diff --git a/your-code/main.ipynb b/your-code/main.ipynb
index 46f5aa1..623e1b7 100644
--- a/your-code/main.ipynb
+++ b/your-code/main.ipynb
@@ -16,11 +16,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
-    "### [your code here]\n"
+    "import numpy as np"
    ]
   },
   {
@@ -34,11 +34,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 2,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2.2.4\n"
+     ]
+    }
+   ],
    "source": [
-    "### [your code here]\n"
+    "print(np.version.version)"
    ]
   },
   {
@@ -51,11 +59,62 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "### [your code here]\n"
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "A is an array of the following numbers: \n",
+      "3\n",
+      "[[[4 2 8 9 9]\n",
+      "  [9 0 6 6 8]\n",
+      "  [3 3 4 8 5]]\n",
+      "\n",
+      " [[9 3 5 4 4]\n",
+      "  [8 1 4 5 5]\n",
+      "  [4 2 3 2 8]]]\n",
+      "A2 is an array of the following numbers: \n",
+      "3\n",
+      "[[[0.58705264 0.10439797 0.10987155 0.87880466 0.19634468]\n",
+      "  [0.01690683 0.90795606 0.46336664 0.29963763 0.22100271]\n",
+      "  [0.64851394 0.07692552 0.87480797 0.77126095 0.9695411 ]]\n",
+      "\n",
+      " [[0.40088819 0.1784533  0.48114638 0.22217642 0.75097671]\n",
+      "  [0.7116865  0.12059496 0.32261741 0.4235361  0.78969466]\n",
+      "  [0.17073756 0.11060123 0.13605561 0.33102555 0.2068833 ]]]\n",
+      "A3 is an array of the following numbers: \n",
+      "3\n",
+      "[[[ 0.5121003  -0.46159845  1.61143687  0.40841123  0.20668906]\n",
+      "  [ 0.98682028 -0.47623397 -1.72452115  0.03894566  0.12958093]\n",
+      "  [ 1.62019624  0.92710677 -0.18568419 -1.70274415  1.14417101]]\n",
+      "\n",
+      " [[ 0.47493394 -2.08219872 -0.04255597  0.17259219 -0.77573742]\n",
+      "  [-1.19144815  0.82735278  1.83961642  1.30307053  1.66074257]\n",
+      "  [ 0.3060472  -0.87736169 -1.96939736  0.46438388 -0.84827314]]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "from random import randint, random\n",
+    "#method 1\n",
+    "a = np.random.randint(10, size = (2,3,5))\n",
+    "print(\"A is an array of the following numbers: \")\n",
+    "print(a.ndim)\n",
+    "print(a)\n",
+    "\n",
+    "#method 2\n",
+    "a2 = np.random.rand(2,3,5)\n",
+    "print(\"A2 is an array of the following numbers: \")\n",
+    "print(a2.ndim)\n",
+    "print(a2)\n",
+    "\n",
+    "#method 3\n",
+    "a3 = np.random.randn(2,3,5)\n",
+    "print(\"A3 is an array of the following numbers: \")\n",
+    "print(a3.ndim)\n",
+    "print(a3)"
    ]
   },
   {
@@ -68,11 +127,41 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "### [your code here]\n"
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[[4 2 8 9 9]\n",
+      "  [9 0 6 6 8]\n",
+      "  [3 3 4 8 5]]\n",
+      "\n",
+      " [[9 3 5 4 4]\n",
+      "  [8 1 4 5 5]\n",
+      "  [4 2 3 2 8]]]\n",
+      "[[[0.58705264 0.10439797 0.10987155 0.87880466 0.19634468]\n",
+      "  [0.01690683 0.90795606 0.46336664 0.29963763 0.22100271]\n",
+      "  [0.64851394 0.07692552 0.87480797 0.77126095 0.9695411 ]]\n",
+      "\n",
+      " [[0.40088819 0.1784533  0.48114638 0.22217642 0.75097671]\n",
+      "  [0.7116865  0.12059496 0.32261741 0.4235361  0.78969466]\n",
+      "  [0.17073756 0.11060123 0.13605561 0.33102555 0.2068833 ]]]\n",
+      "[[[ 0.5121003  -0.46159845  1.61143687  0.40841123  0.20668906]\n",
+      "  [ 0.98682028 -0.47623397 -1.72452115  0.03894566  0.12958093]\n",
+      "  [ 1.62019624  0.92710677 -0.18568419 -1.70274415  1.14417101]]\n",
+      "\n",
+      " [[ 0.47493394 -2.08219872 -0.04255597  0.17259219 -0.77573742]\n",
+      "  [-1.19144815  0.82735278  1.83961642  1.30307053  1.66074257]\n",
+      "  [ 0.3060472  -0.87736169 -1.96939736  0.46438388 -0.84827314]]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(a)\n",
+    "print(a2)\n",
+    "print(a3)"
    ]
   },
   {
@@ -85,11 +174,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
-    "### [your code here]\n"
+    "b = np.ones((5,2,3))\n"
    ]
   },
   {
@@ -102,11 +191,35 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "B is an array of the following numbers: \n",
+      "[[[1. 1. 1.]\n",
+      "  [1. 1. 1.]]\n",
+      "\n",
+      " [[1. 1. 1.]\n",
+      "  [1. 1. 1.]]\n",
+      "\n",
+      " [[1. 1. 1.]\n",
+      "  [1. 1. 1.]]\n",
+      "\n",
+      " [[1. 1. 1.]\n",
+      "  [1. 1. 1.]]\n",
+      "\n",
+      " [[1. 1. 1.]\n",
+      "  [1. 1. 1.]]]\n"
+     ]
+    }
+   ],
    "source": [
-    "### [your code here]\n"
+    "### [your code here]\n",
+    "print(\"B is an array of the following numbers: \")\n",
+    "print(b)"
    ]
   },
   {
@@ -119,11 +232,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 15,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "A and B have the same number of dimensions\n"
+     ]
+    }
+   ],
    "source": [
-    "### [your code here]\n"
+    "if a.ndim == b.ndim:\n",
+    "    print(\"A and B have the same number of dimensions\")\n",
+    "elif a.shape == b.shape:\n",
+    "    print(\"A and B have the same shape\")\n",
+    "elif a.size == b.size:\n",
+    "    print(\"A and B have the same size\")"
    ]
   },
   {
@@ -136,11 +262,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "ValueError",
+     "evalue": "operands could not be broadcast together with shapes (2,3,5) (5,2,3) ",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
+      "\u001b[31mValueError\u001b[39m                                Traceback (most recent call last)",
+      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[16]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[38;5;28mprint\u001b[39m(\u001b[43ma\u001b[49m\u001b[43m \u001b[49m\u001b[43m+\u001b[49m\u001b[43m \u001b[49m\u001b[43mb\u001b[49m)\n",
+      "\u001b[31mValueError\u001b[39m: operands could not be broadcast together with shapes (2,3,5) (5,2,3) "
+     ]
+    }
+   ],
    "source": [
-    "### [your code here]\n"
+    "# We are not able to add a and b as they are not the same shape "
    ]
   },
   {
@@ -154,11 +292,53 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 20,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "### [your code here]\n"
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[[1. 1. 1.]\n",
+      "  [1. 1. 1.]]\n",
+      "\n",
+      " [[1. 1. 1.]\n",
+      "  [1. 1. 1.]]\n",
+      "\n",
+      " [[1. 1. 1.]\n",
+      "  [1. 1. 1.]]\n",
+      "\n",
+      " [[1. 1. 1.]\n",
+      "  [1. 1. 1.]]\n",
+      "\n",
+      " [[1. 1. 1.]\n",
+      "  [1. 1. 1.]]]\n",
+      "C is an array of the following numbers: \n",
+      "[[[1. 1. 1. 1. 1.]\n",
+      "  [1. 1. 1. 1. 1.]\n",
+      "  [1. 1. 1. 1. 1.]]\n",
+      "\n",
+      " [[1. 1. 1. 1. 1.]\n",
+      "  [1. 1. 1. 1. 1.]\n",
+      "  [1. 1. 1. 1. 1.]]]\n",
+      "[[[ 5.  3.  9. 10. 10.]\n",
+      "  [10.  1.  7.  7.  9.]\n",
+      "  [ 4.  4.  5.  9.  6.]]\n",
+      "\n",
+      " [[10.  4.  6.  5.  5.]\n",
+      "  [ 9.  2.  5.  6.  6.]\n",
+      "  [ 5.  3.  4.  3.  9.]]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "arrayb1d = np.array(b)\n",
+    "print(arrayb1d)\n",
+    "c = np.reshape(arrayb1d, (2,3,5))\n",
+    "print(\"C is an array of the following numbers: \")\n",
+    "print(c)\n",
+    "print(a + c)\n",
+    "\n"
    ]
   },
   {
@@ -171,11 +351,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
-    "### [your code here]\n"
+    "d = a + c\n"
    ]
   },
   {
@@ -188,12 +368,35 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "### [your code here]\n",
-    "\n"
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[[4 2 8 9 9]\n",
+      "  [9 0 6 6 8]\n",
+      "  [3 3 4 8 5]]\n",
+      "\n",
+      " [[9 3 5 4 4]\n",
+      "  [8 1 4 5 5]\n",
+      "  [4 2 3 2 8]]]\n",
+      "[[[ 5.  3.  9. 10. 10.]\n",
+      "  [10.  1.  7.  7.  9.]\n",
+      "  [ 4.  4.  5.  9.  6.]]\n",
+      "\n",
+      " [[10.  4.  6.  5.  5.]\n",
+      "  [ 9.  2.  5.  6.  6.]\n",
+      "  [ 5.  3.  4.  3.  9.]]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(a)\n",
+    "print(d)\n",
+    "\n",
+    "#D is an array of the same shape as A, with each value + 1, because the original array that we added to it (b) was an array of ones."
    ]
   },
   {
@@ -206,11 +409,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 24,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "### [your code here]\n"
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "E is an array created by multiplying A and C: \n",
+      "[[[4. 2. 8. 9. 9.]\n",
+      "  [9. 0. 6. 6. 8.]\n",
+      "  [3. 3. 4. 8. 5.]]\n",
+      "\n",
+      " [[9. 3. 5. 4. 4.]\n",
+      "  [8. 1. 4. 5. 5.]\n",
+      "  [4. 2. 3. 2. 8.]]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "e = a * c\n",
+    "print(\"E is an array created by multiplying A and C: \")\n",
+    "print(e)\n"
    ]
   },
   {
@@ -224,12 +444,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 28,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "E is the same as A, because c consists of ones only\n"
+     ]
+    }
+   ],
    "source": [
-    "### [your code here]\n",
-    "\n"
+    "if e.all() == a.all():\n",
+    "    print(\"E is the same as A, because c consists of ones only\")\n",
+    "else:\n",
+    "    print(\"E is not the same as A\")\n"
    ]
   },
   {
@@ -245,9 +475,24 @@
    "cell_type": "code",
    "execution_count": 32,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "### [your code here]\n",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Max value in d = 10.0\n",
+      "Min value in d = 1.0\n",
+      "Mean value in d = 6.033333333333333\n"
+     ]
+    }
+   ],
+   "source": [
+    "d_max = d.max()\n",
+    "print(\"Max value in d =\", d_max)\n",
+    "d_min = d.min()\n",
+    "print(\"Min value in d =\", d_min)\n",
+    "d_mean = d.mean()\n",
+    "print(\"Mean value in d =\", d_mean)\n",
     "\n"
    ]
   },
@@ -263,9 +508,18 @@
    "cell_type": "code",
    "execution_count": 33,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "F is an empy array of the shape 2x3x5\n"
+     ]
+    }
+   ],
    "source": [
-    "### [your code here]\n"
+    "f = np.empty((2,3,5))\n",
+    "print(\"F is an empy array of the shape 2x3x5\")\n"
    ]
   },
   {
@@ -287,11 +541,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [],
    "source": [
-    "### [your code here]\n"
+    "for i in range(d.shape[0]):\n",
+    "    for j in range(d.shape[1]):\n",
+    "        for k in range(d.shape[2]):\n",
+    "            # Get the current value\n",
+    "            value = d[i, j, k]\n",
+    "            \n",
+    "            # Apply conditions and update f\n",
+    "            if value > d_min and value < d_mean:\n",
+    "                f[i, j, k] = 25\n",
+    "            elif value > d_mean and value < d_max:\n",
+    "                f[i, j, k] = 75\n",
+    "            elif value == d_mean:\n",
+    "                f[i, j, k] = 50\n",
+    "            elif value == d_max:\n",
+    "                f[i, j, k] = 100\n",
+    "                \n"
    ]
   },
   {
@@ -325,11 +594,39 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "### [your code here]\n"
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "D array (original):\n",
+      "[[[ 5.  3.  9. 10. 10.]\n",
+      "  [10.  1.  7.  7.  9.]\n",
+      "  [ 4.  4.  5.  9.  6.]]\n",
+      "\n",
+      " [[10.  4.  6.  5.  5.]\n",
+      "  [ 9.  2.  5.  6.  6.]\n",
+      "  [ 5.  3.  4.  3.  9.]]]\n",
+      "\n",
+      "F is an array of the following numbers:\n",
+      "[[[ 25.  25.  75. 100. 100.]\n",
+      "  [100.   0.  75.  75.  75.]\n",
+      "  [ 25.  25.  25.  75.  25.]]\n",
+      "\n",
+      " [[100.  25.  25.  25.  25.]\n",
+      "  [ 75.  25.  25.  25.  25.]\n",
+      "  [ 25.  25.  25.  25.  75.]]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"\\nD array (original):\")\n",
+    "print(d)\n",
+    "print(\"\\nF is an array of the following numbers:\")\n",
+    "print(f)"
    ]
   },
   {
@@ -350,11 +647,59 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "### [your code here]"
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[[ 5.  3.  9. 10. 10.]\n",
+      "  [10.  1.  7.  7.  9.]\n",
+      "  [ 4.  4.  5.  9.  6.]]\n",
+      "\n",
+      " [[10.  4.  6.  5.  5.]\n",
+      "  [ 9.  2.  5.  6.  6.]\n",
+      "  [ 5.  3.  4.  3.  9.]]]\n",
+      "[[[ 25.  25.  75. 100. 100.]\n",
+      "  [100.   0.  75.  75.  75.]\n",
+      "  [ 25.  25.  25.  75.  25.]]\n",
+      "\n",
+      " [[100.  25.  25.  25.  25.]\n",
+      "  [ 75.  25.  25.  25.  25.]\n",
+      "  [ 25.  25.  25.  25.  75.]]]\n",
+      "[[['A' 'A' 'C' 'D' 'D']\n",
+      "  ['D' '0.0' 'C' 'C' 'C']\n",
+      "  ['A' 'A' 'A' 'C' 'A']]\n",
+      "\n",
+      " [['D' 'A' 'A' 'A' 'A']\n",
+      "  ['C' 'A' 'A' 'A' 'A']\n",
+      "  ['A' 'A' 'A' 'A' 'C']]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "fs = f.astype(str)\n",
+    "\n",
+    "for i in range(d.shape[0]):\n",
+    "    for j in range(d.shape[1]):\n",
+    "        for k in range(d.shape[2]):\n",
+    "            # Get the current value\n",
+    "            value = d[i, j, k]\n",
+    "            \n",
+    "            # Apply conditions and update f\n",
+    "            if value > d_min and value < d_mean:\n",
+    "                fs[i, j, k] = \"A\"\n",
+    "            elif value > d_mean and value < d_max:\n",
+    "                fs[i, j, k] = \"C\"\n",
+    "            elif value == d_mean:\n",
+    "                fs[i, j, k] = \"B\"\n",
+    "            elif value == d_max:\n",
+    "                fs[i, j, k] = \"D\"\n",
+    "                \n",
+    "print(d)\n",
+    "print(f)\n",
+    "print(fs)"
    ]
   }
  ],
@@ -374,7 +719,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.0"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,