Great_Gatsby_Analysis.ipynb

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      "name": "Great Gatsby Color Analysis",
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      "source": [
        "# Deducing Plot in <i> The Great Gatsby </i> By Analyzing the Narrative Timeline of Colors"
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        "## Goal/Purpose\n",
        "\n",
        "In literature, color is often an essential motif, as it helps an author convey certain messages and thus can help with analysis of a work. Different colors are associated with various meanings; red, for example, is often associated with love and passion, while white is connected with purity and holiness.\n",
        "\n",
        "Therefore, it would be useful to construct a program that \"reads\" a text, and extracts the frequency of the usage of different colors throughout the text. Such a program would save many hours of analyzing a work by hand and would help readers interpret a novel.\n",
        "\n",
        "One could even argue that a chapter-by-chapter analysis of colors could help deduce the plot of a novel, to some extent, as readers could associated rises and drops in the frequency of colors in a chapter with events and themes throughout the chapter. Therefore, the goal of this document is to create a program that takes a text and plots the frequency of the occurence of color-related words in every chapter of a book. Doing so would allow for a side-by-side comparison of the usage of colors in chapters in the novel and would save literary analysts much time."
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      "source": [
        "import numpy as np\n",
        "import string\n",
        "import matplotlib as plt\n",
        "import matplotlib.patheffects as mpe\n",
        "import matplotlib.pyplot as plt"
      ],
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      "source": [
        "filename = 'Gatsby.txt'\n",
        "file = open(filename, encoding = \"ISO-8859-1\" )\n",
        "text = file.read()\n",
        "file.close()\n",
        "# split into words by white space\n",
        "words = text.split()\n",
        "# remove punctuation from each word\n",
        "punctuation = str.maketrans('', '', string.punctuation)\n",
        "gatsby = [i.translate(punctuation) for i in words] #list of the words in the book"
      ],
      "execution_count": 0,
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      "source": [
        "To decide what colors to use, I looked at the palette of <i> The Great Gatsby </i> and noticed that the major colors used in the Great Gatsby are White, Golden, Silver, Gray, Lavender, Pink, Red, Green, and Blue.\n",
        "The traditional meanings assigned to these colors in the Great Gatsby are as follows:\n",
        "\n",
        "White represents purity and high morals.\n",
        "\n",
        "Golden represents wealth and sucess.\n",
        "\n",
        "Silver represents material wealth, like jewels.\n",
        "\n",
        "Gray represents the unininteresting, or the mundane.\n",
        "\n",
        "Lavender often represents the excess indulgences of the wealthy.\n",
        "\n",
        "Pink represents romance, love, and passion.\n",
        "\n",
        "Red represents shame and rage.\n",
        "\n",
        "Green represents hope.\n",
        "\n",
        "Blue represents the superficiality of wealth, as well as the depression associated with this facade.\n",
        "\n",
        "\n",
        "Sources:\n",
        "\n",
        "Haibing, Z. (2015). Symbolic Meanings of Colors in The Great Gatsby. Studies in Literature and Language, 10, 38-44.\n",
        "\n",
        "Huber, H. (2011, August 11). The Use of Colors in <i> The Great Gatsby </i>. Retrieved from http://www.lesekost.de/amlit/HHL252C.htm\n",
        "\n",
        "Stribley, M. (2019, February 01). The History and Psychology of Colors. Retrieved from https://www.canva.com/learn/color-meanings/\n",
        "\n"
      ]
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      "source": [
        "In order to clarify and analyze usage of colors as it relates to plot, the following functions and lines of code will be used to plot different mentions of colors in the book throughout narrative time."
      ]
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        "def splitIntoChapters(textList):\n",
        "  \"\"\"\n",
        "  Parameters:\n",
        "  textList (list): list of words representing a book\n",
        "  \n",
        "  Returns:\n",
        "  A list of floats representing the positions of chapters, relative to the entire book length\n",
        "  \"\"\"\n",
        "  \n",
        "  bookLength = 0 #represents total number of words in book\n",
        "  chapterLocations = [] #represents location of chapters in book\n",
        "  chapterPos = [] #represents relative location of chapters in book\n",
        "  for i in range(len(textList)):\n",
        "    bookLength+=1\n",
        "  for i in range(len(textList)):\n",
        "    if textList[i] == \"Chapter\":\n",
        "      chapterLocations.append(i/bookLength)\n",
        "  chapterLocations.append(1) #add last point for the end of the book\n",
        "  graphPoints = np.array_split(chapterLocations, len(chapterLocations)) #split array into number of chapters\n",
        "  for i in graphPoints:\n",
        "    chapterPos.append(i.item(0))\n",
        "  return chapterPos"
      ],
      "execution_count": 0,
      "outputs": []
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      "source": [
        "chapterPosition = splitIntoChapters(gatsby) #list of chapters locations relative to book length\n",
        "chapterPositionWords = [i * len(gatsby) for i in chapterPosition] #list of chapter locations based on how\n",
        "                                                                  #many words into the book each chapter starts at"
      ],
      "execution_count": 0,
      "outputs": []
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      "source": [
        "def colorSum(textList):\n",
        "  from collections import defaultdict\n",
        "  colors1 = []\n",
        "  \"\"\"\n",
        "  Parameters:\n",
        "  textList (list): list of words representing a book\n",
        "  \n",
        "  Returns:\n",
        "  A list representing the number of mentions of each color in a text\n",
        "  \"\"\"\n",
        "\n",
        "  textList = [i.lower() for i in textList] #lowercase each word in book\n",
        "  \n",
        "  colors_dict = defaultdict(int) #initialize dictionary\n",
        "  \n",
        "  #list of colors to search for\n",
        "  colors = ['white','gold','silver','grey','lavender','pink','red','green','blue']\n",
        "  \n",
        "  for i in textList:\n",
        "    if i in colors:\n",
        "      colors_dict[i] += 1 #create dictionary with colors and corresponding values\n",
        "      \n",
        "  for i in colors:\n",
        "    colors1.append(colors_dict[i]) #make list with ints representing number of mentions of colors in textList\n",
        "  return (colors1)\n"
      ],
      "execution_count": 0,
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        "def countColorInChapters(textList, chapterWordLocation):\n",
        "  \"\"\"\n",
        "  Parameters: \n",
        "  textList(list): list of words representing a book\n",
        "  chapterWordLocation(list): list of ints representing at what word count the chapters in a book begin\n",
        "  \n",
        "  Returns:\n",
        "  A list of lists of ints representing the number of mentions of colors in each chapter of the book\n",
        "  \n",
        "  \"\"\"\n",
        "\n",
        "  colorCount = []\n",
        "  #colorCount.append([0,0,0,0,0,0,0,0,0]) #accounts for the very start of the book\n",
        "  for i in range(1,len(chapterWordLocation)):\n",
        "    start = int(chapterWordLocation[i-1]) #word that represents start of the chapter\n",
        "    end = int(chapterWordLocation[i]) #word that represents the end of the chapter\n",
        "    colorCount.append(colorSum(textList[start:end])) #calculates the number of colors in the chapter\n",
        "  return colorCount"
      ],
      "execution_count": 0,
      "outputs": []
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      "source": [
        "colorCount = countColorInChapters(gatsby, chapterPositionWords)"
      ],
      "execution_count": 0,
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      "source": [
        "def graphColorsNarrativeTimeLine(colorCount,chapterPosition,bookTitle):\n",
        "  \"\"\"\n",
        "  Parameters:\n",
        "  colorCount (list of lists): list of lists of ints representing the number of mentions of colors in each chapter of the book\n",
        "  chapterPosition(list): list of floats representing chapter location relative to book length\n",
        "  bookTitle(string): string representing the title of the book\n",
        "  \n",
        "  Returns:\n",
        "  A line plot that depicts the change in color throughout chapters and narrative time in the novel; the chapters are\n",
        "  labeled in order from left to right\n",
        "  \"\"\"\n",
        "  \n",
        "  colors = ['White','Gold','Silver','Gray','Purple','Pink','Red','Green','Blue']\n",
        "  xvalues = []\n",
        "  yvalues = []\n",
        "  x = []\n",
        "  chapterList = []\n",
        "  \n",
        "  #set up plot, title, and axes labels\n",
        "  fig = plt.figure(figsize=(15,8))\n",
        "  ax1 = fig.add_subplot(111)\n",
        "  ax1.set_xlim(left = 0,right = 1.3)\n",
        "  ax1.set_xlabel('Relative position in book')\n",
        "  ax1.set_ylabel('Frequency of color-related words')\n",
        "  ax1.set_title('The Usage of Color Over Time in ' + bookTitle)\n",
        "  \n",
        "  #graphs approporiately colored points representing the usage of colors over time\n",
        "  colorCount.append([0,0,0,0,0,0,0,0,0])\n",
        "  for i in range(len(chapterPosition)):\n",
        "    for j in range(len(colorCount[0])):\n",
        "      ax1.scatter(chapterPosition[i], colorCount[i][j], c = colors[j], edgecolor = 'black')\n",
        "  for i in chapterPosition:\n",
        "      xvalues.append(i)\n",
        "      \n",
        "  #plots a scatter plot line connecting the points with the appropriate colored lines\n",
        "  for j in range(len(colorCount[0])):\n",
        "    x= []\n",
        "    yvalues.append(x)\n",
        "    for i in range(len(colorCount)):\n",
        "      x.append(colorCount[i][j])\n",
        "  #path effects ensure that there is a border around each line so the white line will not look invisible\n",
        "  pe = [mpe.Stroke(linewidth=2, foreground='black'),\n",
        "        mpe.Stroke(foreground='black',alpha=1),\n",
        "        mpe.Normal()]\n",
        "  for i in range(len(colorCount[0])):\n",
        "    ax1.plot(xvalues, yvalues[i], label='{}'.format(colors[i]), marker='o', color = colors[i], path_effects = pe)\n",
        "    \n",
        "  #adds values to chapterList to signify the positions of chapter in narrative time \n",
        "  for i in range(len(chapterPosition)):\n",
        "    if (i == 0):\n",
        "      chapterList.append('start')\n",
        "    elif (i == len(chapterPosition)-1):\n",
        "      chapterList.append('End of Chapter' + str(i))\n",
        "    else:\n",
        "      chapterList.append(\"Chapter \" + str(i))\n",
        "  #plots the chapters as vertical lines\n",
        "  list3 = []\n",
        "  list4 = []\n",
        "  for i in range(len(chapterPosition)):\n",
        "    plt.axvline(x = chapterPosition[i],color = 'black', linestyle = \":\")\n",
        "    list3.append(chapterPosition[i])\n",
        "    list4.append(chapterList[i])\n",
        "  plt.xticks(list3,list4) #labels chapters\n",
        "  ax1.legend()\n",
        "  \n",
        "  colorCount.remove([0,0,0,0,0,0,0,0,0])\n",
        "  return ax1"
      ],
      "execution_count": 0,
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      "source": [
        "graphColorsNarrativeTimeLine(colorCount,chapterPosition, 'The Great Gatsby')"
      ],
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mnDt3Di8vr0x5DR06lM2bN9O7d29OnTqlbnrvpjylr1pKb/laStVFyU5wcLBV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uiYnMAFYDWsDHq+I94ATU+z+5TqaYT6G2qI1/OX/mj5Y/z5GOjg537tyhZ8+eBAYGUqtWLYxN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7f5QKp8CwvWWtOoy1UKFop53k2nTp0oVKgQly5dYtu2bTqHpCWm3RRFoVOnThQoUIDHjx/T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\nAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 1080x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "L3J-0qXWl1GW",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def maxVal(list1):\n",
        "  \"\"\"\n",
        "  Parameters:\n",
        "  list1 (list of lists) - a list of lists of floats or integers\n",
        "  \n",
        "  Returns:\n",
        "  The maximum value of the list of lists\n",
        "  \"\"\"\n",
        "  maxValue = 0\n",
        "  for i in range(len(list1)):\n",
        "    for j in range(len(list1)):\n",
        "      if (list1[i][j] > maxValue):\n",
        "        maxValue = list1[i][j]\n",
        "  return maxValue\n",
        "      "
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VnPnkmrOz6mM",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def graphColorsNarrativeTimeBar(colorCount,chapterPosition,bookTitle):\n",
        "  \"\"\"\n",
        "  Parameters:\n",
        "  colorCount (list of lists): list of lists of ints representing the number of mentions of colors in each chapter of the book\n",
        "  chapterPosition(list): list of floats representing chapter location relative to book length\n",
        "  bookTitle(string): string representing the title of the book\n",
        "  \n",
        "  Returns:\n",
        "  A line plot that depicts the change in color throughout chapters and narrative time in the novel; the chapters are\n",
        "  labeled in order from left to right\n",
        "  \"\"\"\n",
        "  \n",
        "  colors = ['White','Gold','Silver','Gray','Purple','Pink','Red','Green','Blue'] #list of colors\n",
        "\n",
        "  #set up plot, title, and axes labels\n",
        "  fig = plt.figure(figsize=(15,8))\n",
        "  ax1 = fig.add_subplot(111)\n",
        "  #ax1.set_xlim(left = 0,right = 100)\n",
        "  ax1.set_xlabel('Relative position in book', fontsize = 15)\n",
        "  ax1.set_ylabel('Frequency of color-related words', fontsize = 15)\n",
        "  ax1.set_title('The Usage of Color Over Time in ' + bookTitle, fontsize = 15)\n",
        "  \n",
        "  #graphs approporiately colored points representing the usage of colors over tim\n",
        "  xvals = np.arange(len(colorCount[0]))\n",
        "  colorxs = []\n",
        "  colorys = colors[:]\n",
        "  colorystemp = [colorys[i][0:2] for i in range(len(colorys))] #abbreviates color names \n",
        "  colorys = colorystemp[:]\n",
        "  xvalsplot = []\n",
        "  vLineTrack = []\n",
        "  for i in range(len(colorCount)):\n",
        "    ax1.bar(xvals+(i*len(chapterPosition)),colorCount[i], width = 1, edgecolor = 'black',color = colors) #graphs approporiate bars\n",
        "    colorxs.extend((xvals+(i*len(chapterPosition))).tolist()) #x-vals for where to place color labels\n",
        "    colorys.extend(colorystemp) #corresponding labels\n",
        "    vLineTrack.extend([len(colorCount[0])-1+len(chapterPosition)*i]) #used for plotting vertical lines\n",
        "\n",
        "  height = maxVal(colorCount) #height of the graph\n",
        "  plt.xticks(colorxs,colorys,fontsize = 10) #make appropriate ticks on graph\n",
        "  fig.set_size_inches(len(chapterPosition)*3, height+1, forward=True) #set figure size - could also make this interactive so user can choose\n",
        "\n",
        "  \n",
        "  xvalsplot = colorxs[:] #deep copy\n",
        "  vLines = [] #list for where to plot vertical lines\n",
        "\n",
        "  \n",
        "  for i in range(len(xvalsplot)):\n",
        "    if (xvalsplot[i] in vLineTrack):\n",
        "      vLines.append(xvalsplot[i]+1) #append appropriate list for vertical lines\n",
        "\n",
        "\n",
        "  for i in range(len(vLines)):\n",
        "    plt.axvline(x = vLines[i],color = 'black', linestyle = \":\") #plot vertical lines\n",
        "\n",
        "\n",
        "  chapterLabels = [] #used for plotting labels of chapters\n",
        "\n",
        "  #used for labels\n",
        "  for i in range(0,len(vLines)):\n",
        "    chapterLabels.append('Chp. ' + str(i+1))\n",
        "\n",
        "\n",
        "\n",
        "    \n",
        "  #label chapters\n",
        "  for i in range(0,len(chapterLabels)):\n",
        "    ax1.text((i*len(chapterPosition))+(len(colorCount[0])-1)/2,height,chapterLabels[i], fontsize = 15)\n",
        "\n",
        "\n",
        "  "
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ih-N0FvlUCkY",
        "colab_type": "code",
        "outputId": "0330efcb-7d3e-472e-a19c-9ed28cf6907c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 648
        }
      },
      "source": [
        "graphColorsNarrativeTimeBar(colorCount,chapterPosition, 'The Great Gatsby')"
      ],
      "execution_count": 318,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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EXAzu2p7Wl2PJ3U12YhsG27A2sZ8FPgU0le2RZ5ZsrOwFm9Ylc7xwtp1rZ737Vn9R1/D9hyGmPe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\nSZIkSZIkSdKs9v/t1JsL3SYZAAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 2160x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uQ9vm5P-0tZg",
        "colab_type": "text"
      },
      "source": [
        "## Analysis of Graph"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RVMpaajN0qvw",
        "colab_type": "text"
      },
      "source": [
        "The graph above is very interesting because it emphasizes the fluctuations of color throughout <i> The Great Gatsby</i>. Notice how easily visible the distribution of colors throughout the narrative timeline of <i> The Great Gatsby </i>, when the data is presented in the bar graph above."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0do9dg571Lpk",
        "colab_type": "text"
      },
      "source": [
        "For this analysis, let's simultaneously consider a brief summary of eaach chapter, and, recalling the meanings associated with color as described earlier, note how this is perhaps reflected in fluctuations of colors."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UrDVmt2H1wnA",
        "colab_type": "text"
      },
      "source": [
        "<b> Chapter 1 </b>\n",
        "In Chapter 1, readers are introduced to Nick Carraway, the narrator of the story. The drastic increase in white is notable here, as Nick describes his high morals. Nick meets up with his cousin, Daisy Buchanan, and her husband Tom, for dinner. He is also introduced to Daisy's friend, Jordan. The lack of a pink color here is interesting, as Tom is cheating on Daisy, and there does not seem to be a big connection betwee Nick and Jordan - thus the lack of pink represents the lack of passion between the individuals at the dinner. In addition, the large increase in red signifies the hidden shame and rage that is present in the room - Tom may feel guilty for cheating on his wife, and his wife may feel a deep, inner rage, toward her husband because he is cheating on her. The last notable color fluctuation here is the slight increase in green, simply because it is not used much in the beginning of the book, but rather comes into play later, when Gatsby enters the scene. However, as Nick sees Gatsby for the time, Gatsby is looking out into the water, gazing at a green light. This green light represent the hope that Nick feels upon seeing Gatsby - he is a new person in Nick's life and perhaps may teach Nick some valuable lessons. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "niNrNM881y3z",
        "colab_type": "text"
      },
      "source": [
        "<b> Chapter 2</b> The major color fluctuations in this chapters are the increases in the colors blue and gray. Tom and Nick take the train into the city, and Nick notes the grayness of the city, including a billboard for an optometrist. This sense of dull lifenesses contributes to the large increase of gray in this chapter, as gray is indicative of the mundane qualities of life. Tom and Nick meet Myrtle, Tom's mistress, and they head back to the apartment that Tom has for Myrtle. Tom hosts a party with friends at the apartment, but it ends badly, as Myrtle and Tom argue about Daisy and Tom ultimately breaks Myrtles's nose. The increase in blue in this chapter is significant, because it emphasizes the depression and the loss of hope associated with using money to act as a shield from the world. Tom tries to use his money to enjoy life, but deep down he realizes the essential issues with his life, such as the immorality associated with cheating on his wife, and it is hard for him to ignore this, even when he uses his wealth as a shield from these problems. Again, note the total lack of pink in this chapter, as there is no true romantic passion between lovers in this chapter."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iQEFgBRM_EJR",
        "colab_type": "text"
      },
      "source": [
        "<b> Chapter 3 </b>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mdfaKnog_IcH",
        "colab_type": "text"
      },
      "source": [
        "The color analysis for this chapter is very interesting, as during this chapter Nick describes Gatsby's luxurious parties, and attends one himself. The luxury of these parties contributes to the increase in yellow, as Nick is reminded of the wonders associated with wealth and success. Also note the drastic decrease of gray, as this chapter does not reflect the dull qualities of life, but rather emphasizes the wonders and luxuries associated with wealthy nightlife. At the party, Nick meets Gatsby and also runs into Jordan. The large decrease in the usage of white in this chapter is reflective of the fact that Nick discovers a personality trait of Jordan: she is dishonest. Nick finds out that Jordan cheats in golf and is generally not truthful; the decrease in the color white, which represents high morals and purity, reflects this notion of Jordan's dishonesty."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "v7dn-HfpBmKq",
        "colab_type": "text"
      },
      "source": [
        "<b> Chapter 4 </b> In Chapter 4, Nick learns more about Gatsby, and also meets his shady friend, Meyer Wolfshiem, who is involved in organized crime and illegal betting. Thus, it is interesting to see such an increase in the usage of the color white in this chapter. Perhaps this increase can be attributed to Gatsby's life story. Nick believes that Gatsby is lying to him, but in fact some of his tales later turn out to be accurate, reflecting truth and thus meriting an increase in the color white. In addition, Nick learns that Daisy had originally planned to marry Gatsby, but, after he went overseas for the war, Tom pursued her and she ultimately married him - an action which, to some extent, she regrets. Gatsby still secretely hopes to win Daisy back, which is why his house his so close to Daisy's; he throws such fancy parties in hopes that Daisy will attend. Thus, the increase in red in this chapter reflects the inner anger and regret that both Daisy and Gatsby feel. There is currently no passion between them, and thus the pink color remains low."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7DP44tA0ENrs",
        "colab_type": "text"
      },
      "source": [
        "<b> Chapter 5 </b> Chapter 5 is a unique chapter thus far, as events seem to turn out relatively well. Gatsby, although initially nervous, ends up meeting with Daisy by himself, and the two get along very well. Daisy appreciates Gatsby's material wealth. Note the large changes in color here - pink, green, lavender, and yellow all increase significantly, while red decreases. Pink experiences a large increase because there is a reuinted love, a strong passion, between Gatsby and his former lover, Daisy. Green sees a spike because Gatsby has a newfound hope - perhaps he and Daisy may work out after all. Lavender also sees a large increase, as Gatsby flaunts his wealth to Daisy. Seeing that lavender is reflective of material indulgence, which Gatsby is no stranger to, the increase in lavender represents Gatsby's many material possesions. Yellow also increases because Gatsby appears to be satisfied with his wealth and success, as it seems like this wealth may draw Daisy back to him. Red decreases because the shame and anger built up deep in Gatsby and Daisy recede in this chapter, as the two happily reunite. However, one cannot ignore the large drop in white in this chapter - it signifies the lack of morals that Gatsby has had to exercise in order to become so wealthy. It could also signify that Daisy feels impure - rather than waiting for Gatsby to return from overseas she was tempted by Tom and now perhaps feels guilty."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7GftnCyqF_4x",
        "colab_type": "text"
      },
      "source": [
        "<b> Chapter 6 </b> In Chapter 6, Nick reveals some of Gatsby's true background, and readers begin to realize that <i> parts </i> of Gatsby's tales were a lie. Thus, there is an increase in white, as the truth is revealed. Gatsby did not start as a wealthy individual, he is part of the \"new rich\", rather than the \"old rich\", and thus the decrease of lavender in this chapter represents Gatsby's initial lack of material wealth. In addition, Tom, acting as the epitome of a hypocrite, visits Gatsby, as he is suspicious that Daisy visits Gatsby's house alone. However, Tom does not yet know that Daisy and Gatsby love each other. Tom thinks that Gatsby lacks proper social skills. Thus, the decrease in yellow symolizes Gatsby's seeming lack of success, in Tom's eyes. In addition, the decrease in pink resembles the lack of passion that Tom and Gatsby feel for each other, and perhaps foreshadows animosity between the two."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ytNBTUg0KsV2",
        "colab_type": "text"
      },
      "source": [
        "<b> Chapter 7 </b> In Chapter 7, the primary color fluctuations occur with pink and white. There is a great increase in passion, as Tom realizes that Gatsby and Daisy love each other and Myrtle's husband, Wilson, also discovers Myrtle's infidentlity. There is great tension, as Gatsby and Tom confront each other in a New York City hotel, but Daisy ultimately ends up choosing Tom over Gatsby.  Daisy and Gatsby end up driving back from New York City together in Tom's car, and Daisy hits Myrtle with the car, killing her. Gatsby, however, says that he will take the blame for Daisy. Thus, it is interesting that white increases in this chapter, as there are many decietful and immoral events occuring, but perhaps this is due to the purity that results as the cheating going on among couples has finally been brought out into the open. The elephant in the room has revealed itself."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "idLJIBQKMwdY",
        "colab_type": "text"
      },
      "source": [
        "<b> Chapter 8 </b> In this Chapter, Gatsby reveals that he lied to Daisy about his wealthy background upon meeting her, in order to woo her. Thus, white drops, as Gatsby reveals his tendency to lie. In addition, Wilson vows to get revenge on the individual who killed Myrtle, so he, believing it was Gatsby, kills Gatsby as he lounges in the pool, before killing himself. Thus, pink plummets, as there can no longer be any chance of passion between Gatsby and Daisy. Also, the use of green decreases as Gatsby's hopes of finding love are destroyed the moment he is killed. Red increases slighly too, perhaps representing the extreme rage of Wilson."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OB3F7oJdMLiu",
        "colab_type": "text"
      },
      "source": [
        "<b> Chapter 9 </b> In the last chapter of the book, Nick arranges a funeral for Gatsby, which almost nobody, with the exception of some servants and Gatsby's father, attends. Nick decides to move back to the Midwest, and runs into Tom one last time, who explains that he thought Gatsby deserved to die, and thus told Wilson that the car used to kill Myrtle belonged to Gatsby. Almost all of the colors in this chapter, with the exception of green, plummet. Silver, which has not played a big role thus far, drops, representing the lack of material wealth that Gatsby now owns, as he is dead. Similarly, yellow decreases, as Gatsby can no longer enjoy the benefits of his wealth. Blue also decreases, as readers understand that it is not healthy, and arguably not possible, to live ones life behind a shield of wealth. Interestingly, the only color that increases in this chapter is green, which represents the hope that Nick has for his future in the Midwest."
      ]
    }
  ]
}