Jiya_Agarwal_01_Numpy_Exercise.ipynb

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        "<a href=\"https://colab.research.google.com/github/Jiya918/WordForThought/blob/main/Jiya_Agarwal_01_Numpy_Exercise.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    {
      "cell_type": "markdown",
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      "source": [
        "# NumPy Exercises\n",
        "\n",
        "Now that we've learned about NumPy let's test your knowledge. We'll start off with a few simple tasks, and then you'll be asked some more complicated questions."
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np"
      ],
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      "source": [
        "#### Import NumPy as np"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np"
      ],
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        "id": "MNgxifN5x-Am"
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      "outputs": []
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    {
      "cell_type": "code",
      "execution_count": null,
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      "outputs": [],
      "source": [
        "import numpy as np"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ehlpKUPc9xlM"
      },
      "source": [
        "#### Create an array of 10 zeros"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "arr = np.array([0,0,0,0,0,0,0,0,0])"
      ],
      "metadata": {
        "id": "9bfGvkO7yEtC"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "aEQkK-Dw9xlN"
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      "outputs": [],
      "source": [
        "arr = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6QHp05Ei9xlN"
      },
      "source": [
        "#### Create an array of 10 ones"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "scrolled": true,
        "id": "ebe9xrC29xlN"
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      "outputs": [],
      "source": [
        "array = np.ones(10)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ziS-l3xp9xlO"
      },
      "source": [
        "#### Create an array of 10 fives"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "fFC7bqLM9xlO"
      },
      "outputs": [],
      "source": [
        "array = np.ones(10)*5"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kBugMXlC9xlO"
      },
      "source": [
        "#### Create an array of the integers from 10 to 50"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "JsO6qS9R9xlO"
      },
      "outputs": [],
      "source": [
        "array = np.arange(10.51)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "g__F0rB39xlP"
      },
      "source": [
        "#### Create a 3x3 matrix with values ranging from 0 to 8"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "MmVXCn0K9xlP"
      },
      "outputs": [],
      "source": [
        "array = np.arange(0,9).reshape(3,3)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4YfT0aLo9xlP"
      },
      "source": [
        "#### Create a 3x3 identity matrix"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "UHa42UpQ9xlP"
      },
      "outputs": [],
      "source": [
        "array = np.eye(3)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bfwDbjhI9xlP"
      },
      "source": [
        "#### Use NumPy to generate a random number between 0 and 1"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Z0OroZxW9xlP"
      },
      "outputs": [],
      "source": [
        "array = np.random.rand(1)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rLW0Jjzp9xlP"
      },
      "source": [
        "#### Use NumPy to generate an array of 25 random numbers sampled from a standard normal distribution"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "szluy14n9xlP"
      },
      "outputs": [],
      "source": [
        "array = np.random.randn(25)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_GhI8LYn9xlP"
      },
      "source": [
        "#### Create the following matrix:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "wS1ZBddV9xlP"
      },
      "outputs": [],
      "source": [
        "array = np.arange(1,101).reshape(10,10)/100\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3OqA-QtL9xlQ"
      },
      "source": [
        "#### Create an array of 20 linearly spaced points between 0 and 1:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "FNXTugQ29xlQ"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "elx0EaxE9xlQ"
      },
      "source": [
        "## Numpy Indexing and Selection\n",
        "\n",
        "Now you will be given a few matrices, and be asked to replicate the resulting matrix outputs:"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2Tbm9kVf9xlQ"
      },
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Ft8P8e249xlQ"
      },
      "outputs": [],
      "source": [
        "array = np.arange(1,26).reshape(5,5)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "rnUSntEa9xlQ"
      },
      "outputs": [],
      "source": [
        "array = np.arange(20,26)\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "3DMBC_wp9xlQ"
      },
      "outputs": [],
      "source": [
        "array = np.arange(2,13,5).reshape(3,1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "pGjD4HUK9xlQ"
      },
      "outputs": [],
      "source": [
        "array = np.arange(21,26).reshape(1,5)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "dqsdpxUo9xlR"
      },
      "outputs": [],
      "source": [
        "array = np.arange(16,26).reshape(2,5)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "collapsed": true,
        "id": "6vtHuVJU9xlf"
      },
      "source": [
        "# Great Job!"
      ]
    }
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