Again, following along with the live coding video was helpful. I did have some issue with the superturtle, it causes an error when testing the lab.

scatterplot.py

@@ -4,7 +4,6 @@
 # Uses lots of helper functions in other modules to draw a scatter plot.
 
 from turtle import *
-from superturtle.movement import no_delay
 import constants
 from generate_data import generate_data
 from ticks import get_tick_values
@@ -35,6 +34,20 @@ def draw_scatterplot(data, size=5, color="black"):
 
 def draw_axes(data):
     "Draws the scatter plot's axes."
+    draw_x_axis()
+    x_values = get_x_values(data)
+    xmin, xmax = bounds(x_values)
+    ticks = get_tick_values(xmin, xmax)
+    for tick in ticks:
+        screen_x_position = scale(tick, xmin, xmax, 0, constants. PLOT_WIDTH)
+        draw_x_tick(screen_x_position, tick)
+    draw_y_axis
+    y_values = get_y_values(data)
+    ymin, ymax = bounds(y_values)
+    ticks = get_tick_values(ymin, ymax)
+    for tick in ticks:
+        screen_y_position = scale(tick, ymin, ymax, 0, constants. PLOT_HEIGHT)
+        draw_y_tick(screen_y_position, tick)
 
 def draw_points(data, color, size):
     "Draws the scatter plot's points."

transform.py

@@ -26,30 +26,43 @@ def minimum(data):
 
 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:
+        return value
+    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
+    unclamped_ratio = (value - start) / (end - start)
+    return clamp(unclamped_ratio, 0, 1)
 
 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
+    x_values = []
+    for x, y in points:
+        x_values.append(x)
+    return x_values
 
 def get_y_values(points):
     "Returns the second value for each point in points."
-    raise NotImplementedError
+    y_values = []
+    for x, y in points:
+        y_values.append(y)
+    return y_values