point in points."
-    raise NotImplementedError
+    xlist = []
+    for x in range(len(points)):
+        val = points[x][0]
+        xlist.append(val)
+    return xlist
+
 
 def get_y_values(points):
     "Returns the second value for each point in points."
-    raise NotImplementedError
+    ylist = []
+    for y in range(len(points)):
+        val = points[y][1]
+        ylist.append(val)
+    return ylist
+