Fabric-Analytics-MCP

{ "cells": [ { "cell_type": "markdown", "id": "43333c11", "metadata": {}, "source": [ "# Sample Notebook for Microsoft Fabric\n", "\n", "This is a sample notebook that demonstrates the structure supported by the Fabric Analytics MCP Server." ] }, { "cell_type": "code", "execution_count": null, "id": "342f31ff", "metadata": {}, "outputs": [], "source": [ "# Import required libraries\n", "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "\n", "print('Welcome to Microsoft Fabric Analytics!')" ] }, { "cell_type": "code", "execution_count": null, "id": "dee21013", "metadata": {}, "outputs": [], "source": [ "# Create sample data\n", "data = {\n", " 'date': pd.date_range('2024-01-01', periods=100, freq='D'),\n", " 'value': np.random.randn(100).cumsum()\n", "}\n", "df = pd.DataFrame(data)\n", "\n", "print(f'Generated {len(df)} rows of sample data')\n", "print(df.head())" ] }, { "cell_type": "code", "execution_count": null, "id": "044115c9", "metadata": {}, "outputs": [], "source": [ "# Create visualization\n", "plt.figure(figsize=(12, 6))\n", "plt.plot(df['date'], df['value'])\n", "plt.title('Sample Time Series Data')\n", "plt.xlabel('Date')\n", "plt.ylabel('Value')\n", "plt.xticks(rotation=45)\n", "plt.tight_layout()\n", "plt.show()" ] } ], "metadata": { "language_info": { "name": "python" } }, "nbformat": 4, "nbformat_minor": 5 }