Add Vaishnavi's Day 1 dashboard summarization (cleared outputs)

week1/community-contributions/Dashboard summarization.ipynb

@@ -0,0 +1,256 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "e0ab4a60-bc68-446d-ae13-6bd90d54ae44",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# imports\n",
+    "import os\n",
+    "from dotenv import load_dotenv\n",
+    "import requests\n",
+    "from bs4 import BeautifulSoup\n",
+    "from IPython.display import Markdown, display\n",
+    "from openai import OpenAI"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "749afaa0-a82e-4783-91fc-f69756075606",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# A class to represent a Webpage\n",
+    "\n",
+    "# Some websites need you to use proper headers when fetching them:\n",
+    "headers = {\n",
+    " \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36\"\n",
+    "}\n",
+    "\n",
+    "class Website:\n",
+    "\n",
+    "    def __init__(self, url):\n",
+    "        \"\"\"\n",
+    "        Create this Website object from the given url using the BeautifulSoup library\n",
+    "        \"\"\"\n",
+    "        self.url = url\n",
+    "        response = requests.get(url, headers=headers)\n",
+    "        soup = BeautifulSoup(response.content, 'html.parser')\n",
+    "        self.title = soup.title.string if soup.title else \"No title found\"\n",
+    "        for irrelevant in soup.body([\"script\", \"style\", \"img\", \"input\"]):\n",
+    "            irrelevant.decompose()\n",
+    "        self.text = soup.body.get_text(separator=\"\\n\", strip=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "7e760d9c-d899-49e5-8b8f-c202794486cc",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "API key found and looks good so far!\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Load environment variables in a file called .env\n",
+    "\n",
+    "load_dotenv(override=True)\n",
+    "api_key = os.getenv('OPENAI_API_KEY')\n",
+    "\n",
+    "# Check the key\n",
+    "\n",
+    "if not api_key:\n",
+    "    print(\"No API key was found - please head over to the troubleshooting notebook in this folder to identify & fix!\")\n",
+    "elif not api_key.startswith(\"sk-proj-\"):\n",
+    "    print(\"An API key was found, but it doesn't start sk-proj-; please check you're using the right key - see troubleshooting notebook\")\n",
+    "elif api_key.strip() != api_key:\n",
+    "    print(\"An API key was found, but it looks like it might have space or tab characters at the start or end - please remove them - see troubleshooting notebook\")\n",
+    "else:\n",
+    "    print(\"API key found and looks good so far!\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "8efb8bb3-9be9-404b-aff5-306db64a75e7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "openai = OpenAI()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "cf677c78-012c-4b86-a76c-be47ed3cb987",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define our system prompt - you can experiment with this later, changing the last sentence to 'Respond in markdown in Spanish.\"\n",
+    "\n",
+    "system_prompt = \"You are an assistant that analyzes the \\\n",
+    "the dashboard in a website and provides a short executive summary, ignoring text that might be navigation related. \\\n",
+    "Respond in markdown.\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "970a493a-880a-4206-9609-eee0651aa91f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# A function that writes a User Prompt that asks for summaries of websites:\n",
+    "\n",
+    "def user_prompt_for(website):\n",
+    "    user_prompt = f\"You are looking at a website titled {website.title}\"\n",
+    "    user_prompt += \"\\nPlease provide a detailed summary of the report for the year in markdown for its user (CFO); \\\n",
+    "The summary should be in a suitable form which could be sent through a mail for the exective.\\n\\n\"\n",
+    "    user_prompt += website.text\n",
+    "    return user_prompt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "2520cdd1-4755-4c87-854f-430e81dbc3fc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def messages_for(website):\n",
+    "    return [\n",
+    "        {\"role\": \"system\", \"content\": system_prompt},\n",
+    "        {\"role\": \"user\", \"content\": user_prompt_for(website)}\n",
+    "    ]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "7452990b-352b-43cc-adc6-4307d6d5c1d5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def summarize(url):\n",
+    "    website = Website(url)\n",
+    "    response = openai.chat.completions.create(\n",
+    "        model = \"gpt-4o-mini\",\n",
+    "        messages = messages_for(website)\n",
+    "    )\n",
+    "    return response.choices[0].message.content"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "7372da3c-f3c7-455b-825e-f54d3b0cee68",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def display_summary(url):\n",
+    "    summary = summarize(url)\n",
+    "    display(Markdown(summary))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "be7d57dc-bec1-4771-9d15-d80fd4d3fbb5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/markdown": [
+       "# Executive Summary: Revenue & Profitability Dashboard\n",
+       "\n",
+       "**To:** [CFO Name]  \n",
+       "**From:** [Your Name]  \n",
+       "**Date:** [Current Date]  \n",
+       "**Subject:** Yearly Analysis of Revenue & Profitability  \n",
+       "\n",
+       "---\n",
+       "\n",
+       "Dear [CFO Name],\n",
+       "\n",
+       "I am pleased to present the Year-over-Year analysis derived from the Revenue & Profitability Dashboard. This dashboard has been designed to provide concise insights into our core financial performance metrics, enabling data-driven decision-making at the executive level.\n",
+       "\n",
+       "### Key Metrics Overview:\n",
+       "- **Revenue**: Comprehensive insights into total revenue across various regions and product categories, indicating sustainable growth patterns.\n",
+       "- **Profit**: Detailed profitability analysis segmented by customer groups, revealing key opportunities for margin improvement and cost optimization.\n",
+       "- **Unit Sales**: Analysis of unit sales trends that highlight product performance and demand fluctuations.\n",
+       "\n",
+       "### Insights by Segment:\n",
+       "- **Regional Performance**: Comparative analysis of revenue and profitability by region helps identify areas of growth and those requiring strategic intervention.\n",
+       "- **Product Performance**: A focused review of individual product lines shows which offerings are driving profitability and where we might consider realignment or innovation.\n",
+       "\n",
+       "### Dashboard Features:\n",
+       "- A **clean and focused layout** reduces cognitive load, allowing for quick assimilation and understanding of critical data points.\n",
+       "- **Contextual metrics** that align with our overarching business strategy, ensuring that our analysis supports our organizational goals.\n",
+       "- **Clear comparison points** are established to aid executives in making informed and timely decisions.\n",
+       "- Insightful details are presented at both product and regional levels, facilitating targeted strategies for improvement.\n",
+       "\n",
+       "### Conclusion:\n",
+       "The integration of design and context in our dashboard framework turns our data into strategic tools, empowering us to make faster and more informed decisions that drive real business impact.\n",
+       "\n",
+       "Please feel free to reach out for a more detailed discussion or specific metrics that may interest you.\n",
+       "\n",
+       "Best regards,\n",
+       "\n",
+       "[Your Name]  \n",
+       "[Your Position]\n",
+       "\n",
+       "--- \n",
+       "\n",
+       "*Note: For additional inquiries or insights, feel free to follow our updates on LinkedIn or contact me directly.*"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "display_summary(\"https://community.fabric.microsoft.com/t5/Data-Stories-Gallery/Revenue-amp-Profitability-Dashboard/td-p/4780272\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1aa33cfd-d497-4ab8-abb5-eb4e6030890b",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}