diff --git a/cookbook/company-info/scrapegraph_sdk.ipynb b/cookbook/company-info/scrapegraph_sdk.ipynb
new file mode 100644
index 0000000..cf207c9
--- /dev/null
+++ b/cookbook/company-info/scrapegraph_sdk.ipynb
@@ -0,0 +1,1942 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "jEkuKbcRrPcK"
+   },
+   "source": [
+    "## \ud83d\udd77\ufe0f Extract Company Info with Official Scrapegraph SDK\n",
+    "\n",
+    "[![Open in Alph](https://www.runalph.ai/badges/open-in-alph.svg)](https://www.runalph.ai/notebooks/scrapegraphai/scrapegraph-sdk) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/12d7LycLAYO2bFsBo_jtPHXSaIg7AqR3O?usp=sharing)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "3Q5VM3SsRlxO"
+   },
+   "source": [
+    "![scrapegraph banner](data:image/png;base64,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+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "IzsyDXEWwPVt"
+   },
+   "source": [
+    "### \ud83d\udd27 Install `dependencies`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "os_vm0MkIxr9"
+   },
+   "outputs": [],
+   "source": [
+    "%%capture\n",
+    "!pip install scrapegraph-py"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "apBsL-L2KzM7"
+   },
+   "source": [
+    "### \ud83d\udd11 Import `ScrapeGraph` API key"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "ol9gQbAFkh9b"
+   },
+   "source": [
+    "You can find the Scrapegraph API key [here](https://dashboard.scrapegraphai.com/)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "executionInfo": {
+     "elapsed": 6877,
+     "status": "ok",
+     "timestamp": 1734532300517,
+     "user": {
+      "displayName": "ScrapeGraphAI",
+      "userId": "10474323355016263615"
+     },
+     "user_tz": -60
+    },
+    "id": "sffqFG2EJ8bI",
+    "outputId": "f6b837cd-0f00-49cc-cb6f-f2bca57544f5"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "SGAI_API_KEY not found in environment.\n",
+      "Please enter your SGAI_API_KEY: \u00b7\u00b7\u00b7\u00b7\u00b7\u00b7\u00b7\u00b7\u00b7\u00b7\n",
+      "SGAI_API_KEY has been set in the environment.\n"
+     ]
+    }
+   ],
+   "source": [
+    "import getpass\n",
+    "import os\n",
+    "\n",
+    "if not os.environ.get(\"SGAI_API_KEY\"):\n",
+    "    os.environ[\"SGAI_API_KEY\"] = getpass.getpass(\"Scrapegraph API key:\\n\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "jnqMB2-xVYQ7"
+   },
+   "source": [
+    "### \ud83d\udcdd Defining an `Output Schema` for Webpage Content Extraction\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "VZvxbjfXvbgd"
+   },
+   "source": [
+    "If you already know what you want to extract from a webpage, you can **define an output schema** using **Pydantic**. This schema acts as a \"blueprint\" that tells the AI how to structure the response.\n",
+    "\n",
+    "<details>\n",
+    "  <summary>Pydantic Schema Quick Guide</summary>\n",
+    "\n",
+    "Types of Schemas  \n",
+    "\n",
+    "1. Simple Schema  \n",
+    "Use this when you want to extract straightforward information, such as a single piece of content.  \n",
+    "\n",
+    "```python\n",
+    "from pydantic import BaseModel, Field\n",
+    "\n",
+    "# Simple schema for a single webpage\n",
+    "class PageInfoSchema(BaseModel):\n",
+    "    title: str = Field(description=\"The title of the webpage\")\n",
+    "    description: str = Field(description=\"The description of the webpage\")\n",
+    "\n",
+    "# Example Output JSON after AI extraction\n",
+    "{\n",
+    "    \"title\": \"ScrapeGraphAI: The Best Content Extraction Tool\",\n",
+    "    \"description\": \"ScrapeGraphAI provides powerful tools for structured content extraction from websites.\"\n",
+    "}\n",
+    "```\n",
+    "\n",
+    "2. Complex Schema (Nested)  \n",
+    "If you need to extract structured information with multiple related items (like a list of repositories), you can **nest schemas**.\n",
+    "\n",
+    "```python\n",
+    "from pydantic import BaseModel, Field\n",
+    "from typing import List\n",
+    "\n",
+    "# Define a schema for a single repository\n",
+    "class RepositorySchema(BaseModel):\n",
+    "    name: str = Field(description=\"Name of the repository (e.g., 'owner/repo')\")\n",
+    "    description: str = Field(description=\"Description of the repository\")\n",
+    "    stars: int = Field(description=\"Star count of the repository\")\n",
+    "    forks: int = Field(description=\"Fork count of the repository\")\n",
+    "    today_stars: int = Field(description=\"Stars gained today\")\n",
+    "    language: str = Field(description=\"Programming language used\")\n",
+    "\n",
+    "# Define a schema for a list of repositories\n",
+    "class ListRepositoriesSchema(BaseModel):\n",
+    "    repositories: List[RepositorySchema] = Field(description=\"List of GitHub trending repositories\")\n",
+    "\n",
+    "# Example Output JSON after AI extraction\n",
+    "{\n",
+    "    \"repositories\": [\n",
+    "        {\n",
+    "            \"name\": \"google-gemini/cookbook\",\n",
+    "            \"description\": \"Examples and guides for using the Gemini API\",\n",
+    "            \"stars\": 8036,\n",
+    "            \"forks\": 1001,\n",
+    "            \"today_stars\": 649,\n",
+    "            \"language\": \"Jupyter Notebook\"\n",
+    "        },\n",
+    "        {\n",
+    "            \"name\": \"TEN-framework/TEN-Agent\",\n",
+    "            \"description\": \"TEN Agent is a conversational AI powered by TEN, integrating Gemini 2.0 Multimodal Live API, OpenAI Realtime API, RTC, and more.\",\n",
+    "            \"stars\": 3224,\n",
+    "            \"forks\": 311,\n",
+    "            \"today_stars\": 361,\n",
+    "            \"language\": \"Python\"\n",
+    "        }\n",
+    "    ]\n",
+    "}\n",
+    "```\n",
+    "\n",
+    "Key Takeaways  \n",
+    "- **Simple Schema**: Perfect for small, straightforward extractions.  \n",
+    "- **Complex Schema**: Use nesting to extract lists or structured data, like \"a list of repositories.\"  \n",
+    "\n",
+    "Both approaches give the AI a clear structure to follow, ensuring that the extracted content matches exactly what you need.\n",
+    "</details>\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "dlrOEgZk_8V4"
+   },
+   "outputs": [],
+   "source": [
+    "from pydantic import BaseModel, Field\n",
+    "from typing import List, Dict, Optional\n",
+    "\n",
+    "# Schema for founder information\n",
+    "class FounderSchema(BaseModel):\n",
+    "    name: str = Field(description=\"Name of the founder\")\n",
+    "    role: str = Field(description=\"Role of the founder in the company\")\n",
+    "    linkedin: str = Field(description=\"LinkedIn profile of the founder\")\n",
+    "\n",
+    "# Schema for pricing plans\n",
+    "class PricingPlanSchema(BaseModel):\n",
+    "    tier: str = Field(description=\"Name of the pricing tier\")\n",
+    "    price: str = Field(description=\"Price of the plan\")\n",
+    "    credits: int = Field(description=\"Number of credits included in the plan\")\n",
+    "\n",
+    "# Schema for social links\n",
+    "class SocialLinksSchema(BaseModel):\n",
+    "    linkedin: str = Field(description=\"LinkedIn page of the company\")\n",
+    "    twitter: str = Field(description=\"Twitter page of the company\")\n",
+    "    github: str = Field(description=\"GitHub page of the company\")\n",
+    "\n",
+    "# Schema for company information\n",
+    "class CompanyInfoSchema(BaseModel):\n",
+    "    company_name: str = Field(description=\"Name of the company\")\n",
+    "    description: str = Field(description=\"Brief description of the company\")\n",
+    "    founders: List[FounderSchema] = Field(description=\"List of company founders\")\n",
+    "    logo: str = Field(description=\"Logo URL of the company\")\n",
+    "    partners: List[str] = Field(description=\"List of company partners\")\n",
+    "    pricing_plans: List[PricingPlanSchema] = Field(description=\"Details of pricing plans\")\n",
+    "    contact_emails: List[str] = Field(description=\"Contact emails of the company\")\n",
+    "    social_links: SocialLinksSchema = Field(description=\"Social links of the company\")\n",
+    "    privacy_policy: str = Field(description=\"URL to the privacy policy\")\n",
+    "    terms_of_service: str = Field(description=\"URL to the terms of service\")\n",
+    "    api_status: str = Field(description=\"API status page URL\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "cDGH0b2DkY63"
+   },
+   "source": [
+    "### \ud83d\ude80 Initialize `SGAI Client` and start extraction"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "4SLJgXgcob6L"
+   },
+   "source": [
+    "Initialize the client for scraping (there's also an async version [here](https://github.com/ScrapeGraphAI/scrapegraph-sdk/blob/main/scrapegraph-py/examples/async_smartscraper_example.py))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "PQI25GZvoCSk"
+   },
+   "outputs": [],
+   "source": [
+    "from scrapegraph_py import Client\n",
+    "\n",
+    "# Initialize the client with explicit API key\n",
+    "sgai_client = Client(api_key=sgai_api_key)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "M1KSXffZopUD"
+   },
+   "source": [
+    "Here we use `Smartscraper` service to extract structured data using AI from a webpage.\n",
+    "\n",
+    "\n",
+    "> If you already have an HTML file, you can upload it and use `Localscraper` instead.\n",
+    "\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "2FIKomclLNFx"
+   },
+   "outputs": [],
+   "source": [
+    "# Request for Trending Repositories\n",
+    "repo_response = sgai_client.smartscraper(\n",
+    "    website_url=\"https://scrapegraphai.com/\",\n",
+    "    user_prompt=\"Extract info about the company\",\n",
+    "    output_schema=CompanyInfoSchema,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "YZz1bqCIpoL8"
+   },
+   "source": [
+    "Print the response"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "executionInfo": {
+     "elapsed": 339,
+     "status": "ok",
+     "timestamp": 1734532533318,
+     "user": {
+      "displayName": "ScrapeGraphAI",
+      "userId": "10474323355016263615"
+     },
+     "user_tz": -60
+    },
+    "id": "F1VfD8B4LPc8",
+    "outputId": "8d7b2955-1569-4b3a-8ffe-014a8442dd12"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Request ID: 87a7ea1a-9dd4-4d1d-ae76-b419ead57c11\n",
+      "Company Info:\n",
+      "{\n",
+      "  \"company_name\": \"ScrapeGraphAI\",\n",
+      "  \"description\": \"ScrapeGraphAI is a powerful AI scraping API designed for efficient web data extraction to power LLM applications and AI agents. It enables developers to perform intelligent AI scraping and extract structured information from websites using advanced AI techniques.\",\n",
+      "  \"founders\": [\n",
+      "    {\n",
+      "      \"name\": \"\",\n",
+      "      \"role\": \"Founder & Technical Lead\",\n",
+      "      \"linkedin\": \"https://www.linkedin.com/in/perinim/\"\n",
+      "    },\n",
+      "    {\n",
+      "      \"name\": \"Marco Vinciguerra\",\n",
+      "      \"role\": \"Founder & Software Engineer\",\n",
+      "      \"linkedin\": \"https://www.linkedin.com/in/marco-vinciguerra-7ba365242/\"\n",
+      "    },\n",
+      "    {\n",
+      "      \"name\": \"Lorenzo Padoan\",\n",
+      "      \"role\": \"Founder & Product Engineer\",\n",
+      "      \"linkedin\": \"https://www.linkedin.com/in/lorenzo-padoan-4521a2154/\"\n",
+      "    }\n",
+      "  ],\n",
+      "  \"logo\": \"https://scrapegraphai.com/images/scrapegraphai_logo.svg\",\n",
+      "  \"partners\": [\n",
+      "    \"PostHog\",\n",
+      "    \"AWS\",\n",
+      "    \"NVIDIA\",\n",
+      "    \"JinaAI\",\n",
+      "    \"DagWorks\",\n",
+      "    \"Browserbase\",\n",
+      "    \"ScrapeDo\",\n",
+      "    \"HackerNews\",\n",
+      "    \"Medium\",\n",
+      "    \"HackADay\"\n",
+      "  ],\n",
+      "  \"pricing_plans\": [\n",
+      "    {\n",
+      "      \"tier\": \"Free\",\n",
+      "      \"price\": \"$0\",\n",
+      "      \"credits\": 100\n",
+      "    },\n",
+      "    {\n",
+      "      \"tier\": \"Starter\",\n",
+      "      \"price\": \"$20/month\",\n",
+      "      \"credits\": 5000\n",
+      "    },\n",
+      "    {\n",
+      "      \"tier\": \"Growth\",\n",
+      "      \"price\": \"$100/month\",\n",
+      "      \"credits\": 40000\n",
+      "    },\n",
+      "    {\n",
+      "      \"tier\": \"Pro\",\n",
+      "      \"price\": \"$500/month\",\n",
+      "      \"credits\": 250000\n",
+      "    }\n",
+      "  ],\n",
+      "  \"contact_emails\": [\n",
+      "    \"contact@scrapegraphai.com\"\n",
+      "  ],\n",
+      "  \"social_links\": {\n",
+      "    \"linkedin\": \"https://www.linkedin.com/company/101881123\",\n",
+      "    \"twitter\": \"https://x.com/scrapegraphai\",\n",
+      "    \"github\": \"https://github.com/ScrapeGraphAI/Scrapegraph-ai\"\n",
+      "  },\n",
+      "  \"privacy_policy\": \"https://scrapegraphai.com/privacy\",\n",
+      "  \"terms_of_service\": \"https://scrapegraphai.com/terms\",\n",
+      "  \"api_status\": \"https://scrapegraphapi.openstatus.dev\"\n",
+      "}\n"
+     ]
+    }
+   ],
+   "source": [
+    "import json\n",
+    "\n",
+    "# Print the response\n",
+    "request_id = repo_response['request_id']\n",
+    "result = repo_response['result']\n",
+    "\n",
+    "print(f\"Request ID: {request_id}\")\n",
+    "print(\"Company Info:\")\n",
+    "print(json.dumps(result, indent=2))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "2as65QLypwdb"
+   },
+   "source": [
+    "### \ud83d\udcbe Save the output to a `CSV` file"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "HTLVFgbVLLBR"
+   },
+   "source": [
+    "Let's create a pandas dataframe and show the tables with the extracted content"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "1lS9O1KOI51y"
+   },
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "# Flatten and save main company information\n",
+    "company_info = {\n",
+    "    \"company_name\": result[\"company_name\"],\n",
+    "    \"description\": result[\"description\"],\n",
+    "    \"logo\": result[\"logo\"],\n",
+    "    \"contact_emails\": \", \".join(result[\"contact_emails\"]),\n",
+    "    \"privacy_policy\": result[\"privacy_policy\"],\n",
+    "    \"terms_of_service\": result[\"terms_of_service\"],\n",
+    "    \"api_status\": result[\"api_status\"],\n",
+    "    \"linkedin\": result[\"social_links\"][\"linkedin\"],\n",
+    "    \"twitter\": result[\"social_links\"][\"twitter\"],\n",
+    "    \"github\": result[\"social_links\"].get(\"github\", None)\n",
+    "}\n",
+    "\n",
+    "# Creating dataframes\n",
+    "df_company = pd.DataFrame([company_info])\n",
+    "df_founders = pd.DataFrame(result[\"founders\"])\n",
+    "df_pricing = pd.DataFrame(result[\"pricing_plans\"])\n",
+    "df_partners = pd.DataFrame({\"partner\": result[\"partners\"]})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "JJI9huPkOY9t"
+   },
+   "source": [
+    "Show flattened tables"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 153
+    },
+    "executionInfo": {
+     "elapsed": 199,
+     "status": "ok",
+     "timestamp": 1734533012061,
+     "user": {
+      "displayName": "ScrapeGraphAI",
+      "userId": "10474323355016263615"
+     },
+     "user_tz": -60
+    },
+    "id": "vZs8ZutKOT63",
+    "outputId": "1278a9b9-2ab8-4150-8d37-328d4eb27e49"
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.google.colaboratory.intrinsic+json": {
+       "summary": "{\n  \"name\": \"df_company\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"company_name\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"ScrapeGraphAI\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"description\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"ScrapeGraphAI is a powerful AI scraping API designed for efficient web data extraction to power LLM applications and AI agents. It enables developers to perform intelligent AI scraping and extract structured information from websites using advanced AI techniques.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"logo\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"https://scrapegraphai.com/images/scrapegraphai_logo.svg\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"contact_emails\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"contact@scrapegraphai.com\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"privacy_policy\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"https://scrapegraphai.com/privacy\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"terms_of_service\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"https://scrapegraphai.com/terms\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"api_status\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"https://scrapegraphapi.openstatus.dev\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"linkedin\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"https://www.linkedin.com/company/101881123\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"twitter\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"https://x.com/scrapegraphai\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"github\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"https://github.com/ScrapeGraphAI/Scrapegraph-ai\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
+       "type": "dataframe",
+       "variable_name": "df_company"
+      },
+      "text/html": [
+       "\n",
+       "  <div id=\"df-b0d2d222-aa80-4dc1-8984-4ae5ea28dafb\" class=\"colab-df-container\">\n",
+       "    <div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>company_name</th>\n",
+       "      <th>description</th>\n",
+       "      <th>logo</th>\n",
+       "      <th>contact_emails</th>\n",
+       "      <th>privacy_policy</th>\n",
+       "      <th>terms_of_service</th>\n",
+       "      <th>api_status</th>\n",
+       "      <th>linkedin</th>\n",
+       "      <th>twitter</th>\n",
+       "      <th>github</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>ScrapeGraphAI</td>\n",
+       "      <td>ScrapeGraphAI is a powerful AI scraping API de...</td>\n",
+       "      <td>https://scrapegraphai.com/images/scrapegraphai...</td>\n",
+       "      <td>contact@scrapegraphai.com</td>\n",
+       "      <td>https://scrapegraphai.com/privacy</td>\n",
+       "      <td>https://scrapegraphai.com/terms</td>\n",
+       "      <td>https://scrapegraphapi.openstatus.dev</td>\n",
+       "      <td>https://www.linkedin.com/company/101881123</td>\n",
+       "      <td>https://x.com/scrapegraphai</td>\n",
+       "      <td>https://github.com/ScrapeGraphAI/Scrapegraph-ai</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>\n",
+       "    <div class=\"colab-df-buttons\">\n",
+       "\n",
+       "  <div class=\"colab-df-container\">\n",
+       "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b0d2d222-aa80-4dc1-8984-4ae5ea28dafb')\"\n",
+       "            title=\"Convert this dataframe to an interactive table.\"\n",
+       "            style=\"display:none;\">\n",
+       "\n",
+       "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+       "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+       "  </svg>\n",
+       "    </button>\n",
+       "\n",
+       "  <style>\n",
+       "    .colab-df-container {\n",
+       "      display:flex;\n",
+       "      gap: 12px;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-convert {\n",
+       "      background-color: #E8F0FE;\n",
+       "      border: none;\n",
+       "      border-radius: 50%;\n",
+       "      cursor: pointer;\n",
+       "      display: none;\n",
+       "      fill: #1967D2;\n",
+       "      height: 32px;\n",
+       "      padding: 0 0 0 0;\n",
+       "      width: 32px;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-convert:hover {\n",
+       "      background-color: #E2EBFA;\n",
+       "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "      fill: #174EA6;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-buttons div {\n",
+       "      margin-bottom: 4px;\n",
+       "    }\n",
+       "\n",
+       "    [theme=dark] .colab-df-convert {\n",
+       "      background-color: #3B4455;\n",
+       "      fill: #D2E3FC;\n",
+       "    }\n",
+       "\n",
+       "    [theme=dark] .colab-df-convert:hover {\n",
+       "      background-color: #434B5C;\n",
+       "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+       "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+       "      fill: #FFFFFF;\n",
+       "    }\n",
+       "  </style>\n",
+       "\n",
+       "    <script>\n",
+       "      const buttonEl =\n",
+       "        document.querySelector('#df-b0d2d222-aa80-4dc1-8984-4ae5ea28dafb button.colab-df-convert');\n",
+       "      buttonEl.style.display =\n",
+       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "\n",
+       "      async function convertToInteractive(key) {\n",
+       "        const element = document.querySelector('#df-b0d2d222-aa80-4dc1-8984-4ae5ea28dafb');\n",
+       "        const dataTable =\n",
+       "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+       "                                                    [key], {});\n",
+       "        if (!dataTable) return;\n",
+       "\n",
+       "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+       "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+       "          + ' to learn more about interactive tables.';\n",
+       "        element.innerHTML = '';\n",
+       "        dataTable['output_type'] = 'display_data';\n",
+       "        await google.colab.output.renderOutput(dataTable, element);\n",
+       "        const docLink = document.createElement('div');\n",
+       "        docLink.innerHTML = docLinkHtml;\n",
+       "        element.appendChild(docLink);\n",
+       "      }\n",
+       "    </script>\n",
+       "  </div>\n",
+       "\n",
+       "\n",
+       "  <div id=\"id_ea278784-498f-41a9-a197-b71952af827d\">\n",
+       "    <style>\n",
+       "      .colab-df-generate {\n",
+       "        background-color: #E8F0FE;\n",
+       "        border: none;\n",
+       "        border-radius: 50%;\n",
+       "        cursor: pointer;\n",
+       "        display: none;\n",
+       "        fill: #1967D2;\n",
+       "        height: 32px;\n",
+       "        padding: 0 0 0 0;\n",
+       "        width: 32px;\n",
+       "      }\n",
+       "\n",
+       "      .colab-df-generate:hover {\n",
+       "        background-color: #E2EBFA;\n",
+       "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "        fill: #174EA6;\n",
+       "      }\n",
+       "\n",
+       "      [theme=dark] .colab-df-generate {\n",
+       "        background-color: #3B4455;\n",
+       "        fill: #D2E3FC;\n",
+       "      }\n",
+       "\n",
+       "      [theme=dark] .colab-df-generate:hover {\n",
+       "        background-color: #434B5C;\n",
+       "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+       "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+       "        fill: #FFFFFF;\n",
+       "      }\n",
+       "    </style>\n",
+       "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df_company')\"\n",
+       "            title=\"Generate code using this dataframe.\"\n",
+       "            style=\"display:none;\">\n",
+       "\n",
+       "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+       "       width=\"24px\">\n",
+       "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
+       "  </svg>\n",
+       "    </button>\n",
+       "    <script>\n",
+       "      (() => {\n",
+       "      const buttonEl =\n",
+       "        document.querySelector('#id_ea278784-498f-41a9-a197-b71952af827d button.colab-df-generate');\n",
+       "      buttonEl.style.display =\n",
+       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "\n",
+       "      buttonEl.onclick = () => {\n",
+       "        google.colab.notebook.generateWithVariable('df_company');\n",
+       "      }\n",
+       "      })();\n",
+       "    </script>\n",
+       "  </div>\n",
+       "\n",
+       "    </div>\n",
+       "  </div>\n"
+      ],
+      "text/plain": [
+       "    company_name                                        description  \\\n",
+       "0  ScrapeGraphAI  ScrapeGraphAI is a powerful AI scraping API de...   \n",
+       "\n",
+       "                                                logo  \\\n",
+       "0  https://scrapegraphai.com/images/scrapegraphai...   \n",
+       "\n",
+       "              contact_emails                     privacy_policy  \\\n",
+       "0  contact@scrapegraphai.com  https://scrapegraphai.com/privacy   \n",
+       "\n",
+       "                  terms_of_service                             api_status  \\\n",
+       "0  https://scrapegraphai.com/terms  https://scrapegraphapi.openstatus.dev   \n",
+       "\n",
+       "                                     linkedin                      twitter  \\\n",
+       "0  https://www.linkedin.com/company/101881123  https://x.com/scrapegraphai   \n",
+       "\n",
+       "                                            github  \n",
+       "0  https://github.com/ScrapeGraphAI/Scrapegraph-ai  "
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_company"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 143
+    },
+    "executionInfo": {
+     "elapsed": 304,
+     "status": "ok",
+     "timestamp": 1734533051319,
+     "user": {
+      "displayName": "ScrapeGraphAI",
+      "userId": "10474323355016263615"
+     },
+     "user_tz": -60
+    },
+    "id": "QR-fyx5cOetl",
+    "outputId": "4b7d55ed-9ef4-44f9-9008-688d734ca820"
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.google.colaboratory.intrinsic+json": {
+       "summary": "{\n  \"name\": \"df_founders\",\n  \"rows\": 3,\n  \"fields\": [\n    {\n      \"column\": \"name\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"\",\n          \"Marco Vinciguerra\",\n          \"Lorenzo Padoan\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"role\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Founder & Technical Lead\",\n          \"Founder & Software Engineer\",\n          \"Founder & Product Engineer\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"linkedin\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"https://www.linkedin.com/in/perinim/\",\n          \"https://www.linkedin.com/in/marco-vinciguerra-7ba365242/\",\n          \"https://www.linkedin.com/in/lorenzo-padoan-4521a2154/\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
+       "type": "dataframe",
+       "variable_name": "df_founders"
+      },
+      "text/html": [
+       "\n",
+       "  <div id=\"df-e6271b34-031c-493a-82c7-3c701e9ecb52\" class=\"colab-df-container\">\n",
+       "    <div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>name</th>\n",
+       "      <th>role</th>\n",
+       "      <th>linkedin</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td></td>\n",
+       "      <td>Founder &amp; Technical Lead</td>\n",
+       "      <td>https://www.linkedin.com/in/perinim/</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Marco Vinciguerra</td>\n",
+       "      <td>Founder &amp; Software Engineer</td>\n",
+       "      <td>https://www.linkedin.com/in/marco-vinciguerra-...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Lorenzo Padoan</td>\n",
+       "      <td>Founder &amp; Product Engineer</td>\n",
+       "      <td>https://www.linkedin.com/in/lorenzo-padoan-452...</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>\n",
+       "    <div class=\"colab-df-buttons\">\n",
+       "\n",
+       "  <div class=\"colab-df-container\">\n",
+       "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e6271b34-031c-493a-82c7-3c701e9ecb52')\"\n",
+       "            title=\"Convert this dataframe to an interactive table.\"\n",
+       "            style=\"display:none;\">\n",
+       "\n",
+       "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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+       "  </svg>\n",
+       "    </button>\n",
+       "\n",
+       "  <style>\n",
+       "    .colab-df-container {\n",
+       "      display:flex;\n",
+       "      gap: 12px;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-convert {\n",
+       "      background-color: #E8F0FE;\n",
+       "      border: none;\n",
+       "      border-radius: 50%;\n",
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+       "      fill: #1967D2;\n",
+       "      height: 32px;\n",
+       "      padding: 0 0 0 0;\n",
+       "      width: 32px;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-convert:hover {\n",
+       "      background-color: #E2EBFA;\n",
+       "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "      fill: #174EA6;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-buttons div {\n",
+       "      margin-bottom: 4px;\n",
+       "    }\n",
+       "\n",
+       "    [theme=dark] .colab-df-convert {\n",
+       "      background-color: #3B4455;\n",
+       "      fill: #D2E3FC;\n",
+       "    }\n",
+       "\n",
+       "    [theme=dark] .colab-df-convert:hover {\n",
+       "      background-color: #434B5C;\n",
+       "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+       "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+       "      fill: #FFFFFF;\n",
+       "    }\n",
+       "  </style>\n",
+       "\n",
+       "    <script>\n",
+       "      const buttonEl =\n",
+       "        document.querySelector('#df-e6271b34-031c-493a-82c7-3c701e9ecb52 button.colab-df-convert');\n",
+       "      buttonEl.style.display =\n",
+       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "\n",
+       "      async function convertToInteractive(key) {\n",
+       "        const element = document.querySelector('#df-e6271b34-031c-493a-82c7-3c701e9ecb52');\n",
+       "        const dataTable =\n",
+       "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+       "                                                    [key], {});\n",
+       "        if (!dataTable) return;\n",
+       "\n",
+       "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+       "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+       "          + ' to learn more about interactive tables.';\n",
+       "        element.innerHTML = '';\n",
+       "        dataTable['output_type'] = 'display_data';\n",
+       "        await google.colab.output.renderOutput(dataTable, element);\n",
+       "        const docLink = document.createElement('div');\n",
+       "        docLink.innerHTML = docLinkHtml;\n",
+       "        element.appendChild(docLink);\n",
+       "      }\n",
+       "    </script>\n",
+       "  </div>\n",
+       "\n",
+       "\n",
+       "<div id=\"df-fea0bf16-7c1c-4428-8b69-c09713e41c72\">\n",
+       "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-fea0bf16-7c1c-4428-8b69-c09713e41c72')\"\n",
+       "            title=\"Suggest charts\"\n",
+       "            style=\"display:none;\">\n",
+       "\n",
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+       "    </g>\n",
+       "</svg>\n",
+       "  </button>\n",
+       "\n",
+       "<style>\n",
+       "  .colab-df-quickchart {\n",
+       "      --bg-color: #E8F0FE;\n",
+       "      --fill-color: #1967D2;\n",
+       "      --hover-bg-color: #E2EBFA;\n",
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+       "\n",
+       "  [theme=dark] .colab-df-quickchart {\n",
+       "      --bg-color: #3B4455;\n",
+       "      --fill-color: #D2E3FC;\n",
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+       "\n",
+       "  .colab-df-quickchart {\n",
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+       "    border: none;\n",
+       "    border-radius: 50%;\n",
+       "    cursor: pointer;\n",
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+       "    height: 32px;\n",
+       "    padding: 0;\n",
+       "    width: 32px;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart:hover {\n",
+       "    background-color: var(--hover-bg-color);\n",
+       "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "    fill: var(--button-hover-fill-color);\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart-complete:disabled,\n",
+       "  .colab-df-quickchart-complete:disabled:hover {\n",
+       "    background-color: var(--disabled-bg-color);\n",
+       "    fill: var(--disabled-fill-color);\n",
+       "    box-shadow: none;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-spinner {\n",
+       "    border: 2px solid var(--fill-color);\n",
+       "    border-color: transparent;\n",
+       "    border-bottom-color: var(--fill-color);\n",
+       "    animation:\n",
+       "      spin 1s steps(1) infinite;\n",
+       "  }\n",
+       "\n",
+       "  @keyframes spin {\n",
+       "    0% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "      border-left-color: var(--fill-color);\n",
+       "    }\n",
+       "    20% {\n",
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+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
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+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    40% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    60% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    80% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "    90% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "  }\n",
+       "</style>\n",
+       "\n",
+       "  <script>\n",
+       "    async function quickchart(key) {\n",
+       "      const quickchartButtonEl =\n",
+       "        document.querySelector('#' + key + ' button');\n",
+       "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+       "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+       "      try {\n",
+       "        const charts = await google.colab.kernel.invokeFunction(\n",
+       "            'suggestCharts', [key], {});\n",
+       "      } catch (error) {\n",
+       "        console.error('Error during call to suggestCharts:', error);\n",
+       "      }\n",
+       "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+       "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+       "    }\n",
+       "    (() => {\n",
+       "      let quickchartButtonEl =\n",
+       "        document.querySelector('#df-fea0bf16-7c1c-4428-8b69-c09713e41c72 button');\n",
+       "      quickchartButtonEl.style.display =\n",
+       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "    })();\n",
+       "  </script>\n",
+       "</div>\n",
+       "\n",
+       "  <div id=\"id_b7848ba8-666c-4518-b408-a7861b414f0e\">\n",
+       "    <style>\n",
+       "      .colab-df-generate {\n",
+       "        background-color: #E8F0FE;\n",
+       "        border: none;\n",
+       "        border-radius: 50%;\n",
+       "        cursor: pointer;\n",
+       "        display: none;\n",
+       "        fill: #1967D2;\n",
+       "        height: 32px;\n",
+       "        padding: 0 0 0 0;\n",
+       "        width: 32px;\n",
+       "      }\n",
+       "\n",
+       "      .colab-df-generate:hover {\n",
+       "        background-color: #E2EBFA;\n",
+       "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "        fill: #174EA6;\n",
+       "      }\n",
+       "\n",
+       "      [theme=dark] .colab-df-generate {\n",
+       "        background-color: #3B4455;\n",
+       "        fill: #D2E3FC;\n",
+       "      }\n",
+       "\n",
+       "      [theme=dark] .colab-df-generate:hover {\n",
+       "        background-color: #434B5C;\n",
+       "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+       "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+       "        fill: #FFFFFF;\n",
+       "      }\n",
+       "    </style>\n",
+       "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df_founders')\"\n",
+       "            title=\"Generate code using this dataframe.\"\n",
+       "            style=\"display:none;\">\n",
+       "\n",
+       "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+       "       width=\"24px\">\n",
+       "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
+       "  </svg>\n",
+       "    </button>\n",
+       "    <script>\n",
+       "      (() => {\n",
+       "      const buttonEl =\n",
+       "        document.querySelector('#id_b7848ba8-666c-4518-b408-a7861b414f0e button.colab-df-generate');\n",
+       "      buttonEl.style.display =\n",
+       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "\n",
+       "      buttonEl.onclick = () => {\n",
+       "        google.colab.notebook.generateWithVariable('df_founders');\n",
+       "      }\n",
+       "      })();\n",
+       "    </script>\n",
+       "  </div>\n",
+       "\n",
+       "    </div>\n",
+       "  </div>\n"
+      ],
+      "text/plain": [
+       "                name                         role  \\\n",
+       "0            Founder & Technical Lead   \n",
+       "1  Marco Vinciguerra  Founder & Software Engineer   \n",
+       "2     Lorenzo Padoan   Founder & Product Engineer   \n",
+       "\n",
+       "                                            linkedin  \n",
+       "0               https://www.linkedin.com/in/perinim/  \n",
+       "1  https://www.linkedin.com/in/marco-vinciguerra-...  \n",
+       "2  https://www.linkedin.com/in/lorenzo-padoan-452...  "
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_founders"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 175
+    },
+    "executionInfo": {
+     "elapsed": 312,
+     "status": "ok",
+     "timestamp": 1734533059550,
+     "user": {
+      "displayName": "ScrapeGraphAI",
+      "userId": "10474323355016263615"
+     },
+     "user_tz": -60
+    },
+    "id": "SWpCvl53OgyQ",
+    "outputId": "c256f5e5-227a-4df4-da16-d0021aaf03a1"
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.google.colaboratory.intrinsic+json": {
+       "summary": "{\n  \"name\": \"df_pricing\",\n  \"rows\": 4,\n  \"fields\": [\n    {\n      \"column\": \"tier\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"Starter\",\n          \"Pro\",\n          \"Free\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"price\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"$20/month\",\n          \"$500/month\",\n          \"$0\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"credits\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 118819,\n        \"min\": 100,\n        \"max\": 250000,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          5000,\n          250000,\n          100\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
+       "type": "dataframe",
+       "variable_name": "df_pricing"
+      },
+      "text/html": [
+       "\n",
+       "  <div id=\"df-038000b4-e4e0-4aa6-9d61-cf0482a146e6\" class=\"colab-df-container\">\n",
+       "    <div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>tier</th>\n",
+       "      <th>price</th>\n",
+       "      <th>credits</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Free</td>\n",
+       "      <td>$0</td>\n",
+       "      <td>100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Starter</td>\n",
+       "      <td>$20/month</td>\n",
+       "      <td>5000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Growth</td>\n",
+       "      <td>$100/month</td>\n",
+       "      <td>40000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Pro</td>\n",
+       "      <td>$500/month</td>\n",
+       "      <td>250000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>\n",
+       "    <div class=\"colab-df-buttons\">\n",
+       "\n",
+       "  <div class=\"colab-df-container\">\n",
+       "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-038000b4-e4e0-4aa6-9d61-cf0482a146e6')\"\n",
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+       "            style=\"display:none;\">\n",
+       "\n",
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+       "  </svg>\n",
+       "    </button>\n",
+       "\n",
+       "  <style>\n",
+       "    .colab-df-container {\n",
+       "      display:flex;\n",
+       "      gap: 12px;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-convert {\n",
+       "      background-color: #E8F0FE;\n",
+       "      border: none;\n",
+       "      border-radius: 50%;\n",
+       "      cursor: pointer;\n",
+       "      display: none;\n",
+       "      fill: #1967D2;\n",
+       "      height: 32px;\n",
+       "      padding: 0 0 0 0;\n",
+       "      width: 32px;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-convert:hover {\n",
+       "      background-color: #E2EBFA;\n",
+       "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "      fill: #174EA6;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-buttons div {\n",
+       "      margin-bottom: 4px;\n",
+       "    }\n",
+       "\n",
+       "    [theme=dark] .colab-df-convert {\n",
+       "      background-color: #3B4455;\n",
+       "      fill: #D2E3FC;\n",
+       "    }\n",
+       "\n",
+       "    [theme=dark] .colab-df-convert:hover {\n",
+       "      background-color: #434B5C;\n",
+       "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+       "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+       "      fill: #FFFFFF;\n",
+       "    }\n",
+       "  </style>\n",
+       "\n",
+       "    <script>\n",
+       "      const buttonEl =\n",
+       "        document.querySelector('#df-038000b4-e4e0-4aa6-9d61-cf0482a146e6 button.colab-df-convert');\n",
+       "      buttonEl.style.display =\n",
+       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "\n",
+       "      async function convertToInteractive(key) {\n",
+       "        const element = document.querySelector('#df-038000b4-e4e0-4aa6-9d61-cf0482a146e6');\n",
+       "        const dataTable =\n",
+       "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+       "                                                    [key], {});\n",
+       "        if (!dataTable) return;\n",
+       "\n",
+       "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+       "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+       "          + ' to learn more about interactive tables.';\n",
+       "        element.innerHTML = '';\n",
+       "        dataTable['output_type'] = 'display_data';\n",
+       "        await google.colab.output.renderOutput(dataTable, element);\n",
+       "        const docLink = document.createElement('div');\n",
+       "        docLink.innerHTML = docLinkHtml;\n",
+       "        element.appendChild(docLink);\n",
+       "      }\n",
+       "    </script>\n",
+       "  </div>\n",
+       "\n",
+       "\n",
+       "<div id=\"df-092eddc8-f108-49e4-baa8-6eddc7d4ed94\">\n",
+       "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-092eddc8-f108-49e4-baa8-6eddc7d4ed94')\"\n",
+       "            title=\"Suggest charts\"\n",
+       "            style=\"display:none;\">\n",
+       "\n",
+       "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+       "     width=\"24px\">\n",
+       "    <g>\n",
+       "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+       "    </g>\n",
+       "</svg>\n",
+       "  </button>\n",
+       "\n",
+       "<style>\n",
+       "  .colab-df-quickchart {\n",
+       "      --bg-color: #E8F0FE;\n",
+       "      --fill-color: #1967D2;\n",
+       "      --hover-bg-color: #E2EBFA;\n",
+       "      --hover-fill-color: #174EA6;\n",
+       "      --disabled-fill-color: #AAA;\n",
+       "      --disabled-bg-color: #DDD;\n",
+       "  }\n",
+       "\n",
+       "  [theme=dark] .colab-df-quickchart {\n",
+       "      --bg-color: #3B4455;\n",
+       "      --fill-color: #D2E3FC;\n",
+       "      --hover-bg-color: #434B5C;\n",
+       "      --hover-fill-color: #FFFFFF;\n",
+       "      --disabled-bg-color: #3B4455;\n",
+       "      --disabled-fill-color: #666;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart {\n",
+       "    background-color: var(--bg-color);\n",
+       "    border: none;\n",
+       "    border-radius: 50%;\n",
+       "    cursor: pointer;\n",
+       "    display: none;\n",
+       "    fill: var(--fill-color);\n",
+       "    height: 32px;\n",
+       "    padding: 0;\n",
+       "    width: 32px;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart:hover {\n",
+       "    background-color: var(--hover-bg-color);\n",
+       "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "    fill: var(--button-hover-fill-color);\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart-complete:disabled,\n",
+       "  .colab-df-quickchart-complete:disabled:hover {\n",
+       "    background-color: var(--disabled-bg-color);\n",
+       "    fill: var(--disabled-fill-color);\n",
+       "    box-shadow: none;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-spinner {\n",
+       "    border: 2px solid var(--fill-color);\n",
+       "    border-color: transparent;\n",
+       "    border-bottom-color: var(--fill-color);\n",
+       "    animation:\n",
+       "      spin 1s steps(1) infinite;\n",
+       "  }\n",
+       "\n",
+       "  @keyframes spin {\n",
+       "    0% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "      border-left-color: var(--fill-color);\n",
+       "    }\n",
+       "    20% {\n",
+       "      border-color: transparent;\n",
+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    30% {\n",
+       "      border-color: transparent;\n",
+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    40% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    60% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    80% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "    90% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "  }\n",
+       "</style>\n",
+       "\n",
+       "  <script>\n",
+       "    async function quickchart(key) {\n",
+       "      const quickchartButtonEl =\n",
+       "        document.querySelector('#' + key + ' button');\n",
+       "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+       "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+       "      try {\n",
+       "        const charts = await google.colab.kernel.invokeFunction(\n",
+       "            'suggestCharts', [key], {});\n",
+       "      } catch (error) {\n",
+       "        console.error('Error during call to suggestCharts:', error);\n",
+       "      }\n",
+       "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+       "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+       "    }\n",
+       "    (() => {\n",
+       "      let quickchartButtonEl =\n",
+       "        document.querySelector('#df-092eddc8-f108-49e4-baa8-6eddc7d4ed94 button');\n",
+       "      quickchartButtonEl.style.display =\n",
+       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "    })();\n",
+       "  </script>\n",
+       "</div>\n",
+       "\n",
+       "  <div id=\"id_e8056e3a-1717-4066-8b9c-332d574d7a7e\">\n",
+       "    <style>\n",
+       "      .colab-df-generate {\n",
+       "        background-color: #E8F0FE;\n",
+       "        border: none;\n",
+       "        border-radius: 50%;\n",
+       "        cursor: pointer;\n",
+       "        display: none;\n",
+       "        fill: #1967D2;\n",
+       "        height: 32px;\n",
+       "        padding: 0 0 0 0;\n",
+       "        width: 32px;\n",
+       "      }\n",
+       "\n",
+       "      .colab-df-generate:hover {\n",
+       "        background-color: #E2EBFA;\n",
+       "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "        fill: #174EA6;\n",
+       "      }\n",
+       "\n",
+       "      [theme=dark] .colab-df-generate {\n",
+       "        background-color: #3B4455;\n",
+       "        fill: #D2E3FC;\n",
+       "      }\n",
+       "\n",
+       "      [theme=dark] .colab-df-generate:hover {\n",
+       "        background-color: #434B5C;\n",
+       "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+       "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+       "        fill: #FFFFFF;\n",
+       "      }\n",
+       "    </style>\n",
+       "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df_pricing')\"\n",
+       "            title=\"Generate code using this dataframe.\"\n",
+       "            style=\"display:none;\">\n",
+       "\n",
+       "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+       "       width=\"24px\">\n",
+       "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
+       "  </svg>\n",
+       "    </button>\n",
+       "    <script>\n",
+       "      (() => {\n",
+       "      const buttonEl =\n",
+       "        document.querySelector('#id_e8056e3a-1717-4066-8b9c-332d574d7a7e button.colab-df-generate');\n",
+       "      buttonEl.style.display =\n",
+       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "\n",
+       "      buttonEl.onclick = () => {\n",
+       "        google.colab.notebook.generateWithVariable('df_pricing');\n",
+       "      }\n",
+       "      })();\n",
+       "    </script>\n",
+       "  </div>\n",
+       "\n",
+       "    </div>\n",
+       "  </div>\n"
+      ],
+      "text/plain": [
+       "      tier       price  credits\n",
+       "0     Free          $0      100\n",
+       "1  Starter   $20/month     5000\n",
+       "2   Growth  $100/month    40000\n",
+       "3      Pro  $500/month   250000"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_pricing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 363
+    },
+    "executionInfo": {
+     "elapsed": 216,
+     "status": "ok",
+     "timestamp": 1734533067079,
+     "user": {
+      "displayName": "ScrapeGraphAI",
+      "userId": "10474323355016263615"
+     },
+     "user_tz": -60
+    },
+    "id": "jNLaHXlEOisi",
+    "outputId": "6f075db5-fc3f-437d-9aaa-d6f8e3085c49"
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.google.colaboratory.intrinsic+json": {
+       "summary": "{\n  \"name\": \"df_partners\",\n  \"rows\": 10,\n  \"fields\": [\n    {\n      \"column\": \"partner\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 10,\n        \"samples\": [\n          \"Medium\",\n          \"AWS\",\n          \"Browserbase\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
+       "type": "dataframe",
+       "variable_name": "df_partners"
+      },
+      "text/html": [
+       "\n",
+       "  <div id=\"df-cfeb4fa6-745e-4edb-87a3-9c425abe859e\" class=\"colab-df-container\">\n",
+       "    <div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>partner</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>PostHog</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>AWS</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>NVIDIA</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>JinaAI</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>DagWorks</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Browserbase</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>ScrapeDo</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>HackerNews</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>Medium</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>HackADay</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>\n",
+       "    <div class=\"colab-df-buttons\">\n",
+       "\n",
+       "  <div class=\"colab-df-container\">\n",
+       "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-cfeb4fa6-745e-4edb-87a3-9c425abe859e')\"\n",
+       "            title=\"Convert this dataframe to an interactive table.\"\n",
+       "            style=\"display:none;\">\n",
+       "\n",
+       "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+       "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+       "  </svg>\n",
+       "    </button>\n",
+       "\n",
+       "  <style>\n",
+       "    .colab-df-container {\n",
+       "      display:flex;\n",
+       "      gap: 12px;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-convert {\n",
+       "      background-color: #E8F0FE;\n",
+       "      border: none;\n",
+       "      border-radius: 50%;\n",
+       "      cursor: pointer;\n",
+       "      display: none;\n",
+       "      fill: #1967D2;\n",
+       "      height: 32px;\n",
+       "      padding: 0 0 0 0;\n",
+       "      width: 32px;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-convert:hover {\n",
+       "      background-color: #E2EBFA;\n",
+       "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "      fill: #174EA6;\n",
+       "    }\n",
+       "\n",
+       "    .colab-df-buttons div {\n",
+       "      margin-bottom: 4px;\n",
+       "    }\n",
+       "\n",
+       "    [theme=dark] .colab-df-convert {\n",
+       "      background-color: #3B4455;\n",
+       "      fill: #D2E3FC;\n",
+       "    }\n",
+       "\n",
+       "    [theme=dark] .colab-df-convert:hover {\n",
+       "      background-color: #434B5C;\n",
+       "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+       "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+       "      fill: #FFFFFF;\n",
+       "    }\n",
+       "  </style>\n",
+       "\n",
+       "    <script>\n",
+       "      const buttonEl =\n",
+       "        document.querySelector('#df-cfeb4fa6-745e-4edb-87a3-9c425abe859e button.colab-df-convert');\n",
+       "      buttonEl.style.display =\n",
+       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "\n",
+       "      async function convertToInteractive(key) {\n",
+       "        const element = document.querySelector('#df-cfeb4fa6-745e-4edb-87a3-9c425abe859e');\n",
+       "        const dataTable =\n",
+       "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+       "                                                    [key], {});\n",
+       "        if (!dataTable) return;\n",
+       "\n",
+       "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+       "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+       "          + ' to learn more about interactive tables.';\n",
+       "        element.innerHTML = '';\n",
+       "        dataTable['output_type'] = 'display_data';\n",
+       "        await google.colab.output.renderOutput(dataTable, element);\n",
+       "        const docLink = document.createElement('div');\n",
+       "        docLink.innerHTML = docLinkHtml;\n",
+       "        element.appendChild(docLink);\n",
+       "      }\n",
+       "    </script>\n",
+       "  </div>\n",
+       "\n",
+       "\n",
+       "<div id=\"df-0c94c86c-bfa9-44b7-a34c-7fbab23404f3\">\n",
+       "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-0c94c86c-bfa9-44b7-a34c-7fbab23404f3')\"\n",
+       "            title=\"Suggest charts\"\n",
+       "            style=\"display:none;\">\n",
+       "\n",
+       "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+       "     width=\"24px\">\n",
+       "    <g>\n",
+       "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+       "    </g>\n",
+       "</svg>\n",
+       "  </button>\n",
+       "\n",
+       "<style>\n",
+       "  .colab-df-quickchart {\n",
+       "      --bg-color: #E8F0FE;\n",
+       "      --fill-color: #1967D2;\n",
+       "      --hover-bg-color: #E2EBFA;\n",
+       "      --hover-fill-color: #174EA6;\n",
+       "      --disabled-fill-color: #AAA;\n",
+       "      --disabled-bg-color: #DDD;\n",
+       "  }\n",
+       "\n",
+       "  [theme=dark] .colab-df-quickchart {\n",
+       "      --bg-color: #3B4455;\n",
+       "      --fill-color: #D2E3FC;\n",
+       "      --hover-bg-color: #434B5C;\n",
+       "      --hover-fill-color: #FFFFFF;\n",
+       "      --disabled-bg-color: #3B4455;\n",
+       "      --disabled-fill-color: #666;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart {\n",
+       "    background-color: var(--bg-color);\n",
+       "    border: none;\n",
+       "    border-radius: 50%;\n",
+       "    cursor: pointer;\n",
+       "    display: none;\n",
+       "    fill: var(--fill-color);\n",
+       "    height: 32px;\n",
+       "    padding: 0;\n",
+       "    width: 32px;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart:hover {\n",
+       "    background-color: var(--hover-bg-color);\n",
+       "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "    fill: var(--button-hover-fill-color);\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-quickchart-complete:disabled,\n",
+       "  .colab-df-quickchart-complete:disabled:hover {\n",
+       "    background-color: var(--disabled-bg-color);\n",
+       "    fill: var(--disabled-fill-color);\n",
+       "    box-shadow: none;\n",
+       "  }\n",
+       "\n",
+       "  .colab-df-spinner {\n",
+       "    border: 2px solid var(--fill-color);\n",
+       "    border-color: transparent;\n",
+       "    border-bottom-color: var(--fill-color);\n",
+       "    animation:\n",
+       "      spin 1s steps(1) infinite;\n",
+       "  }\n",
+       "\n",
+       "  @keyframes spin {\n",
+       "    0% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "      border-left-color: var(--fill-color);\n",
+       "    }\n",
+       "    20% {\n",
+       "      border-color: transparent;\n",
+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    30% {\n",
+       "      border-color: transparent;\n",
+       "      border-left-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    40% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-top-color: var(--fill-color);\n",
+       "    }\n",
+       "    60% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "    }\n",
+       "    80% {\n",
+       "      border-color: transparent;\n",
+       "      border-right-color: var(--fill-color);\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "    90% {\n",
+       "      border-color: transparent;\n",
+       "      border-bottom-color: var(--fill-color);\n",
+       "    }\n",
+       "  }\n",
+       "</style>\n",
+       "\n",
+       "  <script>\n",
+       "    async function quickchart(key) {\n",
+       "      const quickchartButtonEl =\n",
+       "        document.querySelector('#' + key + ' button');\n",
+       "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+       "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+       "      try {\n",
+       "        const charts = await google.colab.kernel.invokeFunction(\n",
+       "            'suggestCharts', [key], {});\n",
+       "      } catch (error) {\n",
+       "        console.error('Error during call to suggestCharts:', error);\n",
+       "      }\n",
+       "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+       "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+       "    }\n",
+       "    (() => {\n",
+       "      let quickchartButtonEl =\n",
+       "        document.querySelector('#df-0c94c86c-bfa9-44b7-a34c-7fbab23404f3 button');\n",
+       "      quickchartButtonEl.style.display =\n",
+       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "    })();\n",
+       "  </script>\n",
+       "</div>\n",
+       "\n",
+       "  <div id=\"id_7ac6f3b5-9f2c-42c0-8154-8c5d1ed8cc37\">\n",
+       "    <style>\n",
+       "      .colab-df-generate {\n",
+       "        background-color: #E8F0FE;\n",
+       "        border: none;\n",
+       "        border-radius: 50%;\n",
+       "        cursor: pointer;\n",
+       "        display: none;\n",
+       "        fill: #1967D2;\n",
+       "        height: 32px;\n",
+       "        padding: 0 0 0 0;\n",
+       "        width: 32px;\n",
+       "      }\n",
+       "\n",
+       "      .colab-df-generate:hover {\n",
+       "        background-color: #E2EBFA;\n",
+       "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+       "        fill: #174EA6;\n",
+       "      }\n",
+       "\n",
+       "      [theme=dark] .colab-df-generate {\n",
+       "        background-color: #3B4455;\n",
+       "        fill: #D2E3FC;\n",
+       "      }\n",
+       "\n",
+       "      [theme=dark] .colab-df-generate:hover {\n",
+       "        background-color: #434B5C;\n",
+       "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+       "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+       "        fill: #FFFFFF;\n",
+       "      }\n",
+       "    </style>\n",
+       "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df_partners')\"\n",
+       "            title=\"Generate code using this dataframe.\"\n",
+       "            style=\"display:none;\">\n",
+       "\n",
+       "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+       "       width=\"24px\">\n",
+       "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
+       "  </svg>\n",
+       "    </button>\n",
+       "    <script>\n",
+       "      (() => {\n",
+       "      const buttonEl =\n",
+       "        document.querySelector('#id_7ac6f3b5-9f2c-42c0-8154-8c5d1ed8cc37 button.colab-df-generate');\n",
+       "      buttonEl.style.display =\n",
+       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+       "\n",
+       "      buttonEl.onclick = () => {\n",
+       "        google.colab.notebook.generateWithVariable('df_partners');\n",
+       "      }\n",
+       "      })();\n",
+       "    </script>\n",
+       "  </div>\n",
+       "\n",
+       "    </div>\n",
+       "  </div>\n"
+      ],
+      "text/plain": [
+       "       partner\n",
+       "0      PostHog\n",
+       "1          AWS\n",
+       "2       NVIDIA\n",
+       "3       JinaAI\n",
+       "4     DagWorks\n",
+       "5  Browserbase\n",
+       "6     ScrapeDo\n",
+       "7   HackerNews\n",
+       "8       Medium\n",
+       "9     HackADay"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_partners"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "v0CBYVk7qA5Z"
+   },
+   "source": [
+    "Save the results to CSV"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "executionInfo": {
+     "elapsed": 213,
+     "status": "ok",
+     "timestamp": 1734533092882,
+     "user": {
+      "displayName": "ScrapeGraphAI",
+      "userId": "10474323355016263615"
+     },
+     "user_tz": -60
+    },
+    "id": "BtEbB9pmQGhO",
+    "outputId": "3f05c8ba-7b34-4b53-ab20-bfcc78060557"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Data saved to CSV files\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Save the DataFrames to a CSV file\n",
+    "df_company.to_csv(\"company_info.csv\", index=False)\n",
+    "df_founders.to_csv(\"founders.csv\", index=False)\n",
+    "df_pricing.to_csv(\"pricing_plans.csv\", index=False)\n",
+    "df_partners.to_csv(\"partners.csv\", index=False)\n",
+    "# Print confirmation\n",
+    "print(\"Data saved to CSV files\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "-1SZT8VzTZNd"
+   },
+   "source": [
+    "## \ud83d\udd17 Resources"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "dUi2LtMLRDDR"
+   },
+   "source": [
+    "\n",
+    "<p align=\"left\">\n",
+    "  <img src=\"https://raw.githubusercontent.com/VinciGit00/Scrapegraph-ai/main/docs/assets/api-banner.png\"\n",
+    "       alt=\"ScrapeGraph API Banner\" width=\"600\">\n",
+    "</p>\n",
+    "\n",
+    "\n",
+    "- \ud83d\ude80 **Get your API Key:** [ScrapeGraphAI Dashboard](https://dashboard.scrapegraphai.com)  \n",
+    "- \ud83d\udc19 **GitHub:** [ScrapeGraphAI GitHub](https://github.com/scrapegraphai)  \n",
+    "- \ud83d\udcbc **LinkedIn:** [ScrapeGraphAI LinkedIn](https://www.linkedin.com/company/scrapegraphai/)  \n",
+    "- \ud83d\udc26 **Twitter:** [ScrapeGraphAI Twitter](https://twitter.com/scrapegraphai)  \n",
+    "- \ud83d\udcac **Discord:** [Join our Discord Community](https://discord.gg/uJN7TYcpNa)  \n",
+    "\n",
+    "Made with \u2764\ufe0f by the [ScrapeGraphAI](https://scrapegraphai.com) Team  \n"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "authorship_tag": "ABX9TyO57uo4LpNqAm10rmE0B6Q5",
+   "collapsed_sections": [
+    "IzsyDXEWwPVt"
+   ],
+   "provenance": []
+  },
+  "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": "3.12.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}