Copy_of_Untitled1.ipynb

{
  "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": null,
      "metadata": {
        "id": "40XHsVi29SEQ"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Import the dataset from Nvidia.\n",
        "Stock_Nvidia = pd.read_csv('Stock_Nvidia.csv')\n",
        "print(Stock_Nvidia.head(25))"
      ],
      "metadata": {
        "id": "ngd05Rk2DdVB",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "fe3df303-324e-433a-b2ca-54e46158488c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "          Date    Open    High     Low   Close       Volume\n",
            "0   10/18/2024  138.67  138.90  137.28  138.00  176,090,203\n",
            "1   10/17/2024  139.34  140.89  136.87  136.93  306,435,906\n",
            "2   10/16/2024  133.98  136.62  131.58  135.72  264,879,688\n",
            "3   10/15/2024  137.87  138.57  128.74  131.60  377,831,000\n",
            "4   10/14/2024  136.47  139.60  136.30  138.07  232,347,703\n",
            "5   10/11/2024  134.01  135.78  133.66  134.80  170,209,500\n",
            "6   10/10/2024  131.91  135.00  131.00  134.81  242,311,297\n",
            "7   10/09/2024  134.11  134.52  131.38  132.65  246,191,594\n",
            "8   10/08/2024  130.26  133.48  129.42  132.89  285,722,500\n",
            "9   10/07/2024  124.99  130.64  124.95  127.72  346,250,219\n",
            "10  10/04/2024  124.94  125.04  121.83  124.92  244,465,594\n",
            "11  10/04/2024  124.94  125.04  121.83  124.92  244,465,594\n",
            "12  10/03/2024  120.92  124.36  120.34  122.85  277,118,031\n",
            "13  10/03/2024  120.92  124.36  120.34  122.85  277,118,031\n",
            "14  10/02/2024  116.44  119.38  115.14  118.85  221,845,906\n",
            "15  10/01/2024  121.77  122.44  115.79  117.00  302,094,500\n",
            "16  09/30/2024  118.31  121.50  118.15  121.44  227,053,703\n",
            "17  09/27/2024  123.97  124.03  119.26  121.40  271,009,219\n",
            "18  09/26/2024  126.80  127.67  121.80  124.04  302,582,906\n",
            "19  09/25/2024  122.02  124.94  121.61  123.51  284,692,906\n",
            "20  09/24/2024  116.52  121.80  115.38  120.87  354,966,781\n",
            "21  09/23/2024  116.55  116.99  114.86  116.26  206,228,500\n",
            "22  09/20/2024  117.06  118.62  115.39  116.00  382,462,406\n",
            "23  09/19/2024  117.35  119.66  117.25  117.87  293,506,406\n",
            "24  09/18/2024  115.89  117.70  113.22  113.37  310,318,906\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# The rows 10 to 13 are duplications in the dataset. I will remove them.\n",
        "Stock_Nvidia = Stock_Nvidia.drop_duplicates()\n",
        "print(Stock_Nvidia.head(25))\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "X7JsZS9fHzsm",
        "outputId": "a6324869-103d-481e-bab2-207dc0f45039"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "          Date    Open    High     Low   Close       Volume\n",
            "0   10/18/2024  138.67  138.90  137.28  138.00  176,090,203\n",
            "1   10/17/2024  139.34  140.89  136.87  136.93  306,435,906\n",
            "2   10/16/2024  133.98  136.62  131.58  135.72  264,879,688\n",
            "3   10/15/2024  137.87  138.57  128.74  131.60  377,831,000\n",
            "4   10/14/2024  136.47  139.60  136.30  138.07  232,347,703\n",
            "5   10/11/2024  134.01  135.78  133.66  134.80  170,209,500\n",
            "6   10/10/2024  131.91  135.00  131.00  134.81  242,311,297\n",
            "7   10/09/2024  134.11  134.52  131.38  132.65  246,191,594\n",
            "8   10/08/2024  130.26  133.48  129.42  132.89  285,722,500\n",
            "9   10/07/2024  124.99  130.64  124.95  127.72  346,250,219\n",
            "10  10/04/2024  124.94  125.04  121.83  124.92  244,465,594\n",
            "12  10/03/2024  120.92  124.36  120.34  122.85  277,118,031\n",
            "14  10/02/2024  116.44  119.38  115.14  118.85  221,845,906\n",
            "15  10/01/2024  121.77  122.44  115.79  117.00  302,094,500\n",
            "16  09/30/2024  118.31  121.50  118.15  121.44  227,053,703\n",
            "17  09/27/2024  123.97  124.03  119.26  121.40  271,009,219\n",
            "18  09/26/2024  126.80  127.67  121.80  124.04  302,582,906\n",
            "19  09/25/2024  122.02  124.94  121.61  123.51  284,692,906\n",
            "20  09/24/2024  116.52  121.80  115.38  120.87  354,966,781\n",
            "21  09/23/2024  116.55  116.99  114.86  116.26  206,228,500\n",
            "22  09/20/2024  117.06  118.62  115.39  116.00  382,462,406\n",
            "23  09/19/2024  117.35  119.66  117.25  117.87  293,506,406\n",
            "24  09/18/2024  115.89  117.70  113.22  113.37  310,318,906\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# I will rename the columns.\n",
        "Stock_Nvidia = Stock_Nvidia.rename({'Date':'Date_September_October', 'Volume':'Total Price of the Stock'}, axis=1)\n",
        "print(Stock_Nvidia.head(25))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ezdMQBB8Kjs-",
        "outputId": "cb6da407-6a69-4dee-efb3-4b9f483c7b78"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "   Date_September_October    Open    High     Low   Close  \\\n",
            "0              10/18/2024  138.67  138.90  137.28  138.00   \n",
            "1              10/17/2024  139.34  140.89  136.87  136.93   \n",
            "2              10/16/2024  133.98  136.62  131.58  135.72   \n",
            "3              10/15/2024  137.87  138.57  128.74  131.60   \n",
            "4              10/14/2024  136.47  139.60  136.30  138.07   \n",
            "5              10/11/2024  134.01  135.78  133.66  134.80   \n",
            "6              10/10/2024  131.91  135.00  131.00  134.81   \n",
            "7              10/09/2024  134.11  134.52  131.38  132.65   \n",
            "8              10/08/2024  130.26  133.48  129.42  132.89   \n",
            "9              10/07/2024  124.99  130.64  124.95  127.72   \n",
            "10             10/04/2024  124.94  125.04  121.83  124.92   \n",
            "12             10/03/2024  120.92  124.36  120.34  122.85   \n",
            "14             10/02/2024  116.44  119.38  115.14  118.85   \n",
            "15             10/01/2024  121.77  122.44  115.79  117.00   \n",
            "16             09/30/2024  118.31  121.50  118.15  121.44   \n",
            "17             09/27/2024  123.97  124.03  119.26  121.40   \n",
            "18             09/26/2024  126.80  127.67  121.80  124.04   \n",
            "19             09/25/2024  122.02  124.94  121.61  123.51   \n",
            "20             09/24/2024  116.52  121.80  115.38  120.87   \n",
            "21             09/23/2024  116.55  116.99  114.86  116.26   \n",
            "22             09/20/2024  117.06  118.62  115.39  116.00   \n",
            "23             09/19/2024  117.35  119.66  117.25  117.87   \n",
            "24             09/18/2024  115.89  117.70  113.22  113.37   \n",
            "\n",
            "   Total Price of the Stock  \n",
            "0               176,090,203  \n",
            "1               306,435,906  \n",
            "2               264,879,688  \n",
            "3               377,831,000  \n",
            "4               232,347,703  \n",
            "5               170,209,500  \n",
            "6               242,311,297  \n",
            "7               246,191,594  \n",
            "8               285,722,500  \n",
            "9               346,250,219  \n",
            "10              244,465,594  \n",
            "12              277,118,031  \n",
            "14              221,845,906  \n",
            "15              302,094,500  \n",
            "16              227,053,703  \n",
            "17              271,009,219  \n",
            "18              302,582,906  \n",
            "19              284,692,906  \n",
            "20              354,966,781  \n",
            "21              206,228,500  \n",
            "22              382,462,406  \n",
            "23              293,506,406  \n",
            "24              310,318,906  \n"
          ]
        }
      ]
    }
  ]
}