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 "cells": [
  {
   "cell_type": "markdown",
   "id": "worldwide-blood",
   "metadata": {},
   "source": [
    "# Introduction"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0147bb48-a7c6-4102-973f-042b657a2b96",
   "metadata": {},
   "source": [
    "Argument Project Research - Nelson Mason - November 3, 2025"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "greater-circular",
   "metadata": {},
   "source": [
    "## Overarching Question: \n",
    "I want to know about what relationship exists, if any, between an adult (18 +) person's age and their weight (metric-kg.).\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "permanent-pollution",
   "metadata": {},
   "source": [
    "# Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "technical-evans",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set_theme()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "overhead-sigma",
   "metadata": {},
   "outputs": [],
   "source": [
    "file_name = \"brfss_2020_cleaned.csv\"\n",
    "dataset_path = \"data/brfss_2020_cleaned.csv\"\n",
    "people = pd.read_csv(\"data/brfss_2020_cleaned.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "fdd2f3af-ab54-442c-96de-14bc27a215b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='age', ylabel='count'>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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       "<Figure size 640x480 with 1 Axes>"
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     "metadata": {},
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   ],
   "source": [
    "sns.countplot(data=people, x=\"age\", hue=\"age\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92404f8d-3c67-4d7b-8781-2f8725609eed",
   "metadata": {},
   "source": [
    "I want to see a count of people by every age group.\n",
    "Is this distribution of any significance?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "13abb8a8-b75d-4381-a0cd-92eabb0f2ca7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='weight', ylabel='Count'>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
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       "<Figure size 640x480 with 1 Axes>"
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     "metadata": {},
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    }
   ],
   "source": [
    "sns.histplot(data=people, x=\"weight\", bins=15)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "363219c6-9a49-4170-bc80-ae5a2b89606e",
   "metadata": {},
   "source": [
    "I want to see a count of people by weight(kg). Is this distribution of any significance?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "heated-blade",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='age', ylabel='weight'>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
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     "metadata": {},
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    }
   ],
   "source": [
    "sns.barplot(data=people, x=\"age\", y=\"weight\", hue=\"age\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "continental-franklin",
   "metadata": {},
   "source": [
    "I'm trying to find out at what age, on average, do people experience a dramatic\n",
    "weight gain or loss, if at all.\n",
    "I'm curious to find out if such a dramatic increase or decrease in weight can\n",
    "be captured in a one-time snapshot database, where individuals are NOT tracked \n",
    "over a period of time, but ONLY once."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "infinite-instrument",
   "metadata": {},
   "source": [
    "# Methods and Results"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "recognized-positive",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true
   },
   "source": [
    "Since this chart of this dataset shows that an age 65+ person, on average, is closer in weight to an age 18 to 30 person, does that mean he or she is as healthy?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "graduate-palmer",
   "metadata": {},
   "source": [
    "### Methods"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "endless-variation",
   "metadata": {},
   "source": [
    "*Explain how you will approach this research question below. Consider the following:* \n",
    "  - *Which aspects of the dataset will you use?* \n",
    "  - *How will you reorganize/store the data?* \n",
    "  - *What data science tools/functions will you use and why?* \n",
    "  \n",
    "✏️ *Write your answer below:*\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "portuguese-japan",
   "metadata": {},
   "source": [
    "### Results "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "demographic-future",
   "metadata": {},
   "source": [
    "### Methods"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "incorporate-roller",
   "metadata": {},
   "source": [
    "*Explain how you will approach this research question below. Consider the following:* \n",
    "  - *Which aspects of the dataset will you use?* \n",
    "  - *How will you reorganize/store the data?* \n",
    "  - *What data science tools/functions will you use and why?* \n",
    "\n",
    "✏️ *Write your answer below:*\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "juvenile-creation",
   "metadata": {},
   "source": [
    "### Results "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "pursuant-surrey",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='age', ylabel='weight'>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
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   ],
   "source": [
    "sns.boxplot(data=people, x=\"age\", y=\"weight\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "43e1b5fb-0ec8-4bd1-838c-135e2e9211d9",
   "metadata": {},
   "source": [
    "I want to see a distribution of people by age by weight. \"A box plot displays the\n",
    "distribution of a dataset through its quartiles, highlighting the median, \n",
    "interquartile range and potential outliers. It provides a visual summary of \n",
    "the data's central tendency, dispersion, and skewness.\" \n",
    "- https://www.geeksforgeeks.org/data-visualization/types-of-seaborn-plots/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "located-night",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='age', ylabel='weight'>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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       "<Figure size 640x480 with 1 Axes>"
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(data=people, x=\"age\", y=\"weight\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71e53cb6-d91c-4d61-ba34-61e4344c4059",
   "metadata": {},
   "source": [
    "I want to see the main distribution of people by age by weight. \"A violin plot (violinplot) combines\n",
    "a box plot with a kernel density plot, showing the distribution, probability density,\n",
    "and central tendencies of the data. It provides a detailed view of the data's distribution, \n",
    "highlighting variations and multimodalities.\" - https://www.geeksforgeeks.org/data-visualization/\n",
    "types-of-seaborn-plots/"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "infectious-symbol",
   "metadata": {},
   "source": [
    "# Discussion"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "furnished-camping",
   "metadata": {
    "code_folding": []
   },
   "source": [
    "## Considerations"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bearing-stadium",
   "metadata": {},
   "source": [
    "*It's important to recognize the limitations of our research.\n",
    "Consider the following:*\n",
    "\n",
    "- *Do the results give an accurate depiction of your research question? Why or why not?*\n",
    "- *What were limitations of your datset?*\n",
    "- *Are there any known biases in the data?*\n",
    "\n",
    "✏️ *Write your answer below:*"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "beneficial-invasion",
   "metadata": {},
   "source": [
    "## Summary"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "about-raise",
   "metadata": {},
   "source": [
    "*Summarize what you discovered through the research. Consider the following:*\n",
    "\n",
    "- *What did you learn about your media consumption/digital habits?*\n",
    "- *Did the results make sense?*\n",
    "- *What was most surprising?*\n",
    "- *How will this project impact you going forward?*\n",
    "\n",
    "✏️ *Write your answer below:*"
   ]
  }
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