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Up2date #291

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307 changes: 306 additions & 1 deletion lab-python-data-structures.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -50,6 +50,311 @@
"\n",
"Solve the exercise by implementing the steps using the Python concepts of lists, dictionaries, sets, and basic input/output operations. "
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"#1\n",
"products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"#2\n",
"inventory = {}"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Ingresa la cantidad de t-shirt: 4\n",
"Ingresa la cantidad de mug: 5\n",
"Ingresa la cantidad de hat: 2\n",
"Ingresa la cantidad de book: 3\n",
"Ingresa la cantidad de keychain: 5\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Inventario actual:\n",
"{'t-shirt': 4, 'mug': 5, 'hat': 2, 'book': 3, 'keychain': 5}\n"
]
}
],
"source": [
"#3\n",
"# Recorrer la lista de productos y solicitar la cantidad para cada uno\n",
"\n",
"for product in products:\n",
" # Pedir al usuario ingresar la cantidad para cada producto\n",
" quantity = int(input(f\"Ingresa la cantidad de {product}: \"))\n",
" # Asignar la cantidad en el diccionario \"inventory\"\n",
" inventory[product] = quantity\n",
"\n",
"# Mostrar el inventario resultante\n",
"print(\"Inventario actual:\")\n",
"print(inventory)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"#4\n",
"customer_orders = set()"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Ingresa nombre de product1: mug\n",
"Ingresa nombre de product2: book\n",
"Ingresa nombre de product3: hat\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Nombre de productos que contiene la órden:\n",
"{'book', 'mug', 'hat'}\n"
]
}
],
"source": [
"#5\n",
"# Pedir al usuario ingresar los 3 tipos de producto que quiere en su orden\n",
"product1_name = input(f\"Ingresa nombre de product1: \")\n",
"product2_name = input(f\"Ingresa nombre de product2: \")\n",
"product3_name = input(f\"Ingresa nombre de product3: \")\n",
"# Asignar el nombre de producto en el set \"customer_orders\"\n",
"customer_orders.add (product1_name)\n",
"customer_orders.add (product2_name)\n",
"customer_orders.add (product3_name)\n",
"\n",
"print(\"Nombre de productos que contiene la órden:\")\n",
"print(customer_orders)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Órden de cliente:\n",
"{'book', 'mug', 'hat'}\n"
]
}
],
"source": [
"#6\n",
"# Mostrar la customer order resultante\n",
"print(\"Órden de cliente:\")\n",
"print(customer_orders)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"#7\n",
"#Total Products Number\n",
"total_products_number = len(customer_orders)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"3"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"total_products_number"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"#Percentage of Products Ordered\n",
"percentage_products_ordered = int((total_products_number / len(products))*100)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"60"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"percentage_products_ordered"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"#Guardar las estadísticas en una tupla\n",
"statistics = (total_products_number,percentage_products_ordered)"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(3, 60)"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"statistics"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Order Statistics:\n",
"Total Products Ordered: 3\n",
"Percentage of Products Ordered: 60\n"
]
}
],
"source": [
"#8\n",
"#Mostrar las estadísticas\n",
"print(\"Order Statistics:\")\n",
"print(\"Total Products Ordered:\", total_products_number)\n",
"print(\"Percentage of Products Ordered:\", percentage_products_ordered)"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [],
"source": [
"#9\n",
"for i in inventory:\n",
" inventory[i]-=1"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'t-shirt': 3, 'mug': 4, 'hat': 1, 'book': 2, 'keychain': 4}"
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"inventory"
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"t-shirt 3\n",
"mug 4\n",
"hat 1\n",
"book 2\n",
"keychain 4\n"
]
}
],
"source": [
"#10\n",
"#Mostrar el inventario actualizado\n",
"for x,i in inventory.items():\n",
" print (x,i)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
Expand All @@ -68,7 +373,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.12.4"
}
},
"nbformat": 4,
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