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LuchoRosario Feb 3, 2025
87d4dab
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LuchoRosario Feb 5, 2025
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184 changes: 182 additions & 2 deletions lab-python-data-structures.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,186 @@
"# Lab | Data Structures "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"#n1 list\n",
"products= [\"t-shirt\",\"mug\",\"hat\",\"book\",\"keychain\"]\n",
"\n",
"\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"#n2 empty dictionary\n",
"inventory= {} "
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"#3 fill inventory\n",
"inventory['t-shirt']= int(input('numbers of t-shirts: '))\n",
"inventory['mug']= int(input('numbers of mug: '))\n",
"inventory['hat']= int(input('numbers of hat: '))\n",
"inventory['book']= int(input ('numbers of book: '))\n",
"inventory['keychain']= int(input ('numbers of keychain: ')) \n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'t-shirt': 6, 'mug': 3, 'hat': 2, 'book': 5, 'keychain': 4}\n"
]
}
],
"source": [
"print (inventory)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"#4 empty set\n",
"customers_orders= set ()"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [],
"source": [
"#5\n",
"product1= input(\"primer producto: \") \n",
"customers_orders.add(product1) \n",
"product2= input(\"segundo producto: \") \n",
"customers_orders.add(product2)\n",
"product3= input(\"tercer producto: \")\n",
"customers_orders.add(product3)\n",
"\n",
" \n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'hat', 'mug', 't-shirt'}\n"
]
}
],
"source": [
"#6 realizar el print\n",
"print (customers_orders)"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [],
"source": [
"total_products_ordened= len(customers_orders)\n",
"percent_products_ordened= total_products_ordened/len(products)*100"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [],
"source": [
"order_status=(total_products_ordened, percent_products_ordened)\n"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Order Statistics:\n",
"total products ordened 3\n",
"percent of products ordened 60.0\n"
]
}
],
"source": [
"print(\"Order Statistics:\")\n",
"print(\"total products ordened\",order_status[0])\n",
"print(\"percent of products ordened\",order_status[1]) "
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'t-shirt': 4, 'mug': 1, 'hat': 0, 'book': 3, 'keychain': 2}\n"
]
}
],
"source": [
"#9 modificar inventario\n",
"inventory['t-shirt']-=1 \n",
"inventory['mug']-=1\n",
"inventory['hat']-=1\n",
"inventory['book']-=1\n",
"inventory['keychain']-=1\n",
"print(inventory)\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
Expand Down Expand Up @@ -54,7 +234,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "base",
"language": "python",
"name": "python3"
},
Expand All @@ -68,7 +248,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.12.7"
}
},
"nbformat": 4,
Expand Down