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Update lab-python-data-structures.ipynb #87

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245 changes: 225 additions & 20 deletions lab-python-data-structures.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -57,11 +57,45 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 2,
"metadata": {},
"outputs": [],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"La suma total de las notas es: 39\n",
"Notas seleccionadas ordenadas: [7, 8, 9]\n",
"Cantidad de notas en la lista: 3\n",
"Cantidad de veces que aparece la nota 5: 0\n"
]
}
],
"source": [
"# Your code here"
"# Your code here\n",
"# Lista vacía para guardar las notas\n",
"notas = []\n",
"\n",
"# Pedimos las notas de los 5 estudiantes\n",
"for i in range(5):\n",
" nota = int(input(f\"Ingrese la nota del estudiante {i + 1}: \"))\n",
" notas.append(nota)\n",
"\n",
"# Calculamos la suma total de las notas\n",
"suma_total = sum(notas)\n",
"print(\"La suma total de las notas es:\", suma_total)\n",
"\n",
"# Seleccionamos las notas del 1°, 3° y 5° estudiante\n",
"# (índices 0, 2 y 4)\n",
"notas_seleccionadas = notas[0:5:2]\n",
"\n",
"# Ordenamos la nueva lista\n",
"notas_seleccionadas.sort()\n",
"\n",
"# Mostramos resultados\n",
"print(\"Notas seleccionadas ordenadas:\", notas_seleccionadas)\n",
"print(\"Cantidad de notas en la lista:\", len(notas_seleccionadas))\n",
"print(\"Cantidad de veces que aparece la nota 5:\", notas_seleccionadas.count(5))\n"
]
},
{
Expand Down Expand Up @@ -95,11 +129,57 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 3,
"metadata": {},
"outputs": [],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Tupla original: ('manzana', 'banana', 'naranja', 'pera', 'uva')\n",
"Primera fruta: manzana\n",
"Última fruta: uva\n",
"Tupla actualizada: ('manzana', 'mango', 'naranja', 'pera', 'uva')\n",
"Tupla concatenada: ('manzana', 'mango', 'naranja', 'pera', 'uva', 'kiwi', 'ananá')\n",
"Primera tupla: ('manzana', 'mango', 'naranja')\n",
"Segunda tupla: ('uva', 'kiwi', 'ananá')\n",
"Tupla final: ('manzana', 'mango', 'naranja', 'pera', 'uva', 'manzana', 'mango', 'naranja', 'uva', 'kiwi', 'ananá')\n",
"Longitud de la tupla final: 11\n"
]
}
],
"source": [
"# Your code here"
"# Your code here\n",
"# 1. Creamos una tupla con 5 frutas\n",
"frutas = (\"manzana\", \"banana\", \"naranja\", \"pera\", \"uva\")\n",
"print(\"Tupla original:\", frutas)\n",
"\n",
"# 2. Mostramos el primer y último elemento\n",
"print(\"Primera fruta:\", frutas[0])\n",
"print(\"Última fruta:\", frutas[-1])\n",
"\n",
"# 3. Reemplazamos la segunda fruta (convertimos a lista)\n",
"frutas_lista = list(frutas)\n",
"frutas_lista[1] = \"mango\"\n",
"frutas = tuple(frutas_lista)\n",
"print(\"Tupla actualizada:\", frutas)\n",
"\n",
"# 4. Concatenamos una nueva tupla con 2 frutas más\n",
"nuevas_frutas = (\"kiwi\", \"ananá\")\n",
"frutas_concatenadas = frutas + nuevas_frutas\n",
"print(\"Tupla concatenada:\", frutas_concatenadas)\n",
"\n",
"# 5. Dividimos la tupla en dos tuplas de 3 elementos\n",
"tupla1 = frutas_concatenadas[:3]\n",
"tupla2 = frutas_concatenadas[-3:]\n",
"\n",
"print(\"Primera tupla:\", tupla1)\n",
"print(\"Segunda tupla:\", tupla2)\n",
"\n",
"# 6. Combinamos todo en una nueva tupla\n",
"tupla_final = frutas + tupla1 + tupla2\n",
"print(\"Tupla final:\", tupla_final)\n",
"print(\"Longitud de la tupla final:\", len(tupla_final))\n"
]
},
{
Expand Down Expand Up @@ -136,7 +216,7 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -163,11 +243,60 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 5,
"metadata": {},
"outputs": [],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Cantidad de palabras únicas en el primer poema: 41\n",
"Cantidad de palabras únicas en el segundo poema: 42\n",
"\n",
"Palabras solo en el primer poema:\n",
"{'favor', 'great', 'fire', 'would', 'twice', 'in', 'world', 'hate', 'hold', 'will', 'for', 'tasted', 'ice', 'destruction', 'the', 'perish', 'desire', 'also', 'suffice'}\n",
"\n",
"Palabras solo en el segundo poema:\n",
"{'as', 'though', 'made', 'away', 'dream', 'seen', 'its', 'are', 'side', 'love', 'today', 'fades', 'quest', 'we', 'life', 'test', 'see', 'deem', 'still', 'a'}\n",
"\n",
"Palabras en ambos poemas (ordenadas):\n",
"['and', 'but', 'end', 'enough', 'from', 'had', 'i', 'if', 'is', 'it', 'ive', 'know', 'of', 'say', 'some', 'that', 'think', 'those', 'to', 'what', 'who', 'with']\n"
]
}
],
"source": [
"# Your code here"
"# Your code here\n",
"import string\n",
"\n",
"# Función para limpiar texto y convertirlo en un set de palabras\n",
"def palabras_unicas(texto):\n",
" texto = texto.lower()\n",
" texto = texto.translate(str.maketrans(\"\", \"\", string.punctuation + \"’\"))\n",
" palabras = texto.split()\n",
" return set(palabras)\n",
"\n",
"# Creamos los sets de cada poema\n",
"set_poem = palabras_unicas(poem)\n",
"set_new_poem = palabras_unicas(new_poem)\n",
"\n",
"# 1. Cantidad de palabras únicas\n",
"print(\"Cantidad de palabras únicas en el primer poema:\", len(set_poem))\n",
"print(\"Cantidad de palabras únicas en el segundo poema:\", len(set_new_poem))\n",
"\n",
"# 2. Palabras solo en el primer poema\n",
"solo_poem = set_poem - set_new_poem\n",
"print(\"\\nPalabras solo en el primer poema:\")\n",
"print(solo_poem)\n",
"\n",
"# 3. Palabras solo en el segundo poema\n",
"solo_new_poem = set_new_poem - set_poem\n",
"print(\"\\nPalabras solo en el segundo poema:\")\n",
"print(solo_new_poem)\n",
"\n",
"# 4. Palabras en ambos poemas (ordenadas)\n",
"comunes = sorted(set_poem & set_new_poem)\n",
"print(\"\\nPalabras en ambos poemas (ordenadas):\")\n",
"print(comunes)\n"
]
},
{
Expand All @@ -193,7 +322,7 @@
},
{
"cell_type": "code",
"execution_count": 51,
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -206,7 +335,55 @@
"metadata": {},
"outputs": [],
"source": [
"# Your code here"
"# Your code here\n",
"#diccionario inicial de estudiantes y sus notas\n",
"students = {\n",
" \"Alice\": {\n",
" \"Math\": 85,\n",
" \"History\": 90,\n",
" \"Philosophy\": 88\n",
" },\n",
" \"Bob\": {\n",
" \"Math\": 78,\n",
" \"History\": 82,\n",
" \"Philosophy\": 70\n",
" },\n",
" \"Charlie\": {\n",
" \"Math\": 92,\n",
" \"History\": 88,\n",
" \"Philosophy\": 91\n",
" }\n",
"}\n"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"#actualizamos nota de Bob en Filosofía\n",
"students[\"Bob\"][\"Philosophy\"] = 100\n"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Diccionario actualizado:\n",
"{'Alice': {'Math': 85, 'History': 90, 'Philosophy': 88}, 'Bob': {'Math': 78, 'History': 82, 'Philosophy': 100}, 'Charlie': {'Math': 92, 'History': 88, 'Philosophy': 91}}\n"
]
}
],
"source": [
"#diccionario actualizado\n",
"print(\"Diccionario actualizado:\")\n",
"print(students)\n"
]
},
{
Expand Down Expand Up @@ -239,14 +416,26 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 10,
"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"
"# Your code here\n",
"# Convertimos las listas en diccionario usando zip\n",
"notas = dict(zip(keys, values))\n",
"\n",
"print(notas)\n"
]
},
{
Expand Down Expand Up @@ -275,17 +464,33 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 13,
"metadata": {},
"outputs": [],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"La materia con la nota mas baja es: Chemistry\n",
"La nota mas baja es: 60\n"
]
}
],
"source": [
"# Your code here"
"# Your code here\n",
"notas = {'Physics': 75, 'Math': 85, 'Chemistry': 60, 'Philosophy': 90}\n",
"\n",
"# Obtenemos la materia con la nota mínima\n",
"nota_mas_baja = min(notas, key=notas.get)\n",
"\n",
"print(\"La materia con la nota mas baja es:\", nota_mas_baja)\n",
"print(\"La nota mas baja es:\", notas[nota_mas_baja])"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
Expand All @@ -299,7 +504,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.14.0"
}
},
"nbformat": 4,
Expand Down