Work_numpy.ipynb

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        "<a href=\"https://colab.research.google.com/github/julius-duru/COVID-19/blob/master/Work_numpy.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "source": [
        "## Install numpy library\n",
        "##First preference , ANAconda\n",
        "## conda install numpy\n",
        "## pip instal numpy\n",
        "import numpy as np"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pwd #present working directory"
      ],
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          "height": 35
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        "id": "-km8iOdsvZIH",
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              "'/content'"
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          "execution_count": 2
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      ]
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    {
      "cell_type": "code",
      "source": [
        "myl = [1,2,30,40,-50]\n",
        "print(type(myl))\n",
        "myl"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D1o7Tjmdv7Bp",
        "outputId": "66670d42-6cd3-45ce-9d03-506590c4a712"
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      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'list'>\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[1, 2, 30, 40, -50]"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#From list create array\n",
        "mya = np.array(myl)\n",
        "print(mya.dtype)\n",
        "print(mya)"
      ],
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        "colab": {
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        },
        "id": "ubqZDEbRwx3c",
        "outputId": "dfbbc6c4-aee8-4a6d-eb33-420139347aae"
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      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "int64\n",
            "[  1   2  30  40 -50]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
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      "metadata": {
        "id": "WPeXUyO10mk9"
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      "execution_count": null,
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      "cell_type": "code",
      "source": [
        "# Convert ages of family mebers to array\n",
        "famage = [44,46,48,50,52,54,56,58,60]\n",
        "age = np.array(famage)\n",
        "print(age)\n",
        "print(type(age))\n",
        "print(type(famage))\n",
        "print(age.dtype)"
      ],
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        "id": "Oa6l-ueGxl_H",
        "outputId": "f080057d-c612-4596-c303-7c41822f9ba0"
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      "execution_count": 10,
      "outputs": [
        {
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          "name": "stdout",
          "text": [
            "[44 46 48 50 52 54 56 58 60]\n",
            "<class 'numpy.ndarray'>\n",
            "<class 'list'>\n",
            "int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sh = mya.shape\n",
        "print(type(sh))\n",
        "print(sh)\n",
        "print(sh[0])\n",
        "\n"
      ],
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      "execution_count": 11,
      "outputs": [
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          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'tuple'>\n",
            "(5,)\n",
            "5\n"
          ]
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      ]
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      "cell_type": "code",
      "source": [
        "mya.dtype"
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              "dtype('int64')"
            ]
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          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mya.itemsize"
      ],
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      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "8"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
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    },
    {
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        "mya.shape"
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            "text/plain": [
              "(5,)"
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          },
          "metadata": {},
          "execution_count": 18
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mya.size"
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              "5"
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          },
          "metadata": {},
          "execution_count": 19
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