diff --git a/your-code/main.py b/your-code/main.py
index 78c792b..9737cbc 100644
--- a/your-code/main.py
+++ b/your-code/main.py
@@ -1,66 +1,120 @@
 #1. Import the NUMPY package under the name np.
+import numpy as np
+import random as rd
+
 
 
 
 #2. Print the NUMPY version and the configuration.
+print(np.__version__)
+print(np.show_config())
+
 
 
 
 #3. Generate a 2x3x5 3-dimensional array with random values. Assign the array to variable "a"
+a=np.array([[[rd.randint(0,101) for k in range(5)] for j in range(3)] for i in range(2)]) #from Python List to Numpy Array
+
 # Challenge: there are at least three easy ways that use numpy to generate random arrays. How many ways can you find?
+a1=np.random.randint(101, size =(2, 3, 5)) #np.random.randint
+a2=np.random.random((2,3,5)) #np.random.random
+
 
 
 
 #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(b)
+
 
 
 
 #7. Do a and b have the same size? How do you prove that in Python code?
+print("Do a and b have the same size?")
+print(a.size==b.size)
+print(f"a has size: {a.size}")
+print(f"b has size: {b.size}")
 
 
 
 
 #8. Are you able to add a and b? Why or why not?
+#No, because they have same size but not same shape
+print(f"a has shape: {a.shape}")
+print(f"b has shape: {b.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".
+c=b.transpose(1,2,0)
+print(f"c has shape: {c.shape}")
+print(c)
+
 
 
 
 #10. Try to add a and c. Now it should work. Assign the sum to varialbe "d". But why does it work now?
+d=a+c
+print(d)
+#now it works because a and c has the same shape
+
 
 
 
 #11. Print a and d. Notice the difference and relation of the two array in terms of the values? Explain.
+print("a numpy:")
+print(a)
+print("d numpy:")
+print(d)
+#d is the sum of a and c. since every element of c is a 1, the diifferece between an element of d and the element of a with the same coordinates is always 1
 
 
 
 
 #12. Multiply a and c. Assign the result to e.
+e=a*c
+print(e)
+
 
 
 
 #13. Does e equal to a? Why or why not?
+print("Does e equal to a?")
+#print(e==a)
+print(np.array_equal(e,a))
+# e equals to a because it was obtaining multypling the elements of a for the elements of c, which are all 1s
 
 
 
 
 #14. Identify the max, min, and mean values in d. Assign those values to variables "d_max", "d_min", and "d_mean"
+d_max = np.max(d)
+print(f"max value in d is {d_max}")
+
+d_min = np.min(d)
+print(f"min value in d is {d_min}")
+
+d_mean = np.mean(d)
+print(f"mean value of d is {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`.
+f = np.empty((2,3,5))
 
 
 
@@ -74,9 +128,23 @@
 In the end, f should have only the following values: 0, 25, 50, 75, and 100.
 Note: you don't have to use Numpy in this question.
 """
-
-
-
+for i in range(len(d)):
+    for j in range(len(d[i])):
+        for k in range(len(d[i,j])):
+            d_elem=d[i,j,k]
+            if d_elem>d_min and d_elem<d_mean:
+                f[i,j,k]=25
+            elif d_elem>d_mean and d_elem<d_max:
+                f[i,j,k]=75
+            elif d_elem ==d_mean:
+                f[i,j,k]=50
+            elif d_elem == d_min:
+                f[i,j,k]=0
+            elif d_elem == d_max:
+                f[i,j,k]=100
+
+
+            
 
 """
 #17. Print d and f. Do you have your expected f?
@@ -98,6 +166,13 @@
         [ 75.,  75.,  75.,  75.,  75.],
         [ 25.,  75.,   0.,  75.,  75.]]])
 """
+print(d)
+print(f"max value in d is {d_max}")
+print(f"min value in d is {d_min}")
+print(f"mean value of d is {d_mean}")
+print(f)
+
+
 
 
 """
@@ -111,4 +186,22 @@
         [ 'D',  'D',  'D',  'D',  'D'],
         [ 'B',  'D',   'A',  'D', 'D']]])
 Again, you don't need Numpy in this question.
-"""
\ No newline at end of file
+"""
+f_letters = np.empty((2,3,5),str)
+
+for i in range(len(d)):
+    for j in range(len(d[i])):
+        for k in range(len(d[i,j])):
+            d_elem=d[i,j,k]
+            if d_elem>d_min and d_elem<d_mean:
+                f_letters[i,j,k]='B'
+            elif d_elem>d_mean and d_elem<d_max:
+                f_letters[i,j,k]='D'
+            elif d_elem ==d_mean:
+                f_letters[i,j,k]='C'
+            elif d_elem == d_min:
+                f_letters[i,j,k]='A'
+            elif d_elem == d_max:
+                f_letters[i,j,k]='E'
+
+print(f_letters)
\ No newline at end of file