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289 changes: 287 additions & 2 deletions lab-python-functions.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@
},
{
"cell_type": "markdown",
"id": "0c581062-8967-4d93-b06e-62833222f930",
"id": "340baa2d-38bd-4df9-a193-9c6a4d51dbd7",
"metadata": {
"tags": []
},
Expand Down Expand Up @@ -43,6 +43,291 @@
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "96af86ed-cc29-4320-b538-26a3f4899e33",
"metadata": {},
"outputs": [],
"source": [
"products=[\"t-shirt\", \"mug\", \"hat\", \"book\", \"keychain\"]"
]
},
{
"cell_type": "code",
"execution_count": 201,
"id": "3db15d02-d7e4-4790-b7ab-c9ee5908cacf",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'t-shirt': 2, 'mug': 2, 'hat': 2, 'book': 2, 'keychain': 2}"
]
},
"execution_count": 201,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"inventory_1"
]
},
{
"cell_type": "code",
"execution_count": 202,
"id": "c610d678-0ed4-4d05-8aea-c12cecb86426",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'book', 'mug'}"
]
},
"execution_count": 202,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"customer_order_1"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "5190fc17-c203-4077-ba1f-93f05d929bf4",
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Enter quantity: 22\n",
"Enter quantity: 2\n",
"Enter quantity: 2\n",
"Enter quantity: 2\n",
"Enter quantity: 2\n"
]
}
],
"source": [
"#Define a function named initialize_inventory that takes products as a parameter. Inside the function, implement the code for initializing the inventory dictionary using a loop and user input.\n",
"def initialize_inventory(products):\n",
" inventory=dict()\n",
" for i in products:\n",
" quantity=int(input(\"Enter quantity: \"))\n",
" inventory[i]=quantity\n",
" return inventory\n",
"inventory= initialize_inventory(products)"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "026f7d14-348f-4d23-895b-0c9859c6606e",
"metadata": {},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Enter name of product: mug\n",
"Enter yes or no to add another product: yes\n",
"Enter name of product: book\n",
"Enter yes or no to add another product: no\n"
]
}
],
"source": [
"def get_customer_orders():\n",
" x=len(products)\n",
" customer_orders=set()\n",
" count=0\n",
"\n",
" for count in range(x):\n",
" name=input(\"Enter name of product: \")\n",
" if name in products:\n",
" customer_orders.add(name)\n",
" ask=input(\"Enter yes or no to add another product: \")\n",
" if ask==\"yes\":\n",
" count+=1\n",
" elif ask==\"no\":\n",
" break\n",
" else:\n",
" print(\"please add available\")\n",
" \n",
" return customer_orders\n",
" \n",
"customer_orders=get_customer_orders() "
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "28030f42-4f98-4936-8a7d-6c3d0bee2f47",
"metadata": {},
"outputs": [],
"source": [
"def update_inventory(customer_orders, inventory):\n",
" for i in customer_orders:\n",
" if i in inventory:\n",
" inventory[i]-=1 \n",
" return inventory \n",
"inventory= update_inventory(customer_orders, inventory)"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "5b1b4e48-8663-4638-b293-71d297f0f2f3",
"metadata": {},
"outputs": [],
"source": [
"def calculate_order_statistics(customer_orders, products):\n",
" total_products_ordered=len(customer_orders)\n",
" total_products= len(products)\n",
" percentage_unique_ordered=round((total_products_ordered/total_products)*100)\n",
" return total_products_ordered, percentage_unique_ordered\n",
"\n",
"order_statistics=calculate_order_statistics(customer_orders, products)\n",
" \n",
" \n",
" "
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "5556235c-f778-427c-8dda-addd40370279",
"metadata": {},
"outputs": [],
"source": [
"def print_order_statistics(order_statistics):\n",
" print(f\"Order Statistics= Total products ordered:Percentage of products ordered are {order_statistics}\")\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "974e016c-6f4c-4dc9-aa40-a70f715aaba3",
"metadata": {},
"outputs": [],
"source": [
"def print_updated_inventory(inventory):\n",
" print(f\"The updated inventory is {inventory}\")"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "fa25e788-70a3-435a-8a62-8e5414756a91",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'t-shirt': 22, 'mug': -1, 'hat': 2, 'book': -1, 'keychain': 2}"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"update_inventory(customer_orders, inventory)"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "714357e3-0b7f-4835-9472-b46344cb118d",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(2, 40)"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"calculate_order_statistics(customer_orders, products)"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "150884de-e376-4aba-a26c-7d442d364595",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Order Statistics= Total products ordered:Percentage of products ordered are (2, 40)\n"
]
}
],
"source": [
"print_order_statistics(order_statistics)"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "9785603b-f206-4f27-ad53-3b9fc1c3e6ec",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The updated inventory is {'t-shirt': 22, 'mug': -1, 'hat': 2, 'book': -1, 'keychain': 2}\n"
]
}
],
"source": [
"print_updated_inventory(inventory)"
]
},
{
"cell_type": "code",
"execution_count": 248,
"id": "c13f8ae4-487e-485d-9cb6-f8337d9cb2e4",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'t-shirt': 2, 'mug': 1, 'hat': 2, 'book': 1, 'keychain': 2}"
]
},
"execution_count": 248,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"inventory_1"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ae9e26c5-ce93-4498-bfa5-35a3b627375e",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
Expand All @@ -61,7 +346,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.13"
"version": "3.12.7"
}
},
"nbformat": 4,
Expand Down