lab-numpy

your-code/main.py

@@ -1,68 +1,94 @@
 #1. Import the NUMPY package under the name np.
 
+import numpy as np
 
 
 #2. Print the NUMPY version and the configuration.
 
+print(np.__version__)
+#1.26.1
+print(np.show_config())
 
 
 #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?
 
+        # Method 1:
+a = np.random.random((2, 3, 5))
+        # Method 2:
+# a = np.random.rand(2, 3, 5)
+        # Method 3:
+# a = np.random.randn(2, 3, 5)
 
 
 #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?
-
-
-
+if a.size == b.size:
+        print("Both arrays have the same size")
+else:
+        print("These arrays have different sizes")
 
 #8. Are you able to add a and b? Why or why not?
 
-
+try:
+        print(a + b)
+except ValueError:
+        print("The sum is not possible because these arrays have different shapes")
+
 
 #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))
 
 #10. Try to add a and c. Now it should work. Assign the sum to varialbe "d". But why does it work now?
-
+try:
+        d = a + c
+        print("Sum was possible because a and c have the same shapes")
+except:
+        print("Sum was not possible. These arrays have different shapes")
 
 
 #11. Print a and d. Notice the difference and relation of the two array in terms of the values? Explain.
 
-
+print(a)
+print(d)
+print("d is the same as a, but every element of the d array is one int higher. That's because every element of c was 1")
 
 
 #12. Multiply a and c. Assign the result to e.
 
-
+e = a * c
 
 #13. Does e equal to a? Why or why not?
 
-
+if e.all() == a.all():
+        print("These arrays are the same. e array is the result of multipling the array a to an array of 1, which equals a")
 
 
 #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.amax(d)
+d_min = np.amin(d)
+d_mean = np.mean(d)
+print(f"The max value of d is {d_max}, the min is {d_min}, and the mean 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])
 
 
 """
@@ -75,8 +101,20 @@
 Note: you don't have to use Numpy in this question.
 """
 
-
-
+for i in range(2): #d[0] o d[1]
+        for j in range(3): #d[0][0] o d[0][1] o d[0][2] o d[1][0] o d[1][1] o d[1][2]
+                for k in range(5): #d[0][0][0] o d[0][0][1] o d[0][0][2] o d[0][0][3] o d[0][0][0][4]...
+                        if d_min < d[i][j][k] < d_mean:
+                                f[i][j][k] = 25
+                        if d_mean < d[i][j][k] < d_max:
+                                f[i][j][k] = 75
+                        if d_mean == d[i][j][k]:
+                                f[i][j][k] = 50
+                        if  d_min == d[i][j][k]:
+                                f[i][j][k] = 0
+                        if  d_max == d[i][j][k]:
+                                f[i][j][k] = 100
+f
 
 """
 #17. Print d and f. Do you have your expected f?
@@ -98,6 +136,9 @@
         [ 75.,  75.,  75.,  75.,  75.],
         [ 25.,  75.,   0.,  75.,  75.]]])
 """
+print(d)
+print(d_min, d_mean, d_max)
+print(f)
 
 
 """
@@ -111,4 +152,19 @@
         [ 'D',  'D',  'D',  'D',  'D'],
         [ 'B',  'D',   'A',  'D', 'D']]])
 Again, you don't need Numpy in this question.
-"""
+"""
+g = f.astype('object') 
+for i in range(2):
+        for j in range(3):
+                for k in range(5):
+                        if d_min < d[i][j][k] < d_mean:
+                                g[i][j][k] = "B"
+                        if d_mean < d[i][j][k] < d_max:
+                                g[i][j][k] = ("D")
+                        if d_mean == d[i][j][k]:
+                                g[i][j][k] = "C"
+                        if  d_min == d[i][j][k]:
+                                g[i][j][k] = "A"
+                        if  d_max == d[i][j][k]:
+                                g[i][j][k] = "E"
+print(g)