{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "LXlSRBeHtETj",
        "outputId": "d3524f5c-31a7-448a-ffe4-0fb5835f2d6e"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 500x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# Ejercicio Extra 3.1.1.\n",
        "\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Coordenadas de los vértices (cerrando la figura con el primer punto al final)\n",
        "x = [0, 100, 100, 0, 0]\n",
        "y = [0, 0, 100, 100, 0]\n",
        "\n",
        "# Crear la figura\n",
        "plt.figure(figsize=(5,5))\n",
        "plt.plot(x, y, 'b-', linewidth=2)\n",
        "\n",
        "# Configuración del gráfico\n",
        "plt.title(\"Cuadrado de 100 mm de lado\")\n",
        "plt.gca().set_aspect('equal', adjustable='box')  # mantener proporción 1:1\n",
        "plt.grid(True)\n",
        "plt.xlabel(\"mm en eje X\")\n",
        "plt.ylabel(\"mm en eje Y\")\n",
        "\n",
        "plt.show()"
      ]
    }
  ]
}