2022_numpy.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "2022_numpy.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyPlq91RI1KcN9JThtXk84sX",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/ildacec/Python_Reto100diasconPython/blob/main/2022_numpy.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount ('/content/drive')\n",
        "\n",
        "from IPython.display import Image\n",
        "#filename = \"img1.png\", width = 600, height = 300\n",
        "Image (filename ='/content/drive/MyDrive/Colab Notebooks/Python/numpy-1-1-.png', width = 300, height = 200)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "id": "YIL0YeweQ1cO",
        "outputId": "de8ffae9-e609-48d6-c86a-8aea7c59000a"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.core.display.Image object>"
            ],
            "image/png": 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          },
          "metadata": {
            "image/png": {
              "width": 300,
              "height": 200
            }
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Biblioteca NumPy \n",
        "\n",
        "NumPy significa Python numérico (\"Numerical Python\").\n",
        "\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "Es una biblioteca de Python para realizar cálculos numéricos a gran escala.\n",
        "Las matrices se utilizan con mucha frecuencia en la Ciencia de datos, donde la velocidad y los recursos son muy importantes, para responder problemas de aprendizaje automático.\n",
        "\n",
        "\n",
        "---\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "jB-ftSQQRaMh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#PIP\n",
        "#Si tu usas  pip, puedes instalar NumPy con el siguiente comando:\n",
        "\n",
        "pip install numpy\n"
      ],
      "metadata": {
        "id": "lHYg-JyjRqAP"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#Para comenzar a usar Numpy en su script, tienes que importarlo.\n",
        "import numpy as np\n"
      ],
      "metadata": {
        "id": "U37fFIg-RvP4"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "v0IYUptIEYDQ",
        "outputId": "afe76993-3d1e-443e-d663-0caf18437e6d"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['1' '2' '3' '4' '5']\n"
          ]
        }
      ],
      "source": [
        "#PyLadiesPanamá\n",
        "#Biblioteca NumPy\n",
        "\n",
        "arr = np.array(['1', '2', '3', '4', '5'])\n",
        "print(arr)"
      ]
    }
  ]
}