Assignment.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# **Does the Marketshare of Nvidia hardware relate to the stock price of the Nvidia Corporation?**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By Izaan Syed, 100922342\n",
    "\n",
    "---\n",
    "**Introduction:**\n",
    "-\n",
    "\n",
    "In recent times, Nvidia stock prices have been in the news for skyrocketing massively, being up ~2500% in the last five years. Nvidia is widely recognized by consumers as a gaming-focused company produce of graphics processing units (GPUs), which facilitate video game rendering on desktops and notebooks with their Geforce Graphics product line. Nvidia is also a major player in the industrial sector, being involved in high-performance computing, autonomous vehicles, data centers, and, most notably, artificial intelligence. Nvidia-developed hardware powers both the [Las Vegas Sphere](https://blogs.nvidia.com/blog/sphere-las-vegas/) and most notably the large language AI model known as [ChatGPT.](https://developer.nvidia.com/blog/new-video-what-runs-chatgpt/)\n",
    "\n",
    "\n",
    "\n",
    "As Nvidia's stock price has skyrocketed massively, and Nvidia's most consumer-direct business sector is selling discrete graphics cards, I though it would be interesting to analyze if Nvidia's consumer GPU marketshare can be linked to Nvidia Corporation's stock prices increasing in value.\n",
    "\n",
    "The time period observed will be November 2019, to September 2024. This time period includes many new releases of hardware, including Nvidia's 20 series launch, 16 series launch, 30 series launch, 40 series launch, and rival AMDs' launches of the 5XXX series, 6XXX series, and 7XXX series. The selected time period also includes notable events such as the cryptocurrency boom of 2021 and the release of OpenAI's ChatGPT in 2022.\n",
    "\n",
    "The stock market data data was collected from [Marketwatch](https://www.marketwatch.com/investing/stock/nvda), and the GPU marketshare data was collected by [Valve's Steam hardware survery](https://github.com/jdegene/steamHWsurvey)\n",
    "\n",
    "Unfortunately, the Steam hardware survey does not report total participants, rather only percentages. This means that the comparison will have to be made between marketshare dominance (compared to Intel and AMD) and stock prices, rather than just GPU units compared to stock price.\n",
    "\n",
    "\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import Statements;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd # Libary used to organize date into 'dataframes', allowing for easier manipulation and presentation\n",
    "import matplotlib.pyplot as plt # Library used to generate graphic plots to visually represent data\n",
    "import numpy as np # Library focused on arithmetics, used to generate line of best fit, "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "Cleaning of SHS survery for data on Nvidia Marketshare;\n",
    "\n",
    "(Due to a website limitation, all data was not available in a single CSV file - instead the data is split into 5 files which will be combined in the cleaning process.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          Date  Marketshare Percentage\n",
      "0   2019-11-01                   69.19\n",
      "1   2019-12-01                   69.35\n",
      "2   2020-01-01                   69.21\n",
      "3   2020-02-01                   68.61\n",
      "4   2020-03-01                   68.04\n",
      "5   2020-04-01                   66.80\n",
      "6   2020-05-01                   66.21\n",
      "7   2020-06-01                   67.44\n",
      "8   2020-07-01                   67.85\n",
      "9   2020-08-01                   67.86\n",
      "10  2020-09-01                   67.76\n",
      "11  2020-10-01                   67.66\n",
      "12  2020-11-01                   68.22\n",
      "13  2020-12-01                   72.19\n",
      "14  2021-01-01                   68.56\n",
      "15  2021-02-01                   69.14\n",
      "16  2021-03-01                   69.61\n",
      "17  2021-04-01                   70.09\n",
      "18  2021-05-01                   69.65\n",
      "19  2021-06-01                   70.60\n",
      "20  2021-07-01                   69.16\n",
      "21  2021-08-01                   71.42\n",
      "22  2021-09-01                   70.33\n",
      "23  2021-10-01                   69.52\n",
      "24  2021-11-01                   69.88\n",
      "25  2021-12-01                   70.64\n",
      "26  2022-01-01                   69.73\n",
      "27  2022-02-01                   70.67\n",
      "28  2022-03-01                   71.68\n",
      "29  2022-04-01                   70.73\n",
      "30  2022-05-01                   72.14\n",
      "31  2022-06-01                   70.62\n",
      "32  2022-07-01                   73.95\n",
      "33  2022-08-01                   70.85\n",
      "34  2022-09-01                   72.18\n",
      "35  2022-10-01                   73.57\n",
      "36  2022-11-01                   70.57\n",
      "37  2022-12-01                   70.31\n",
      "38  2023-01-01                   69.36\n",
      "39  2023-02-01                   71.05\n",
      "40  2023-03-01                   80.30\n",
      "41  2023-04-01                   71.00\n",
      "42  2023-05-01                   71.04\n",
      "43  2023-06-01                   70.78\n",
      "44  2023-07-01                   68.82\n",
      "45  2023-08-01                   70.29\n",
      "46  2023-09-01                   72.37\n",
      "47  2023-10-01                   76.99\n",
      "48  2023-11-01                   70.15\n",
      "49  2023-12-01                   68.97\n",
      "50  2024-01-01                   69.58\n",
      "51  2024-02-01                   72.26\n",
      "52  2024-03-01                   72.46\n",
      "53  2024-04-01                   72.08\n",
      "54  2024-05-01                   76.08\n",
      "55  2024-06-01                   71.72\n",
      "56  2024-07-01                   71.62\n",
      "57  2024-08-01                   72.15\n",
      "58  2024-09-01                   73.36\n"
     ]
    }
   ],
   "source": [
    "shs = pd.read_csv('shs.csv')\n",
    "\n",
    "# Delete rows previous to the index of the row of 2019-11-01 (starting index)\n",
    "idx = shs[shs['date'] == '2019-11-01'].index[0]\n",
    "shs = shs.loc[idx:]\n",
    "\n",
    "# Include only columns that have 'Video Card Description' in the category row\n",
    "shs = shs[shs['category'].str.contains('Video Card Description')]\n",
    "\n",
    "# Include only columns that have 'NVIDIA' in the description row\n",
    "shs = shs[shs['name'].str.contains('NVIDIA', na=False, case=False)]\n",
    "\n",
    "# Delete october 2024 as it is outside of analysis range\n",
    "shs = shs[shs['date'] != '2024-10-01']\n",
    "\n",
    "# Calculate the total NVIDIA market share for each month\n",
    "# Convert the 'date' column to datetime for grouping\n",
    "shs['date'] = pd.to_datetime(shs['date'])\n",
    "\n",
    "# Group by year and month, and sum up the percentages. Line generated by copilot\n",
    "nvidia_marketshare = shs.groupby(shs['date'].dt.to_period('M'))['percentage'].sum().reset_index()\n",
    "\n",
    "# Convert period to a string representation for easier handling\n",
    "nvidia_marketshare['date'] = nvidia_marketshare['date'].astype(str)\n",
    "\n",
    "# add day to YYYY-MM (new format YYYY-MM-DD)\n",
    "nvidia_marketshare['date'] = nvidia_marketshare['date'] + '-01'\n",
    "\n",
    "# Change 'date' to 'Date' and 'percentage' to 'Marketshare Percentage', to clean up presentation\n",
    "nvidia_marketshare.columns = ['Date', 'Marketshare Percentage']\n",
    "\n",
    "# Multiply stock value by 100 to convert decimal marketshare value to percentage\n",
    "nvidia_marketshare['Marketshare Percentage'] = nvidia_marketshare['Marketshare Percentage'] * 100\n",
    "\n",
    "# Print the resulting marketshare DataFrame\n",
    "print(nvidia_marketshare)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "Cleaning of Nvidia Stock market data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         Date  Stock Price\n",
      "12 2019-11-01         5.24\n",
      "11 2019-12-01         5.41\n",
      "10 2020-01-01         5.97\n",
      "9  2020-02-01         5.89\n",
      "8  2020-03-01         6.92\n",
      "7  2020-04-01         6.39\n",
      "6  2020-05-01         7.11\n",
      "5  2020-06-01         8.83\n",
      "4  2020-07-01         9.52\n",
      "3  2020-08-01        10.73\n",
      "2  2020-09-01        13.48\n",
      "1  2020-10-01        13.76\n",
      "0  2020-11-01        12.66\n",
      "11 2020-12-01        13.49\n",
      "10 2021-01-01        13.10\n",
      "9  2021-02-01        13.05\n",
      "8  2021-03-01        13.88\n",
      "7  2021-04-01        13.57\n",
      "6  2021-05-01        15.13\n",
      "5  2021-06-01        16.27\n",
      "4  2021-07-01        20.13\n",
      "3  2021-08-01        19.70\n",
      "2  2021-09-01        22.49\n",
      "1  2021-10-01        20.75\n",
      "0  2021-11-01        25.65\n",
      "11 2021-12-01        33.22\n",
      "10 2022-01-01        29.82\n",
      "9  2022-02-01        25.10\n",
      "8  2022-03-01        24.29\n",
      "7  2022-04-01        27.38\n",
      "6  2022-05-01        18.54\n",
      "5  2022-06-01        18.72\n",
      "4  2022-07-01        14.90\n",
      "3  2022-08-01        18.18\n",
      "2  2022-09-01        14.21\n",
      "1  2022-10-01        12.35\n",
      "0  2022-11-01        13.81\n",
      "11 2022-12-01        17.00\n",
      "10 2023-01-01        14.85\n",
      "9  2023-02-01        19.69\n",
      "8  2023-03-01        23.19\n",
      "7  2023-04-01        27.51\n",
      "6  2023-05-01        27.84\n",
      "5  2023-06-01        38.49\n",
      "4  2023-07-01        42.52\n",
      "3  2023-08-01        46.46\n",
      "2  2023-09-01        49.76\n",
      "1  2023-10-01        44.03\n",
      "0  2023-11-01        40.88\n",
      "9  2023-12-01        46.53\n",
      "8  2024-01-01        49.24\n",
      "7  2024-02-01        62.10\n",
      "6  2024-03-01        80.00\n",
      "5  2024-04-01        90.30\n",
      "4  2024-05-01        85.08\n",
      "3  2024-06-01       113.62\n",
      "2  2024-07-01       123.47\n",
      "1  2024-08-01       117.53\n",
      "0  2024-09-01       116.01\n"
     ]
    }
   ],
   "source": [
    "# Combine NVDA1, NVDA2, NVDA3, NVDA4, NVDA5 csv files into a single dataframe\n",
    "nvda1 = pd.read_csv('NVDA1.csv')\n",
    "nvda2 = pd.read_csv('NVDA2.csv')\n",
    "nvda3 = pd.read_csv('NVDA3.csv')\n",
    "nvda4 = pd.read_csv('NVDA4.csv')\n",
    "nvda5 = pd.read_csv('NVDA5.csv')\n",
    "nvda = pd.concat([nvda1, nvda2, nvda3, nvda4, nvda5])\n",
    "\n",
    "# Remove high, low, close, volume rows. Only open is relevant because it matches the most closely to the SHS measurement dates\n",
    "nvda = nvda[['Date', 'Open']]\n",
    "\n",
    "# Rename 'Open' to 'Stock Price', as we will use market open price as the definitive stock price.\n",
    "nvda = nvda.rename(columns={'Open': 'Stock Price'})\n",
    "\n",
    "# Add /01 to date (MM/YYYY to MM/DD/YYYY)\n",
    "nvda['Date'] = nvda['Date'].apply(lambda x: f\"{x.split('/')[0]}/01/{x.split('/')[1]}\") # Line generated by ChatGPT\n",
    "\n",
    "# Move year first (MM/DD/YYYY to YYYY/MM/DD)\n",
    "nvda['Date'] = pd.to_datetime(nvda['Date'])\n",
    "\n",
    "# Sort in ascending order\n",
    "nvda = nvda.sort_values(by='Date')\n",
    "\n",
    "print(nvda)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "Combining both Dataframes for stock price and marketshare into a single Dataframe for graph creation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         Date  Stock Price  Marketshare Percentage\n",
      "0  2019-11-01         5.24                   69.19\n",
      "1  2019-12-01         5.41                   69.35\n",
      "2  2020-01-01         5.97                   69.21\n",
      "3  2020-02-01         5.89                   68.61\n",
      "4  2020-03-01         6.92                   68.04\n",
      "5  2020-04-01         6.39                   66.80\n",
      "6  2020-05-01         7.11                   66.21\n",
      "7  2020-06-01         8.83                   67.44\n",
      "8  2020-07-01         9.52                   67.85\n",
      "9  2020-08-01        10.73                   67.86\n",
      "10 2020-09-01        13.48                   67.76\n",
      "11 2020-10-01        13.76                   67.66\n",
      "12 2020-11-01        12.66                   68.22\n",
      "13 2020-12-01        13.49                   72.19\n",
      "14 2021-01-01        13.10                   68.56\n",
      "15 2021-02-01        13.05                   69.14\n",
      "16 2021-03-01        13.88                   69.61\n",
      "17 2021-04-01        13.57                   70.09\n",
      "18 2021-05-01        15.13                   69.65\n",
      "19 2021-06-01        16.27                   70.60\n",
      "20 2021-07-01        20.13                   69.16\n",
      "21 2021-08-01        19.70                   71.42\n",
      "22 2021-09-01        22.49                   70.33\n",
      "23 2021-10-01        20.75                   69.52\n",
      "24 2021-11-01        25.65                   69.88\n",
      "25 2021-12-01        33.22                   70.64\n",
      "26 2022-01-01        29.82                   69.73\n",
      "27 2022-02-01        25.10                   70.67\n",
      "28 2022-03-01        24.29                   71.68\n",
      "29 2022-04-01        27.38                   70.73\n",
      "30 2022-05-01        18.54                   72.14\n",
      "31 2022-06-01        18.72                   70.62\n",
      "32 2022-07-01        14.90                   73.95\n",
      "33 2022-08-01        18.18                   70.85\n",
      "34 2022-09-01        14.21                   72.18\n",
      "35 2022-10-01        12.35                   73.57\n",
      "36 2022-11-01        13.81                   70.57\n",
      "37 2022-12-01        17.00                   70.31\n",
      "38 2023-01-01        14.85                   69.36\n",
      "39 2023-02-01        19.69                   71.05\n",
      "40 2023-03-01        23.19                   80.30\n",
      "41 2023-04-01        27.51                   71.00\n",
      "42 2023-05-01        27.84                   71.04\n",
      "43 2023-06-01        38.49                   70.78\n",
      "44 2023-07-01        42.52                   68.82\n",
      "45 2023-08-01        46.46                   70.29\n",
      "46 2023-09-01        49.76                   72.37\n",
      "47 2023-10-01        44.03                   76.99\n",
      "48 2023-11-01        40.88                   70.15\n",
      "49 2023-12-01        46.53                   68.97\n",
      "50 2024-01-01        49.24                   69.58\n",
      "51 2024-02-01        62.10                   72.26\n",
      "52 2024-03-01        80.00                   72.46\n",
      "53 2024-04-01        90.30                   72.08\n",
      "54 2024-05-01        85.08                   76.08\n",
      "55 2024-06-01       113.62                   71.72\n",
      "56 2024-07-01       123.47                   71.62\n",
      "57 2024-08-01       117.53                   72.15\n",
      "58 2024-09-01       116.01                   73.36\n"
     ]
    }
   ],
   "source": [
    "# Ensure consistency in date\n",
    "nvda['Date'] = pd.to_datetime(nvda['Date']) \n",
    "nvidia_marketshare['Date'] = pd.to_datetime(nvidia_marketshare['Date']) \n",
    "\n",
    "# Merge the two DataFrames on the 'Date' column\n",
    "nvidia_analysis = pd.merge(nvda, nvidia_marketshare, on='Date', how='outer')\n",
    "\n",
    "# Sort by date after merging to maintain chronological order\n",
    "nvidia_analysis = nvidia_analysis.sort_values(by='Date')\n",
    "\n",
    "# Print the resulting combined DataFrame\n",
    "print(nvidia_analysis)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "Graph plotting NVDA stock prices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(nvidia_analysis['Date'], nvidia_analysis['Stock Price'], label='NVDA Stock Price', color='tab:green') # Creates the plot\n",
    "plt.xlabel('Date')  # Labels X axis\n",
    "plt.ylabel('Stock Price') # Labels Y axis\n",
    "plt.title('NVDA Stock Price Over Time')  # Labels graph\n",
    "\n",
    "#Line of best fit was omitted due to clear trend of data\n",
    "\n",
    "plt.show() # Displays graph"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "Graph plotting marketshare of Nvidia hardware"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Convert 'Date' to numerical values for regression\n",
    "nvidia_analysis['Date_numeric'] = nvidia_analysis['Date'].map(lambda x: x.toordinal())\n",
    "\n",
    "# Perform linear regression to get slope and intercept \n",
    "slope, intercept = np.polyfit(\n",
    "    nvidia_analysis['Date_numeric'],\n",
    "    nvidia_analysis['Marketshare Percentage'],\n",
    "    1\n",
    ")\n",
    "\n",
    "# Generate line of best fit\n",
    "line_of_best_fit = slope * nvidia_analysis['Date_numeric'] + intercept\n",
    "\n",
    "# Plot the data\n",
    "plt.plot(nvidia_analysis['Date'], nvidia_analysis['Marketshare Percentage'], label='NVIDIA Marketshare', color='tab:blue')\n",
    "plt.plot(nvidia_analysis['Date'], line_of_best_fit, label='Line of Best Fit', color='tab:orange', linestyle='--') # Adds line of best fit\n",
    "plt.xlabel('Date') # Labels X axis\n",
    "plt.ylabel('Percentage of Marketshare') # Labels y axis\n",
    "plt.ylim(50, 100) # Sets scale from 50-100 for marketshare percentage\n",
    "plt.legend() # Adds a legend to the plot\n",
    "\n",
    "plt.show() # Displays graph\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "Combined graph of marketshare and stock price;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x189d0090290>]"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax1 = plt.subplots() # Create the initial plot with the first y-axis\n",
    "\n",
    "# Add stock prices\n",
    "color = 'tab:green'\n",
    "ax1.set_xlabel('Date')\n",
    "ax1.set_ylabel('Stock Price', color=color)\n",
    "ax1.plot(nvidia_analysis['Date'], nvidia_analysis['Stock Price'], color=color)\n",
    "ax1.tick_params(axis='y', labelcolor=color)\n",
    "\n",
    "# Add marketshare percentage to the initial plot\n",
    "ax1 = ax1.twinx()\n",
    "color = 'tab:blue'\n",
    "ax1.set_ylabel('Marketshare Percentage', color=color)\n",
    "ax1.set_ylim(50, 100)\n",
    "ax1.plot(nvidia_analysis['Date'], nvidia_analysis['Marketshare Percentage'], color=color)\n",
    "\n",
    "# Line of best fit omitted to prevent confusion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "**Discussion:**\n",
    "-\n",
    "\n",
    "Overall, the marketshare for Nvidia GPU's based on the steam hardware survey appears to be mostly consistent, staying between 65% and 80% for 4 years. This is expected as AMD, their main competitor for consumer GPU's, has remained at the same level of competitiveness in the market within the timespan graphed. There has been a plethora of hardware releaess by both companies in this timeframe.\n",
    "\n",
    "The stock prices for Nvidia however have skyrocketed in recent times. There was a small bump near 2022, attributed to the cryptocurrency mining boom of 2022. There was a huge skyrocket in 2024, occuring in the same timeframe as the deep learning AI boom, which is largely powered by Nvidia's CUDA technology and datacenter hardware. \n",
    "\n",
    "When plotting Nvidia Stock price against their consumer marketshare, it is shown that there is little correlation between stock price and their marketshare, despite their stock pricing shooting high disproportionately compared to their competitors in the market. The bumps in the stock prices in 2022 and 2024 and not reflected as an increase in consumer marketshare. \n",
    "\n",
    "This lack of correlation  suggests that Nvidia's growth and valuation are driven primarily by its dominance in industrial sectors, including high-performance computing, autonomous vehicles, data centers, and, most notably, artificial intelligence. \n",
    "\n",
    "In conclusion, while Nvidia's largest visible presence may be in consumer GPUs, its most significant and recent financial success can instead be attributed to their commercial and industrial applications.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "**References:**\n",
    "-\n",
    "\n",
    "https://www.marketwatch.com/investing/stock/nvda\n",
    "\n",
    "https://github.com/jdegene/steamHWsurvey"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.4"
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 },
 "nbformat": 4,
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}