Edit C0-A22 (Chapter 0, Activity 22).

Author: UPstartDeveloper

chapter0-exercises/chapter_0_part2.ipynb

@@ -1042,29 +1042,125 @@
         "id": "thick-demonstration"
       },
       "source": [
-        "## Activity: Obtain the transpose of a given matrix"
+        "## Activity 22: Transpose of a Matrix\n",
+        "\n",
+        "Another popular matrix operation is to compute the *transpose*. We flip the elements in the matrix over the diagonal producing a new matrix.\n",
+        "\n",
+        "You are given a 2D list of numbers, `matrix`. How would you write Python code to compute the tranpose of `matrix`?"
       ],
       "id": "thick-demonstration"
     },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "eKYvopLpX1B7"
+      },
+      "source": [
+        "### Example Input\n",
+        "\n",
+        "Put another way, the transpose matrix is just what the original `matrix` would be, if you were to read the elements in said `matrix` going up and down vertically, rather than left to right horizontally.\n",
+        "\n",
+        "Therefore, if we had a matrix like the following:\n",
+        "```\n",
+        "matrix = [\n",
+        "    [8, 2, 3],\n",
+        "    [9, 1, 9], \n",
+        "    [5, 4, 1]\n",
+        "]\n",
+        "```\n",
+        "Then we would expect its transpose to be the following output:\n",
+        "```\n",
+        "transposed_matrix = [\n",
+        "    [8, 9, 5],  # first column\n",
+        "    [2, 1, 4],  # second column\n",
+        "    [3, 9, 1]   # third column\n",
+        "]\n",
+        "```\n"
+      ],
+      "id": "eKYvopLpX1B7"
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "id": "7ooH8oluXyzU"
+      },
+      "source": [
+        "matrix = [[8, 2, 3], [9, 1, 9], [5, 4, 1]]"
+      ],
+      "id": "7ooH8oluXyzU",
+      "execution_count": 21,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "9lQnNxm-VeaU"
+      },
+      "source": [
+        "### Solution "
+      ],
+      "id": "9lQnNxm-VeaU"
+    },
     {
       "cell_type": "code",
       "metadata": {
-        "id": "musical-industry",
-        "outputId": "f196159c-a326-4202-f16d-b5de539b0905"
+        "id": "musical-industry"
       },
       "source": [
-        "def transpose(matx):\n",
-        "    t_m = [[] for _ in range(len(matx[0]))]\n",
-        "    # Do not use this: t_m = [[]]*len(matx[0])\n",
-        "    for i in range(len(matx[0])):\n",
+        "def transpose(matrix):\n",
+        "    # A: init the transpose matrix using the dims of the original\n",
+        "    transposed_matrix = [[] for _ in range(len(matrix[0]))] \n",
+        "    # B: iterate over each column\n",
+        "    for col_index in range(len(matrix[0])):\n",
+        "        # C: collect the elements in this column\n",
         "        for row in matrix:\n",
-        "            t_m[i].append(row[i])\n",
-        "    return t_m\n",
+        "            transposed_matrix[col_index].append(row[col_index])\n",
+        "    # D: return the transpose of the matrix\n",
+        "    return transposed_matrix"
+      ],
+      "id": "musical-industry",
+      "execution_count": 22,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "UUcNULKQVg1i"
+      },
+      "source": [
+        "**Note**: in the solution above, it is also possible to implement step A in the following way:\n",
         "\n",
+        "```\n",
+        "transpose = [[]]*len(matrix[0])\n",
+        "```\n",
+        "However, using a list comprehension with the `range()` function is the more efficient way to initialize our matrix, and thus is preferred. "
+      ],
+      "id": "UUcNULKQVg1i"
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "hJGmQfzfXqnR"
+      },
+      "source": [
+        "#### Test Out The Solution"
+      ],
+      "id": "hJGmQfzfXqnR"
+    },
+    {
+      "cell_type": "code",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "B93uZPY0XwrN",
+        "outputId": "0fe978d0-7fd5-49a6-8884-e7445957e73d"
+      },
+      "source": [
         "print(transpose(matrix))"
       ],
-      "id": "musical-industry",
-      "execution_count": null,
+      "id": "B93uZPY0XwrN",
+      "execution_count": 20,
       "outputs": [
         {
           "output_type": "stream",