Update lab-python-data-structures.ipynb

lab-python-data-structures.ipynb

@@ -57,11 +57,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The sum of the grades is: 7\n",
+      "Sorted list of the performance of 3 students: [0, 0, 0]\n",
+      "The number of occurrences of the score '5' is: 0\n"
+     ]
+    }
+   ],
    "source": [
-    "# Your code here"
+    "students_grades = []\n",
+    "for i in range(5):\n",
+    "    grades_input = int(input(\"Enter the grade of each student: \"))\n",
+    "    students_grades.append(grades_input)\n",
+    "\n",
+    "sum_grades = sum(students_grades)\n",
+    "students_selection = students_grades[0:5:2]\n",
+    "students_selection.sort()\n",
+    "\n",
+    "print (f\"The sum of the grades is: {sum_grades}\")\n",
+    "print (f\"Sorted list of the performance of {len(students_selection)} students: {students_selection}\")\n",
+    "print (\"The number of occurrences of the score '5' is:\", students_selection.count(5))"
    ]
   },
   {
@@ -97,11 +118,39 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "('banana', 'grape')\n",
+      "('banana', 'kiwi', 'pineapple', 'watermelon', 'grape')\n",
+      "('banana', 'kiwi', 'pineapple', 'watermelon', 'grape', 'apple', 'melon')\n",
+      "('banana', 'kiwi', 'pineapple', 'watermelon', 'grape', 'banana', 'kiwi', 'pineapple', 'grape', 'apple', 'melon') 11\n"
+     ]
+    }
+   ],
    "source": [
-    "# Your code here"
+    "fruits = (\"banana\", \"orange\", \"pineapple\", \"watermelon\", \"grape\")\n",
+    "print(fruits[0:5:4])\n",
+    "list_fruits = list(fruits)\n",
+    "list_fruits[1] = \"kiwi\"\n",
+    "fruits = tuple(list_fruits)\n",
+    "print(fruits)\n",
+    "extra_fruits = (\"apple\",\"melon\")\n",
+    "new_fruits = fruits + extra_fruits\n",
+    "print(new_fruits)\n",
+    "first_fruits = new_fruits[0:3]\n",
+    "last_fruits = new_fruits[4:7]\n",
+    "mega_fruits = fruits + first_fruits + last_fruits\n",
+    "print(mega_fruits, len(mega_fruits))"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -136,7 +185,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -163,11 +212,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "21\n",
+      "23\n",
+      "['end', 'enough', 'had', 'i', 'if', 'it', 'ive', 'know', 'of', 'say', 'some', 'that', 'think', 'those', 'to', 'what', 'who', 'with']\n"
+     ]
+    }
+   ],
    "source": [
-    "# Your code here"
+    "join_poem = ' '.join(poem.split(' ')) # covierto a lista usando espacios y vuelvo a unir con un solo espacio. Elimino espacios simple, dobles...\n",
+    "join_new_poem = ' '.join(new_poem.split(' '))\n",
+    "clean_poem = join_poem.replace(\".\",\"\").replace(\",\",\"\").replace(\"’\",\"\").lower().split(\" \") # elimino signos de puntiacion y convierto a lista usando como separador los espacios blancos\n",
+    "clean_new_poem = join_new_poem.replace(\".\",\"\").replace(\",\",\"\").replace(\"'\",\"\").lower().split(\" \") # No convierto aun a set porque me separía por letras y no por palabras al ser aun un string\n",
+    "set_poem = set(clean_poem) # convierto a ser la lista \n",
+    "set_new_poem = set(clean_new_poem)\n",
+    "unique_words_poem = set_poem - set_new_poem\n",
+    "unique_words_new_poem = set_new_poem - set_poem\n",
+    "print(len(unique_words_poem))\n",
+    "print(len(unique_words_new_poem))\n",
+    "unique_words = set_poem & set_new_poem\n",
+    "print(sorted(unique_words))"
    ]
   },
   {
@@ -193,7 +263,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -206,7 +276,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here"
+    "grades[\"Bob\"][\"Philosophy\"] = 100\n",
+    "print(grades)"
    ]
   },
   {
@@ -239,14 +310,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'Physics': 75, 'Math': 85, 'Chemistry': 60, 'Philosophy': 90}\n"
+     ]
+    }
+   ],
    "source": [
     "keys = ['Physics', 'Math', 'Chemistry', 'Philosophy']\n",
     "values = [75, 85, 60,90]\n",
     "\n",
-    "# Your code here"
+    "subject_scores_dict = dict(zip(keys,values))\n",
+    "\n",
+    "\n",
+    "print(subject_scores_dict)"
    ]
   },
   {
@@ -275,17 +357,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Chemistry\n"
+     ]
+    }
+   ],
    "source": [
-    "# Your code here"
+    "min_subject = min(subject_scores_dict, key=subject_scores_dict.get)\n",
+    "print(min_subject)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -299,7 +397,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.13"
+   "version": "3.14.4"
   }
  },
  "nbformat": 4,