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Adding data structures lab #680

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220 changes: 219 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 +50,224 @@
"\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": 2,
"metadata": {},
"outputs": [],
"source": [
"inventory ={}"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Quantify t-shirt product: 5\n",
"Quantify mug product: 4\n",
"Quantify hat product: 7\n",
"Quantify book product: 3\n",
"Quantify keychain product: 2\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'t-shirt': 5, 'mug': 4, 'hat': 7, 'book': 3, 'keychain': 2}\n"
]
}
],
"source": [
"#3 \n",
"inventory = {\"t-shirt\": 0,\n",
" \"mug\": 0,\n",
" \"hat\": 0,\n",
" \"book\": 0,\n",
" \"keychain\": 0}\n",
"inventory[\"t-shirt\"] = int(input(\"Quantify t-shirt product: \"))\n",
"inventory[\"mug\"] = int(input(\"Quantify mug product: \"))\n",
"inventory[\"hat\"] = int(input(\"Quantify hat product: \"))\n",
"inventory[\"book\"] = int(input(\"Quantify book product: \"))\n",
"inventory[\"keychain\"] = int(input(\"Quantify keychain product: \"))\n",
"\n",
"print(inventory)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"#4\n",
"costumer_orders = {}"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Add first product: hat\n",
"Add second product: t-shirt\n",
"Add third product: mug\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"['hat', 't-shirt', 'mug']\n"
]
}
],
"source": [
"#5 and 6\n",
"\n",
"customer_orders = []\n",
"\n",
"customer_orders.append(input(\"Add first product: \").lower())\n",
"customer_orders.append(input(\"Add second product: \").lower())\n",
"customer_orders.append(input(\"Add third product: \").lower())\n",
"\n",
"print(customer_orders)\n"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Add first product: mug\n",
"Add second product: t-shirt\n",
"Add third product: hat\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Customer orders: {'hat', 't-shirt', 'mug'}\n",
"Order status: (3, 60.0)\n"
]
}
],
"source": [
"#7\n",
"products = [\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]\n",
"\n",
"customer_orders = set()\n",
"\n",
"customer_orders.add(input(\"Add first product: \").lower())\n",
"customer_orders.add(input(\"Add second product: \").lower())\n",
"customer_orders.add(input(\"Add third product: \").lower())\n",
"\n",
"total_products_ordered = len(customer_orders)\n",
"percentage_of_products_ordered = (total_products_ordered / len(products)) * 100\n",
"\n",
"order_status = (total_products_ordered, percentage_of_products_ordered)\n",
"\n",
"print(\"Customer orders:\", customer_orders)\n",
"print(\"Order status:\", order_status)\n"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Order Statistics:\n",
"Total Products Ordered: 3\n",
"Percentage of Products Ordered: 60.0%\n"
]
}
],
"source": [
"#8\n",
"print(\"Order Statistics:\")\n",
"print(f\"Total Products Ordered: {order_status[0]}\")\n",
"print(f\"Percentage of Products Ordered: {order_status[1]}%\")\n"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"#9\n",
"\n",
"inventory[\"t-shirt\"] -= (\"t-shirt\" in customer_orders)\n",
"inventory[\"mug\"] -= (\"mug\" in customer_orders)\n",
"inventory[\"hat\"] -= (\"hat\" in customer_orders)\n",
"inventory[\"book\"] -= (\"book\" in customer_orders)\n",
"inventory[\"keychain\"] -= (\"keychain\" in customer_orders)\n"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Updated Inventory:\n",
"t-shirt: 4\n",
"mug: 3\n",
"hat: 6\n",
"book: 3\n",
"keychain: 2\n"
]
}
],
"source": [
"#10\n",
"\n",
"print(\"Updated Inventory:\")\n",
"print(f\"t-shirt: {inventory['t-shirt']}\")\n",
"print(f\"mug: {inventory['mug']}\")\n",
"print(f\"hat: {inventory['hat']}\")\n",
"print(f\"book: {inventory['book']}\")\n",
"print(f\"keychain: {inventory['keychain']}\")\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
Expand All @@ -68,7 +286,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.13.9"
}
},
"nbformat": 4,
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