I am not sure if I did submit checkpoint 1. I was very confused and unsure what I am supposed to do. I guessed that I have to write down the steps to create a scatter plot, but I realized that the process is not as intuitive as I assumed. I know I did not do well for checkpoint 1, I still think of how I would create scatter plot on the paper with pencil.

transform.py

@@ -6,38 +6,64 @@
 
 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 low < value and value < high:
+        return value 
+    if value <= low:
+        return low
+    if value >= high:
+        return high
+
 
 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
+    return clamp(((value-start)/(end-start)), 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
+    return ratio(value, domain_min, domain_max)*(range_max - range_min)
 
 def get_x_values(points):
     "Returns the first value for each point in points."
-    raise NotImplementedError
+    onlyx=[]
+    for point in points:
+        onlyx.append(point[0])
+    return onlyx
 
 def get_y_values(points):
     "Returns the second value for each point in points."
-    raise NotImplementedError
+    onlyy=[]
+    for point in points:
+        onlyy.append(point[1])
+    return onlyy