only did up to 16, after if have time will continue

your-code/main.py

@@ -1,69 +1,85 @@
 #1. Import the NUMPY package under the name np.
 
-
+import numpy as np   
 
 #2. Print the NUMPY version and the configuration.
 
-
+print(np.__version__)
 
 #3. Generate a 2x3x5 3-dimensional array with random values. Assign the array to variable "a"
 # Challenge: there are at least three easy ways that use numpy to generate random arrays. How many ways can you find?
 
+a = np.random.randint(10, size = (2, 3, 5))
 
+#a = [1, 2, 4]
+#print(a)
 
 #4. Print a.
-
-
+print(a)
 
 #5. Create a 5x2x3 3-dimensional array with all values equaling 1.
 #Assign the array to variable "b"
-
-
+b = np.ones((5,2,3))
 
 #6. Print b.
-
-
+print("\n6-------------------------------")
+print(b)
 
 #7. Do a and b have the same size? How do you prove that in Python code?
-
-
+print("\n7-------------------------------")
+print(a.size == b.size)
 
 
 #8. Are you able to add a and b? Why or why not?
+print("\n8-------------------------------")
+#result = np.add(a, b) 
+#result
 
-
+#not able to do it because they don't have the same shape
 
 #9. Transpose b so that it has the same structure of a (i.e. become a 2x3x5 array). Assign the transposed array to varialbe "c".
-
-
+print("\n9-------------------------------")
+c = b.transpose(1,2,0)
+print(c)
+print(a.shape)
+print(c.shape)
 
 #10. Try to add a and c. Now it should work. Assign the sum to varialbe "d". But why does it work now?
-
-
+print("\n10-------------------------------")
+d = np.add(a, c) 
+print("It works because we have the same shape now")
 
 #11. Print a and d. Notice the difference and relation of the two array in terms of the values? Explain.
-
-
+print("\n11-------------------------------")
+print(a)
+print(d)
+print("We are adding array c + array a so it's similar about size, shape but values no")
 
 
 #12. Multiply a and c. Assign the result to e.
-
-
+print("\n12-------------------------------")
+e = np.multiply(a,c)
+print(e)
 
 #13. Does e equal to a? Why or why not?
+print("\n13-------------------------------")
 
-
-
+print(e == a)
 
 #14. Identify the max, min, and mean values in d. Assign those values to variables "d_max", "d_min", and "d_mean"
-
-
-
+print("\n14-------------------------------")
+d_max = np.max(d)
+print(d_max)
+d_min = np.min(d)
+print(d_min)
+d_mean = np.mean(d)
+print(d_mean)
 
 #15. Now we want to label the values in d. First create an empty array "f" with the same shape (i.e. 2x3x5) as d using `np.empty`.
-
-
-
+print("\n15-------------------------------")
+f = np.empty((2,3,5), like = d)
+print(f)
+print(d)
 
 """
 #16. Populate the values in f. For each value in d, if it's larger than d_min but smaller than d_mean, assign 25 to the corresponding value in f.

your-code/tempCodeRunnerFile.py

@@ -0,0 +1 @@
+numpy