A_crash_course_on_Numpy_3_Numpy_Operations.ipynb

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  "metadata": {
    "colab": {
      "name": "A crash course on Numpy-3-Numpy Operations.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyPikYPsRU4VesuhW3jfdgBr",
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    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Adeelzafar/Adeelzafar/blob/main/A_crash_course_on_Numpy_3_Numpy_Operations.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2XPA5tK0euPN"
      },
      "source": [
        "# In this notebook, we will see different numpy operations"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BALTqkMsgluS"
      },
      "source": [
        "import numpy as np"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QZdVtjpqgnGg",
        "outputId": "50c51824-fa20-448c-8c9f-f93a7883595e"
      },
      "source": [
        "# Lets create a numpy array \n",
        "array = np.arange(0,10)\n",
        "array"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Pi-OMAazgwzM",
        "outputId": "f3847ed0-f451-4ea0-c09d-4eba4be888cd"
      },
      "source": [
        "# Performing airthemtic operations on array\n",
        "array + 5\n",
        " "
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 5,  6,  7,  8,  9, 10, 11, 12, 13, 14])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "svcvtDtvg7c8",
        "outputId": "c279931f-4055-4f81-ac60-906f001a4523"
      },
      "source": [
        "array - 2"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([-2, -1,  0,  1,  2,  3,  4,  5,  6,  7])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "olp7ENZOhCR9",
        "outputId": "c9e1f01d-a0a2-4c46-d08a-929305897131"
      },
      "source": [
        "array * 6"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 0,  6, 12, 18, 24, 30, 36, 42, 48, 54])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GcvXfKWghDjk",
        "outputId": "f950b2fb-d866-4c28-d45a-02a827a3b930"
      },
      "source": [
        "array + array "
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 0,  2,  4,  6,  8, 10, 12, 14, 16, 18])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_HY62XYrhHi6",
        "outputId": "db1db0fc-3e2f-4024-a0a3-b66743efd9e7"
      },
      "source": [
        "# Numpy comes with some basic mathematical functions as well\n",
        "\n",
        "np.sqrt(array)"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0.        , 1.        , 1.41421356, 1.73205081, 2.        ,\n",
              "       2.23606798, 2.44948974, 2.64575131, 2.82842712, 3.        ])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mMZW1l5kh0sJ",
        "outputId": "ad994b98-abc9-4e78-d5cf-e32c29d4087a"
      },
      "source": [
        "np.square(array)"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 0,  1,  4,  9, 16, 25, 36, 49, 64, 81])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AgMU2mV5h5P0",
        "outputId": "91f8b174-c7dd-4f78-e3b2-406c1b3c57ba"
      },
      "source": [
        "np.sin(array)"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 0.        ,  0.84147098,  0.90929743,  0.14112001, -0.7568025 ,\n",
              "       -0.95892427, -0.2794155 ,  0.6569866 ,  0.98935825,  0.41211849])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9aPIZq7TiAFh",
        "outputId": "4c920828-21cf-47e5-eab6-62b1c3302a05"
      },
      "source": [
        "np.log(array)"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: RuntimeWarning: divide by zero encountered in log\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([      -inf, 0.        , 0.69314718, 1.09861229, 1.38629436,\n",
              "       1.60943791, 1.79175947, 1.94591015, 2.07944154, 2.19722458])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FHAQ6eoRiDGQ",
        "outputId": "a1cb27ef-5afb-4d50-f1ff-061877641762"
      },
      "source": [
        "# Numpy also supports some statistical operations\n",
        "array.sum()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "45"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9C25taVyiT9e",
        "outputId": "2a2103bf-4b83-49e1-943e-273725992e99"
      },
      "source": [
        "array.mean()"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "4.5"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
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        },
        "id": "eUpA_rNgiVFQ",
        "outputId": "6305251e-1612-4650-f233-54f730614c8f"
      },
      "source": [
        "array.max()"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "9"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gt1kbovHiWVN",
        "outputId": "8faf5003-aa22-4a15-87b4-405a0b322e30"
      },
      "source": [
        "array.min()"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_6JF32dAiZ_7",
        "outputId": "e5603646-5d4a-4700-fc64-b3c8a0d3d5d2"
      },
      "source": [
        "array.std()"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2.8722813232690143"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "njAQdWu0iilv",
        "outputId": "b761f763-fed3-4439-8183-f10079b86635"
      },
      "source": [
        "# Lets now create a 2D array \n",
        "array2d = np.arange(1,26).reshape(5,5)\n",
        "print(array2d)"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[[ 1  2  3  4  5]\n",
            " [ 6  7  8  9 10]\n",
            " [11 12 13 14 15]\n",
            " [16 17 18 19 20]\n",
            " [21 22 23 24 25]]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "koUEi0e2ivwg",
        "outputId": "17293cd8-f7fb-4295-eb6c-27e4f7f4aa10"
      },
      "source": [
        "array2d.shape"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(5, 5)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "o3U_5Q4Gi-YC",
        "outputId": "79488f47-918b-4412-b4ee-adef3eb14f64"
      },
      "source": [
        "#Peforming sum across the rows, The below command gives the each row of first column\n",
        "array2d.sum(axis=0)"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([55, 60, 65, 70, 75])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TGhYqk6BjTFo",
        "outputId": "a9904e12-d983-4da7-8c23-d1d0b1386a70"
      },
      "source": [
        "#Peforming sum across the columns\n",
        "array2d.sum(axis=1)"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 15,  40,  65,  90, 115])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    }
  ]
}