project_final_submission_template.ipynb

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   "cell_type": "markdown",
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   "source": [
    "# Project Final Submission Template"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You must sign up for a canvas Project Group on the People page even if you're working alone.\n",
    "\n",
    "Student 1: Darian Tham\n",
    "\n",
    "Student 2:\n",
    "    \n",
    "Canvas Project Group Number: 323"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 1a: Planning \n",
    "#### Identify the information in the file your program will read\n",
    "\n",
    "Double click this cell to edit.\n",
    "\n",
    "Describe (all) the information that is available. Be sure to note any surprising or unusual features. (For example, some information sources have missing data, which may be blank or flagged using values like -99, NaN, or something else.)\n",
    "\n",
    "Information in the video game file:\n",
    " - Certain video games sold globally\n",
    " - For each video game, its rank (in terms of highest global sales), name, platform, year, genre, publisher, NA (North American) sales, EU (European Union) sales, JP (Japan) sales, other sales, and global sales\n",
    " \n",
    "Notes:\n",
    " - For some video games, the year is not available (N/A) (this information is not accessed in the function)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 1b: Planning \n",
    "#### Brainstorm ideas for what your program will produce\n",
    "#### Select the idea you will build on for subsequent steps\n",
    "\n",
    "Double click this cell to edit.\n",
    "\n",
    "You must brainstorm at least three ideas for graphs or charts that your program could produce and choose the one that you'd like to work on. You can choose between a line chart, histogram, bar chart, scatterplot, or pie chart.\n",
    "\n",
    "Possible program outputs\n",
    "- Average number of games per publisher (bar graph)\n",
    "- Sum of total number of games released each year (line graph)\n",
    "- Average profit (in millions) per game for each publisher inputed (a total of any 5 publishers within the csv file)(bar graph)\n",
    "\n",
    "Selected idea: Average profit (in millions) per game for each publisher\n",
    "- I am doing a bar graph for the avearge profit in millions per game for each publisher inputed "
   ]
  },
  {
   "attachments": {
    "sample_graph.png": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 1c: Planning \n",
    "#### Write or draw examples of what your program will produce\n",
    "\n",
    "Double click this cell to edit. \n",
    "\n",
    "You must include an image that shows what your chart or plot will look like. You can insert an image using the Insert Image command near the bottom of the Edit menu.\n",
    "\n",
    "expect(main('video_game_sample_graph_data.csv'), None)\n",
    "\n",
    "![sample_graph.png](attachment:sample_graph.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 2a: Building\n",
    "#### Document which information you will represent in your data definitions\n",
    "#### Design data definitions\n",
    "\n",
    "Double click this cell to edit.\n",
    "\n",
    "Before you design data definitions in the code cell below, you must explicitly document here which information in the file you chose to represent and why that information is crucial to the chart or graph that you'll produce when you complete step 2c.\n",
    "\n",
    "For each certain video game sold globally, we need to know its publisher and the global amount of sales. I need these two pieces of information because I plan to find and plot on a bar graph the average profit (in millions) per game for each publisher that is inputed (a total of any 5 publishers within the csv file).  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<>:28: SyntaxWarning: 'ellipsis' object is not callable; perhaps you missed a comma?\n",
      "<>:43: SyntaxWarning: 'ellipsis' object is not callable; perhaps you missed a comma?\n",
      "<>:28: SyntaxWarning: 'ellipsis' object is not callable; perhaps you missed a comma?\n",
      "<>:43: SyntaxWarning: 'ellipsis' object is not callable; perhaps you missed a comma?\n",
      "<ipython-input-2-bc8be708787d>:28: SyntaxWarning: 'ellipsis' object is not callable; perhaps you missed a comma?\n",
      "  return ...(vg.publisher,\n",
      "<ipython-input-2-bc8be708787d>:43: SyntaxWarning: 'ellipsis' object is not callable; perhaps you missed a comma?\n",
      "  ...(fn_for_video_game(vg), acc)\n"
     ]
    }
   ],
   "source": [
    "from cs103 import *\n",
    "from typing import NamedTuple, List\n",
    "import csv\n",
    "import matplotlib.pyplot as plt\n",
    "##################\n",
    "# Data Definitions\n",
    "\n",
    "VideoGame = NamedTuple('VideoGame', [('publisher', str),\n",
    "                                     ('global_sales', float)])  # in millions, in range[0, ...)\n",
    "\n",
    "# interp. a video game with the name of its publisher and the amount of global sales \n",
    "\n",
    "VG1 = VideoGame('Nintendo', 82.74)\n",
    "VG2 = VideoGame('Nintendo', 40.24)\n",
    "VG3 = VideoGame('Nintendo', 35.82)\n",
    "VG4 = VideoGame('Microsoft Game Studios', 21.82)\n",
    "VG5 = VideoGame('Activision', 14.64)\n",
    "VG6 = VideoGame('Take-Two Interactive', 21.4)\n",
    "VG7 = VideoGame('505 Games', 3.61)\n",
    "VG8 = VideoGame('Sega', 8.06)\n",
    "VG9 = VideoGame('Capcom', 6.3)\n",
    "VG10 = VideoGame('GT Interactive', 6.27)\n",
    "\n",
    "\n",
    "# template based on Compound\n",
    "@typecheck\n",
    "def fn_for_video_game(vg: VideoGame) -> ...:\n",
    "    return ...(vg.publisher,\n",
    "               vg.global_sales)\n",
    "\n",
    "# List[VideoGame]\n",
    "# interp. a list of video games\n",
    "\n",
    "LOVG0 = []\n",
    "LOVG1 = [VG1, VG2, VG3, VG4, VG5, VG6, VG7, VG8, VG9, VG10]\n",
    "\n",
    "# template based on arbitary-sized and reference rule\n",
    "@typecheck\n",
    "def fn_for_lovg(lovg: List[VideoGame]) -> ...:\n",
    "    # description of the acc\n",
    "    acc = ... # type: ...\n",
    "    for vg in lovg:\n",
    "        ...(fn_for_video_game(vg), acc)\n",
    "    \n",
    "    return acc"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 2b and 2c: Building\n",
    "#### Design a function to read the information and store it as data in your program\n",
    "#### Design functions to analyze the data\n",
    "\n",
    "\n",
    "Complete these steps in the code cell below. You will likely want to rename the analyze function so that the function name describes what your analysis function does."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92m2 of 2 tests passed\u001b[0m\n",
      "\u001b[92m2 of 2 tests passed\u001b[0m\n",
      "\u001b[92m3 of 3 tests passed\u001b[0m\n",
      "\u001b[92m2 of 2 tests passed\u001b[0m\n",
      "\u001b[92m1 of 1 tests passed\u001b[0m\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "###########\n",
    "# Functions\n",
    "\n",
    "@typecheck\n",
    "def read(filename: str) -> List[VideoGame]:\n",
    "    \"\"\"    \n",
    "    reads information from the specified file and returns a list of VideoGame data\n",
    "    \"\"\"\n",
    "    # return []  #stub\n",
    "    # Template from HtDAP\n",
    "    # loc contains the result so far\n",
    "    loc = [] # type: List[Consumed]\n",
    "\n",
    "    with open(filename) as csvfile:\n",
    "        \n",
    "        reader = csv.reader(csvfile)\n",
    "        lovg = []\n",
    "        next(reader) # skip header line\n",
    "\n",
    "        for row in reader:\n",
    "            vg = VideoGame(row[5],                 # just a str    \n",
    "                           parse_float(row[10]))   # represents a float [0.00, ...) \n",
    "            lovg.append(vg)\n",
    "    \n",
    "    return lovg\n",
    "\n",
    "start_testing()\n",
    "\n",
    "# examples and tests for read\n",
    "expect(read('video_game_information_test1.csv'), [VG1, VG2, VG3])\n",
    "expect(read('video_game_information_test2.csv'), [VideoGame('Capcom', 4.87),\n",
    "                                                  VideoGame('Nintendo', 4.85),\n",
    "                                                  VideoGame('Sony Computer Entertainment', 4.84)])      \n",
    "summary()\n",
    "\n",
    "\n",
    "def filter_publisher(vg: VideoGame, publisher: str) -> bool:\n",
    "    \"\"\"\n",
    "    filter by each publisher in the list from read\n",
    "    \"\"\"\n",
    "    # return True # stub\n",
    "    # template based on VideoGame, with additional parameter string\n",
    "    return vg.publisher == publisher\n",
    "\n",
    "start_testing()\n",
    "\n",
    "# examples and tests for filter_publisher\n",
    "expect(filter_publisher(VG1, 'Nintendo'), True)\n",
    "expect(filter_publisher(VG2, 'Capcom'), False)\n",
    "\n",
    "summary()\n",
    "\n",
    "def calc_avg_per_publisher(lovg: List[VideoGame], publisher: str) -> float:\n",
    "    \"\"\"\n",
    "    calculate the average sales per game for each publisher\n",
    "    \"\"\"\n",
    "    # return 0.0 #stub\n",
    "    # template based on List[VideoGame], with addtional parameter string\n",
    "    # two accumulators, sum and tally\n",
    "    # sum stores the total amount of sales for video games \n",
    "    # tally stores the number of games per publisher so far\n",
    "    sum = 0.0   # type: float\n",
    "    tally = 0   # type: int \n",
    "    for vg in lovg:\n",
    "        if filter_publisher(vg, publisher):\n",
    "            sum = sum + vg.global_sales\n",
    "            tally = tally + 1\n",
    "    if len(lovg) == 0:\n",
    "        return 0\n",
    "    else:\n",
    "        return sum/tally\n",
    "\n",
    "start_testing()\n",
    "\n",
    "# examples and tests for calculate_average_per_publisher\n",
    "expect(calc_avg_per_publisher([], ''), 0)\n",
    "expect(calc_avg_per_publisher([VG1], \"Nintendo\"), 82.74)\n",
    "expect(calc_avg_per_publisher([VG1, VG3], \"Nintendo\"), 59.28)\n",
    "\n",
    "summary()\n",
    "\n",
    "def list_of_averages(lovg: List[VideoGame], publisher1: str, publisher2: str, publisher3: str, publisher4: str, publisher5: str) -> List[float]:\n",
    "    # return [] #stub\n",
    "    # template based on List[VideoGame] with 5 addtional string parameters\n",
    "    \"\"\"\n",
    "    produces a list of calculated averages\n",
    "    \"\"\"\n",
    "    avg1 = calc_avg_per_publisher(lovg, publisher1)\n",
    "    avg2 = calc_avg_per_publisher(lovg, publisher2)\n",
    "    avg3 = calc_avg_per_publisher(lovg, publisher3)\n",
    "    avg4 = calc_avg_per_publisher(lovg, publisher4)\n",
    "    avg5 = calc_avg_per_publisher(lovg, publisher5)\n",
    "    return [avg1, avg2, avg3, avg4, avg5]\n",
    "    \n",
    "start_testing()\n",
    "\n",
    "# examples and tests for list_of_averages\n",
    "expect(list_of_averages([], '', '', '', '', ''), [0, 0, 0, 0, 0])\n",
    "expect(list_of_averages([VG8, VG7, VG9, VG10, VG6], 'Sega', '505 Games', 'Capcom', 'GT Interactive', 'Take-Two Interactive'), [8.06, 3.61, 6.3, 6.27, 21.4])\n",
    "\n",
    "summary()\n",
    "\n",
    "def bar_graph(lof: List[float], publisher1: str, publisher2: str, publisher3: str, publisher4: str, publisher5: str) -> None:\n",
    "    # return None #stub\n",
    "    # template based on List[float] with five additional string parameters\n",
    "    \"\"\"\n",
    "    creates a function that graphs the list of calculated averages\n",
    "    \"\"\"\n",
    "    x_values = [publisher1, publisher2, publisher3, publisher4, publisher5]\n",
    "    y_values = lof\n",
    "    bar_width = 0.8\n",
    "    plt.bar(x_values, y_values, bar_width, color='lightseagreen')\n",
    "    plt.xlabel('Publisher')\n",
    "    plt.ylabel('Average Sales per Game (in millions)')\n",
    "    plt.title(\"Average Sales per Game for Certain Publishers\")\n",
    "    plt.xticks(rotation=45)\n",
    "    plt.show\n",
    "    return None\n",
    "\n",
    "start_testing()\n",
    "\n",
    "# examples and tests for bar_graph\n",
    "expect(bar_graph([0.29, 2.54, 1.3, 0.75, 0.97],'505 Games', 'Nintendo', 'Microsoft Game Studios', 'Activision', 'Take-Two Interactive'), None)\n",
    "\n",
    "\n",
    "summary()\n",
    "    \n",
    "def main(filename: str, publisher1: str, publisher2: str, publisher3: str, publisher4: str, publisher5: str) -> None:\n",
    "    \"\"\"\n",
    "    produces a graph of the averages for each inputed publisher\n",
    "    \"\"\"\n",
    "    # return None #stub\n",
    "    # template based on composition\n",
    "    return bar_graph(list_of_averages(read(filename), publisher1, publisher2, publisher3, publisher4, publisher5), publisher1, publisher2, publisher3, publisher4, publisher5)\n",
    "    \n",
    "# tests for the main function are in seperate cells below\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92m1 of 1 tests passed\u001b[0m\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "start_testing()\n",
    "\n",
    "# examples and tests for main\n",
    "expect(main('global_video_game_sales_in_millions.csv', 'Nintendo', 'Microsoft Game Studios', '505 Games', 'Ubisoft', 'Sega'), None)\n",
    "\n",
    "summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[92m1 of 1 tests passed\u001b[0m\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "start_testing()\n",
    "\n",
    "# additional examples and tests for main\n",
    "expect(main('global_video_game_sales_in_millions.csv', 'Bethesda Softworks', 'Electronic Arts', 'Konami Digital Entertainment', 'Square Enix', 'THQ'), None)\n",
    "\n",
    "summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Final Graph/Chart\n",
    "\n",
    "Now that everything is working, you **must** call `main` on the intended information source in order to display the final graph/chart:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "main('global_video_game_sales_in_millions.csv', 'Nintendo', 'Microsoft Game Studios', 'Activision', 'Sony Computer Entertainment', 'Take-Two Interactive')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d1bb6d07888f4b65ba20c2940b87d7e5",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Valid(value=True, description='Token')"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6ee2c1a10f1b404eb6be7a04b9360ff3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "SelectMultiple(description='Files', index=(0,), layout=Layout(height='100%', width='50%'), options=('project_m…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7af004336d694842a62a6b7f303ad625",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Button(description='submit', icon='check', style=ButtonStyle(), tooltip='submit')"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Be sure to select ALL THE FILES YOU NEED (including csv's) \n",
    "# when you submit. As usual, you cannot edit this cell.\n",
    "# Instead, run this cell to start the submission process.\n",
    "from cs103 import submit\n",
    "\n",
    "COURSE = 53525\n",
    "ASSIGNMENT = 596984 # Final submission\n",
    "\n",
    "submit(COURSE, ASSIGNMENT)\n",
    "\n",
    "# If your submission fails, SUBMIT by downloading your files and uploading them \n",
    "# to Canvas. You can learn how on the page \"How to submit your Jupyter notebook\" \n",
    "# on our Canvas site."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "celltoolbar": "Edit Metadata",
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.11.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}