IntroToMLFinalProject.ipynb

{
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  {
   "cell_type": "markdown",
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   "source": [
    "# Predictions in Social Media Using Machine Learning"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e52c031",
   "metadata": {},
   "source": [
    "INFO 1998 Final Project"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f8af0b3",
   "metadata": {},
   "source": [
    "Sohan Madishetty, Sanya Mahajan, Nathan Varghese, Vansh Bherwal"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b03b4df",
   "metadata": {},
   "source": [
    "Introduction: This project aims to analyze the effect of social media on indviduals by using concepts learned in the course INFO 1998. Some specific questions we are looking at are how does the amount of time spent on social media impact their mental health and how does the amount of time spent on social media impact if one feels depressed or not? \n",
    "\n",
    "Our hypthoesis is that if an individual spends more time on social media, then they are likely to face depression than someone who does not and spending time on social media will negatively affect their mental health.\n",
    "\n",
    "Dataset: https://www.kaggle.com/datasets/souvikahmed071/social-media-and-mental-health/data"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "Data:\n",
    "The set contains these columns to analyze:\n",
    "- Age\n",
    "- Gender\n",
    "- Relationship Status\n",
    "- Occupation Status\n",
    "- type of organizations affiliated with\n",
    "- social media use (yes/no)\n",
    "- social media platforms commonly used\n",
    "- average time spent on social media every day (hrs)\n",
    "- How often do you find yourself using Social media without a specific purpose\n",
    "- How often do you get distracted by Social media when you are busy doing something?\n",
    "- Do you feel restless if you haven't used Social media in a while?\n",
    "- On a scale of 1 to 5, how easily distracted are you?\n",
    "- On a scale of 1 to 5, how much are you bothered by worries?\n",
    "- Do you find it difficult to concentrate on things?\n",
    "- On a scale of 1-5, how often do you compare yourself to other successful people through the use of social media?\n",
    "- Following the previous question, how do you feel about these comparisons, generally speaking?\n",
    "- How often do you look to seek validation from features of social media?\n",
    "- How often do you feel depressed or down?\n",
    "- On a scale of 1 to 5, how frequently does your interest in daily activities fluctuate?\n",
    "- On a scale of 1 to 5, how often do you face issues regarding sleep?"
   ]
  },
  {
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   "id": "9d96ff67",
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     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 481 entries, 0 to 480\n",
      "Data columns (total 21 columns):\n",
      " #   Column                                                                                                                Non-Null Count  Dtype  \n",
      "---  ------                                                                                                                --------------  -----  \n",
      " 0   Timestamp                                                                                                             481 non-null    object \n",
      " 1   1. What is your age?                                                                                                  481 non-null    float64\n",
      " 2   2. Gender                                                                                                             481 non-null    object \n",
      " 3   3. Relationship Status                                                                                                481 non-null    object \n",
      " 4   4. Occupation Status                                                                                                  481 non-null    object \n",
      " 5   5. What type of organizations are you affiliated with?                                                                451 non-null    object \n",
      " 6   6. Do you use social media?                                                                                           481 non-null    object \n",
      " 7   7. What social media platforms do you commonly use?                                                                   481 non-null    object \n",
      " 8   8. What is the average time you spend on social media every day?                                                      481 non-null    object \n",
      " 9   9. How often do you find yourself using Social media without a specific purpose?                                      481 non-null    int64  \n",
      " 10  10. How often do you get distracted by Social media when you are busy doing something?                                481 non-null    int64  \n",
      " 11  11. Do you feel restless if you haven't used Social media in a while?                                                 481 non-null    int64  \n",
      " 12  12. On a scale of 1 to 5, how easily distracted are you?                                                              481 non-null    int64  \n",
      " 13  13. On a scale of 1 to 5, how much are you bothered by worries?                                                       481 non-null    int64  \n",
      " 14  14. Do you find it difficult to concentrate on things?                                                                481 non-null    int64  \n",
      " 15  15. On a scale of 1-5, how often do you compare yourself to other successful people through the use of social media?  481 non-null    int64  \n",
      " 16  16. Following the previous question, how do you feel about these comparisons, generally speaking?                     481 non-null    int64  \n",
      " 17  17. How often do you look to seek validation from features of social media?                                           481 non-null    int64  \n",
      " 18  18. How often do you feel depressed or down?                                                                          481 non-null    int64  \n",
      " 19  19. On a scale of 1 to 5, how frequently does your interest in daily activities fluctuate?                            481 non-null    int64  \n",
      " 20  20. On a scale of 1 to 5, how often do you face issues regarding sleep?                                               481 non-null    int64  \n",
      "dtypes: float64(1), int64(12), object(8)\n",
      "memory usage: 79.0+ KB\n"
     ]
    },
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Timestamp</th>\n",
       "      <th>1. What is your age?</th>\n",
       "      <th>2. Gender</th>\n",
       "      <th>3. Relationship Status</th>\n",
       "      <th>4. Occupation Status</th>\n",
       "      <th>5. What type of organizations are you affiliated with?</th>\n",
       "      <th>6. Do you use social media?</th>\n",
       "      <th>7. What social media platforms do you commonly use?</th>\n",
       "      <th>8. What is the average time you spend on social media every day?</th>\n",
       "      <th>9. How often do you find yourself using Social media without a specific purpose?</th>\n",
       "      <th>...</th>\n",
       "      <th>11. Do you feel restless if you haven't used Social media in a while?</th>\n",
       "      <th>12. On a scale of 1 to 5, how easily distracted are you?</th>\n",
       "      <th>13. On a scale of 1 to 5, how much are you bothered by worries?</th>\n",
       "      <th>14. Do you find it difficult to concentrate on things?</th>\n",
       "      <th>15. On a scale of 1-5, how often do you compare yourself to other successful people through the use of social media?</th>\n",
       "      <th>16. Following the previous question, how do you feel about these comparisons, generally speaking?</th>\n",
       "      <th>17. How often do you look to seek validation from features of social media?</th>\n",
       "      <th>18. How often do you feel depressed or down?</th>\n",
       "      <th>19. On a scale of 1 to 5, how frequently does your interest in daily activities fluctuate?</th>\n",
       "      <th>20. On a scale of 1 to 5, how often do you face issues regarding sleep?</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4/18/2022 19:18:47</td>\n",
       "      <td>21.0</td>\n",
       "      <td>Male</td>\n",
       "      <td>In a relationship</td>\n",
       "      <td>University Student</td>\n",
       "      <td>University</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Facebook, Twitter, Instagram, YouTube, Discord...</td>\n",
       "      <td>Between 2 and 3 hours</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4/18/2022 19:19:28</td>\n",
       "      <td>21.0</td>\n",
       "      <td>Female</td>\n",
       "      <td>Single</td>\n",
       "      <td>University Student</td>\n",
       "      <td>University</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Facebook, Twitter, Instagram, YouTube, Discord...</td>\n",
       "      <td>More than 5 hours</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4/18/2022 19:25:59</td>\n",
       "      <td>21.0</td>\n",
       "      <td>Female</td>\n",
       "      <td>Single</td>\n",
       "      <td>University Student</td>\n",
       "      <td>University</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Facebook, Instagram, YouTube, Pinterest</td>\n",
       "      <td>Between 3 and 4 hours</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4/18/2022 19:29:43</td>\n",
       "      <td>21.0</td>\n",
       "      <td>Female</td>\n",
       "      <td>Single</td>\n",
       "      <td>University Student</td>\n",
       "      <td>University</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Facebook, Instagram</td>\n",
       "      <td>More than 5 hours</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
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       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4/18/2022 19:33:31</td>\n",
       "      <td>21.0</td>\n",
       "      <td>Female</td>\n",
       "      <td>Single</td>\n",
       "      <td>University Student</td>\n",
       "      <td>University</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Facebook, Instagram, YouTube</td>\n",
       "      <td>Between 2 and 3 hours</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
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       "      <td>3</td>\n",
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       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
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       "<p>5 rows × 21 columns</p>\n",
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      "text/plain": [
       "            Timestamp  1. What is your age? 2. Gender 3. Relationship Status  \\\n",
       "0  4/18/2022 19:18:47                  21.0      Male      In a relationship   \n",
       "1  4/18/2022 19:19:28                  21.0    Female                 Single   \n",
       "2  4/18/2022 19:25:59                  21.0    Female                 Single   \n",
       "3  4/18/2022 19:29:43                  21.0    Female                 Single   \n",
       "4  4/18/2022 19:33:31                  21.0    Female                 Single   \n",
       "\n",
       "  4. Occupation Status 5. What type of organizations are you affiliated with?  \\\n",
       "0   University Student                                         University       \n",
       "1   University Student                                         University       \n",
       "2   University Student                                         University       \n",
       "3   University Student                                         University       \n",
       "4   University Student                                         University       \n",
       "\n",
       "  6. Do you use social media?  \\\n",
       "0                         Yes   \n",
       "1                         Yes   \n",
       "2                         Yes   \n",
       "3                         Yes   \n",
       "4                         Yes   \n",
       "\n",
       "  7. What social media platforms do you commonly use?  \\\n",
       "0  Facebook, Twitter, Instagram, YouTube, Discord...    \n",
       "1  Facebook, Twitter, Instagram, YouTube, Discord...    \n",
       "2            Facebook, Instagram, YouTube, Pinterest    \n",
       "3                                Facebook, Instagram    \n",
       "4                       Facebook, Instagram, YouTube    \n",
       "\n",
       "  8. What is the average time you spend on social media every day?  \\\n",
       "0                              Between 2 and 3 hours                 \n",
       "1                                  More than 5 hours                 \n",
       "2                              Between 3 and 4 hours                 \n",
       "3                                  More than 5 hours                 \n",
       "4                              Between 2 and 3 hours                 \n",
       "\n",
       "   9. How often do you find yourself using Social media without a specific purpose?  \\\n",
       "0                                                  5                                  \n",
       "1                                                  4                                  \n",
       "2                                                  3                                  \n",
       "3                                                  4                                  \n",
       "4                                                  3                                  \n",
       "\n",
       "   ...  11. Do you feel restless if you haven't used Social media in a while?  \\\n",
       "0  ...                                                  2                       \n",
       "1  ...                                                  2                       \n",
       "2  ...                                                  1                       \n",
       "3  ...                                                  1                       \n",
       "4  ...                                                  4                       \n",
       "\n",
       "   12. On a scale of 1 to 5, how easily distracted are you?  \\\n",
       "0                                                  5          \n",
       "1                                                  4          \n",
       "2                                                  2          \n",
       "3                                                  3          \n",
       "4                                                  4          \n",
       "\n",
       "   13. On a scale of 1 to 5, how much are you bothered by worries?  \\\n",
       "0                                                  2                 \n",
       "1                                                  5                 \n",
       "2                                                  5                 \n",
       "3                                                  5                 \n",
       "4                                                  5                 \n",
       "\n",
       "   14. Do you find it difficult to concentrate on things?  \\\n",
       "0                                                  5        \n",
       "1                                                  4        \n",
       "2                                                  4        \n",
       "3                                                  3        \n",
       "4                                                  5        \n",
       "\n",
       "   15. On a scale of 1-5, how often do you compare yourself to other successful people through the use of social media?  \\\n",
       "0                                                  2                                                                      \n",
       "1                                                  5                                                                      \n",
       "2                                                  3                                                                      \n",
       "3                                                  5                                                                      \n",
       "4                                                  3                                                                      \n",
       "\n",
       "   16. Following the previous question, how do you feel about these comparisons, generally speaking?  \\\n",
       "0                                                  3                                                   \n",
       "1                                                  1                                                   \n",
       "2                                                  3                                                   \n",
       "3                                                  1                                                   \n",
       "4                                                  3                                                   \n",
       "\n",
       "   17. How often do you look to seek validation from features of social media?  \\\n",
       "0                                                  2                             \n",
       "1                                                  1                             \n",
       "2                                                  1                             \n",
       "3                                                  2                             \n",
       "4                                                  3                             \n",
       "\n",
       "   18. How often do you feel depressed or down?  \\\n",
       "0                                             5   \n",
       "1                                             5   \n",
       "2                                             4   \n",
       "3                                             4   \n",
       "4                                             4   \n",
       "\n",
       "   19. On a scale of 1 to 5, how frequently does your interest in daily activities fluctuate?  \\\n",
       "0                                                  4                                            \n",
       "1                                                  4                                            \n",
       "2                                                  2                                            \n",
       "3                                                  3                                            \n",
       "4                                                  4                                            \n",
       "\n",
       "   20. On a scale of 1 to 5, how often do you face issues regarding sleep?  \n",
       "0                                                  5                        \n",
       "1                                                  5                        \n",
       "2                                                  5                        \n",
       "3                                                  2                        \n",
       "4                                                  1                        \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from scipy.cluster.hierarchy import dendrogram, linkage\n",
    "from matplotlib import pyplot as plt\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn import preprocessing\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "\n",
    "df = pd.read_csv('/Users/Sohan/FinalProject/smmh.csv')\n",
    "df.info()\n",
    "df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "9aa010a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method NDFrame.describe of                Timestamp  1. What is your age? 2. Gender  \\\n",
       "0     4/18/2022 19:18:47                  21.0      Male   \n",
       "1     4/18/2022 19:19:28                  21.0    Female   \n",
       "2     4/18/2022 19:25:59                  21.0    Female   \n",
       "3     4/18/2022 19:29:43                  21.0    Female   \n",
       "4     4/18/2022 19:33:31                  21.0    Female   \n",
       "..                   ...                   ...       ...   \n",
       "476   5/21/2022 23:38:28                  24.0      Male   \n",
       "477    5/22/2022 0:01:05                  26.0    Female   \n",
       "478   5/22/2022 10:29:21                  29.0    Female   \n",
       "479   7/14/2022 19:33:47                  21.0      Male   \n",
       "480  11/12/2022 13:16:50                  53.0      Male   \n",
       "\n",
       "    3. Relationship Status 4. Occupation Status  \\\n",
       "0        In a relationship   University Student   \n",
       "1                   Single   University Student   \n",
       "2                   Single   University Student   \n",
       "3                   Single   University Student   \n",
       "4                   Single   University Student   \n",
       "..                     ...                  ...   \n",
       "476                 Single      Salaried Worker   \n",
       "477                Married      Salaried Worker   \n",
       "478                Married      Salaried Worker   \n",
       "479                 Single   University Student   \n",
       "480                Married      Salaried Worker   \n",
       "\n",
       "    5. What type of organizations are you affiliated with?  \\\n",
       "0                                           University       \n",
       "1                                           University       \n",
       "2                                           University       \n",
       "3                                           University       \n",
       "4                                           University       \n",
       "..                                                 ...       \n",
       "476                                University, Private       \n",
       "477                                         University       \n",
       "478                                         University       \n",
       "479                                         University       \n",
       "480                                            Private       \n",
       "\n",
       "    6. Do you use social media?  \\\n",
       "0                           Yes   \n",
       "1                           Yes   \n",
       "2                           Yes   \n",
       "3                           Yes   \n",
       "4                           Yes   \n",
       "..                          ...   \n",
       "476                         Yes   \n",
       "477                         Yes   \n",
       "478                         Yes   \n",
       "479                         Yes   \n",
       "480                         Yes   \n",
       "\n",
       "    7. What social media platforms do you commonly use?  \\\n",
       "0    Facebook, Twitter, Instagram, YouTube, Discord...    \n",
       "1    Facebook, Twitter, Instagram, YouTube, Discord...    \n",
       "2              Facebook, Instagram, YouTube, Pinterest    \n",
       "3                                  Facebook, Instagram    \n",
       "4                         Facebook, Instagram, YouTube    \n",
       "..                                                 ...    \n",
       "476                       Facebook, Instagram, YouTube    \n",
       "477                                  Facebook, YouTube    \n",
       "478                                  Facebook, YouTube    \n",
       "479  Facebook, Twitter, Instagram, YouTube, Discord...    \n",
       "480                                  Facebook, YouTube    \n",
       "\n",
       "    8. What is the average time you spend on social media every day?  \\\n",
       "0                                Between 2 and 3 hours                 \n",
       "1                                    More than 5 hours                 \n",
       "2                                Between 3 and 4 hours                 \n",
       "3                                    More than 5 hours                 \n",
       "4                                Between 2 and 3 hours                 \n",
       "..                                                 ...                 \n",
       "476                              Between 2 and 3 hours                 \n",
       "477                              Between 1 and 2 hours                 \n",
       "478                              Between 2 and 3 hours                 \n",
       "479                              Between 2 and 3 hours                 \n",
       "480                                  Less than an Hour                 \n",
       "\n",
       "     9. How often do you find yourself using Social media without a specific purpose?  \\\n",
       "0                                                    5                                  \n",
       "1                                                    4                                  \n",
       "2                                                    3                                  \n",
       "3                                                    4                                  \n",
       "4                                                    3                                  \n",
       "..                                                 ...                                  \n",
       "476                                                  3                                  \n",
       "477                                                  2                                  \n",
       "478                                                  3                                  \n",
       "479                                                  2                                  \n",
       "480                                                  2                                  \n",
       "\n",
       "     ...  \\\n",
       "0    ...   \n",
       "1    ...   \n",
       "2    ...   \n",
       "3    ...   \n",
       "4    ...   \n",
       "..   ...   \n",
       "476  ...   \n",
       "477  ...   \n",
       "478  ...   \n",
       "479  ...   \n",
       "480  ...   \n",
       "\n",
       "     11. Do you feel restless if you haven't used Social media in a while?  \\\n",
       "0                                                    2                       \n",
       "1                                                    2                       \n",
       "2                                                    1                       \n",
       "3                                                    1                       \n",
       "4                                                    4                       \n",
       "..                                                 ...                       \n",
       "476                                                  3                       \n",
       "477                                                  2                       \n",
       "478                                                  4                       \n",
       "479                                                  2                       \n",
       "480                                                  1                       \n",
       "\n",
       "     12. On a scale of 1 to 5, how easily distracted are you?  \\\n",
       "0                                                    5          \n",
       "1                                                    4          \n",
       "2                                                    2          \n",
       "3                                                    3          \n",
       "4                                                    4          \n",
       "..                                                 ...          \n",
       "476                                                  4          \n",
       "477                                                  3          \n",
       "478                                                  3          \n",
       "479                                                  3          \n",
       "480                                                  3          \n",
       "\n",
       "     13. On a scale of 1 to 5, how much are you bothered by worries?  \\\n",
       "0                                                    2                 \n",
       "1                                                    5                 \n",
       "2                                                    5                 \n",
       "3                                                    5                 \n",
       "4                                                    5                 \n",
       "..                                                 ...                 \n",
       "476                                                  3                 \n",
       "477                                                  4                 \n",
       "478                                                  2                 \n",
       "479                                                  3                 \n",
       "480                                                  1                 \n",
       "\n",
       "     14. Do you find it difficult to concentrate on things?  \\\n",
       "0                                                    5        \n",
       "1                                                    4        \n",
       "2                                                    4        \n",
       "3                                                    3        \n",
       "4                                                    5        \n",
       "..                                                 ...        \n",
       "476                                                  4        \n",
       "477                                                  4        \n",
       "478                                                  3        \n",
       "479                                                  2        \n",
       "480                                                  1        \n",
       "\n",
       "     15. On a scale of 1-5, how often do you compare yourself to other successful people through the use of social media?  \\\n",
       "0                                                    2                                                                      \n",
       "1                                                    5                                                                      \n",
       "2                                                    3                                                                      \n",
       "3                                                    5                                                                      \n",
       "4                                                    3                                                                      \n",
       "..                                                 ...                                                                      \n",
       "476                                                  4                                                                      \n",
       "477                                                  4                                                                      \n",
       "478                                                  3                                                                      \n",
       "479                                                  2                                                                      \n",
       "480                                                  3                                                                      \n",
       "\n",
       "     16. Following the previous question, how do you feel about these comparisons, generally speaking?  \\\n",
       "0                                                    3                                                   \n",
       "1                                                    1                                                   \n",
       "2                                                    3                                                   \n",
       "3                                                    1                                                   \n",
       "4                                                    3                                                   \n",
       "..                                                 ...                                                   \n",
       "476                                                  2                                                   \n",
       "477                                                  2                                                   \n",
       "478                                                  3                                                   \n",
       "479                                                  3                                                   \n",
       "480                                                  3                                                   \n",
       "\n",
       "     17. How often do you look to seek validation from features of social media?  \\\n",
       "0                                                    2                             \n",
       "1                                                    1                             \n",
       "2                                                    1                             \n",
       "3                                                    2                             \n",
       "4                                                    3                             \n",
       "..                                                 ...                             \n",
       "476                                                  4                             \n",
       "477                                                  4                             \n",
       "478                                                  4                             \n",
       "479                                                  4                             \n",
       "480                                                  2                             \n",
       "\n",
       "     18. How often do you feel depressed or down?  \\\n",
       "0                                               5   \n",
       "1                                               5   \n",
       "2                                               4   \n",
       "3                                               4   \n",
       "4                                               4   \n",
       "..                                            ...   \n",
       "476                                             3   \n",
       "477                                             4   \n",
       "478                                             2   \n",
       "479                                             4   \n",
       "480                                             2   \n",
       "\n",
       "     19. On a scale of 1 to 5, how frequently does your interest in daily activities fluctuate?  \\\n",
       "0                                                    4                                            \n",
       "1                                                    4                                            \n",
       "2                                                    2                                            \n",
       "3                                                    3                                            \n",
       "4                                                    4                                            \n",
       "..                                                 ...                                            \n",
       "476                                                  4                                            \n",
       "477                                                  4                                            \n",
       "478                                                  2                                            \n",
       "479                                                  5                                            \n",
       "480                                                  2                                            \n",
       "\n",
       "     20. On a scale of 1 to 5, how often do you face issues regarding sleep?  \n",
       "0                                                    5                        \n",
       "1                                                    5                        \n",
       "2                                                    5                        \n",
       "3                                                    2                        \n",
       "4                                                    1                        \n",
       "..                                                 ...                        \n",
       "476                                                  4                        \n",
       "477                                                  1                        \n",
       "478                                                  2                        \n",
       "479                                                  4                        \n",
       "480                                                  3                        \n",
       "\n",
       "[481 rows x 21 columns]>"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d14ea08c",
   "metadata": {},
   "source": [
    "Data cleaning: In these segments, we are renaming the columns to make them easier to use later in the model. Additonally, we will be manipulating certain other values so that we will not run into other errors when running through the idea. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "87056f06",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.rename(columns = {  '1. What is your age?':'Age',\n",
    "                       '2. Gender':'Sex',\n",
    "                       '3. Relationship Status':'Relationship_Status',\n",
    "                       '4. Occupation Status':'Occupation',\n",
    "                       '5. What type of organizations are you affiliated with?':'Affiliations',\n",
    "                       '6. Do you use social media?':'Social_Media_User?',\n",
    "                       '7. What social media platforms do you commonly use?':'Platforms_Used',\n",
    "                       '8. What is the average time you spend on social media every day?':'Time_Spent',\n",
    "                       '9. How often do you find yourself using Social media without a specific purpose?':'Distraction_1',\n",
    "                       '10. How often do you get distracted by Social media when you are busy doing something?':'Distraction_2',\n",
    "                       \"11. Do you feel restless if you haven't used Social media in a while?\":'Stress_1',\n",
    "                       '12. On a scale of 1 to 5, how easily distracted are you?':'Distraction_3',\n",
    "                       '13. On a scale of 1 to 5, how much are you bothered by worries?':'Stress_2',\n",
    "                       '14. Do you find it difficult to concentrate on things?':'Distraction_4',\n",
    "                       '15. On a scale of 1-5, how often do you compare yourself to other successful people through the use of social media?':'SelfEsteem_1',\n",
    "                       '16. Following the previous question, how do you feel about these comparisons, generally speaking?':'SelfEsteem_2',\n",
    "                       '17. How often do you look to seek validation from features of social media?':'SelfEsteem_3',\n",
    "                       '18. How often do you feel depressed or down?':'Depression_1',\n",
    "                       '19. On a scale of 1 to 5, how frequently does your interest in daily activities fluctuate?':'Depression_2',\n",
    "                       '20. On a scale of 1 to 5, how often do you face issues regarding sleep?':'Depression_3' },inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "1a7bf8dd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Timestamp',\n",
       " 'Age',\n",
       " 'Sex',\n",
       " 'Relationship_Status',\n",
       " 'Occupation',\n",
       " 'Affiliations',\n",
       " 'Social_Media_User?',\n",
       " 'Platforms_Used',\n",
       " 'Time_Spent',\n",
       " 'Distraction_1',\n",
       " 'Distraction_2',\n",
       " 'Stress_1',\n",
       " 'Distraction_3',\n",
       " 'Stress_2',\n",
       " 'Distraction_4',\n",
       " 'SelfEsteem_1',\n",
       " 'SelfEsteem_2',\n",
       " 'SelfEsteem_3',\n",
       " 'Depression_1',\n",
       " 'Depression_2',\n",
       " 'Depression_3']"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "columnNames = list(df.columns)\n",
    "columnNames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "fb0fe553",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 481 entries, 0 to 480\n",
      "Data columns (total 21 columns):\n",
      " #   Column               Non-Null Count  Dtype  \n",
      "---  ------               --------------  -----  \n",
      " 0   Timestamp            481 non-null    object \n",
      " 1   Age                  481 non-null    float64\n",
      " 2   Sex                  481 non-null    object \n",
      " 3   Relationship_Status  481 non-null    object \n",
      " 4   Occupation           481 non-null    object \n",
      " 5   Affiliations         451 non-null    object \n",
      " 6   Social_Media_User?   481 non-null    object \n",
      " 7   Platforms_Used       481 non-null    object \n",
      " 8   Time_Spent           481 non-null    object \n",
      " 9   Distraction_1        481 non-null    int64  \n",
      " 10  Distraction_2        481 non-null    int64  \n",
      " 11  Stress_1             481 non-null    int64  \n",
      " 12  Distraction_3        481 non-null    int64  \n",
      " 13  Stress_2             481 non-null    int64  \n",
      " 14  Distraction_4        481 non-null    int64  \n",
      " 15  SelfEsteem_1         481 non-null    int64  \n",
      " 16  SelfEsteem_2         481 non-null    int64  \n",
      " 17  SelfEsteem_3         481 non-null    int64  \n",
      " 18  Depression_1         481 non-null    int64  \n",
      " 19  Depression_2         481 non-null    int64  \n",
      " 20  Depression_3         481 non-null    int64  \n",
      "dtypes: float64(1), int64(12), object(8)\n",
      "memory usage: 79.0+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c1f15133",
   "metadata": {},
   "source": [
    "There are no missing data values in this set. However, age is shown is as a float instead of a integer. We will now change this."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "10abcd7c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 481 entries, 0 to 480\n",
      "Data columns (total 21 columns):\n",
      " #   Column               Non-Null Count  Dtype \n",
      "---  ------               --------------  ----- \n",
      " 0   Timestamp            481 non-null    object\n",
      " 1   Age                  481 non-null    int64 \n",
      " 2   Sex                  481 non-null    object\n",
      " 3   Relationship_Status  481 non-null    object\n",
      " 4   Occupation           481 non-null    object\n",
      " 5   Affiliations         451 non-null    object\n",
      " 6   Social_Media_User?   481 non-null    object\n",
      " 7   Platforms_Used       481 non-null    object\n",
      " 8   Time_Spent           481 non-null    object\n",
      " 9   Distraction_1        481 non-null    int64 \n",
      " 10  Distraction_2        481 non-null    int64 \n",
      " 11  Stress_1             481 non-null    int64 \n",
      " 12  Distraction_3        481 non-null    int64 \n",
      " 13  Stress_2             481 non-null    int64 \n",
      " 14  Distraction_4        481 non-null    int64 \n",
      " 15  SelfEsteem_1         481 non-null    int64 \n",
      " 16  SelfEsteem_2         481 non-null    int64 \n",
      " 17  SelfEsteem_3         481 non-null    int64 \n",
      " 18  Depression_1         481 non-null    int64 \n",
      " 19  Depression_2         481 non-null    int64 \n",
      " 20  Depression_3         481 non-null    int64 \n",
      "dtypes: int64(13), object(8)\n",
      "memory usage: 79.0+ KB\n"
     ]
    }
   ],
   "source": [
    "df['Age'] = df['Age'].astype('int64')\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3491e556",
   "metadata": {},
   "source": [
    "Now we need to look at Self-Esteem question 2. Initially phrased as follows: \"Following the previous question, how do you feel about these comparisons, generally speaking?\"\n",
    "\n",
    "The challenge arises from the interpretation of scores, which differs slightly for this particular question compared to all others.\n",
    "\n",
    "The score breakdown is as follows:\n",
    "\n",
    "- Very Negative: 1\n",
    "- Slightly Negative: 2\n",
    "- Neutral: 3\n",
    "- Slightly Positive: 4\n",
    "- Very Positive: 5\n",
    "\n",
    "In this study, a higher accumulation of points for a facet of mental well-being indicates a poorer state in that aspect. To maintain this premise, a modification is necessary for the scoring system of this specific question. The revised scoring system is as follows:\n",
    "\n",
    "- Very Negative: 4\n",
    "- Slightly Negative: 2\n",
    "- Neutral: 0\n",
    "- Slightly Positive: 0\n",
    "- Very Positive: 0\n",
    "\n",
    "It's important to note that \"Slightly Positive\" and \"Very Positive\" have been assigned 0 values. The focus here is on measuring the negative impact on mental health, hence consideration is limited to the \"Neutral,\" \"Slightly Negative,\" and \"Very Negative\" options."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "89e560a6",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.loc[df['SelfEsteem_2'] == 3, 'SelfEsteem_2'] = 0\n",
    "df.loc[df['SelfEsteem_2'] == 4, 'SelfEsteem_2'] = 0\n",
    "df.loc[df['SelfEsteem_2'] == 5, 'SelfEsteem_2'] = 0\n",
    "\n",
    "df.loc[df['SelfEsteem_2'] == 1, 'SelfEsteem_2'] = 4\n",
    "df.loc[df['SelfEsteem_2'] == 2, 'SelfEsteem_2'] = 2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de0f0732",
   "metadata": {},
   "source": [
    "Now we will create a new column that will calculate the total amount of points from each category from various aspects of mental health and wellbeing.\n",
    "\n",
    "1. Distractions\n",
    "2. Stress\n",
    "3. Self Esteem\n",
    "4. Depression\n",
    "\n",
    "The max score is 59.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "38736c6e",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Timestamp</th>\n",
       "      <th>Age</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Relationship_Status</th>\n",
       "      <th>Occupation</th>\n",
       "      <th>Affiliations</th>\n",
       "      <th>Social_Media_User?</th>\n",
       "      <th>Platforms_Used</th>\n",
       "      <th>Time_Spent</th>\n",
       "      <th>Distraction_1</th>\n",
       "      <th>...</th>\n",
       "      <th>SelfEsteem_2</th>\n",
       "      <th>SelfEsteem_3</th>\n",
       "      <th>Depression_1</th>\n",
       "      <th>Depression_2</th>\n",
       "      <th>Depression_3</th>\n",
       "      <th>Distraction Total</th>\n",
       "      <th>Stress Total</th>\n",
       "      <th>Self Esteem Total</th>\n",
       "      <th>Depression Total</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4/18/2022 19:18:47</td>\n",
       "      <td>21</td>\n",
       "      <td>Male</td>\n",
       "      <td>In a relationship</td>\n",
       "      <td>University Student</td>\n",
       "      <td>University</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Facebook, Twitter, Instagram, YouTube, Discord...</td>\n",
       "      <td>Between 2 and 3 hours</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>18</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>14</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4/18/2022 19:19:28</td>\n",
       "      <td>21</td>\n",
       "      <td>Female</td>\n",
       "      <td>Single</td>\n",
       "      <td>University Student</td>\n",
       "      <td>University</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Facebook, Twitter, Instagram, YouTube, Discord...</td>\n",
       "      <td>More than 5 hours</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>15</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>14</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4/18/2022 19:25:59</td>\n",
       "      <td>21</td>\n",
       "      <td>Female</td>\n",
       "      <td>Single</td>\n",
       "      <td>University Student</td>\n",
       "      <td>University</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Facebook, Instagram, YouTube, Pinterest</td>\n",
       "      <td>Between 3 and 4 hours</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>11</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4/18/2022 19:29:43</td>\n",
       "      <td>21</td>\n",
       "      <td>Female</td>\n",
       "      <td>Single</td>\n",
       "      <td>University Student</td>\n",
       "      <td>University</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Facebook, Instagram</td>\n",
       "      <td>More than 5 hours</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "      <td>6</td>\n",
       "      <td>11</td>\n",
       "      <td>9</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4/18/2022 19:33:31</td>\n",
       "      <td>21</td>\n",
       "      <td>Female</td>\n",
       "      <td>Single</td>\n",
       "      <td>University Student</td>\n",
       "      <td>University</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Facebook, Instagram, YouTube</td>\n",
       "      <td>Between 2 and 3 hours</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Timestamp  Age     Sex Relationship_Status          Occupation  \\\n",
       "0  4/18/2022 19:18:47   21    Male   In a relationship  University Student   \n",
       "1  4/18/2022 19:19:28   21  Female              Single  University Student   \n",
       "2  4/18/2022 19:25:59   21  Female              Single  University Student   \n",
       "3  4/18/2022 19:29:43   21  Female              Single  University Student   \n",
       "4  4/18/2022 19:33:31   21  Female              Single  University Student   \n",
       "\n",
       "  Affiliations Social_Media_User?  \\\n",
       "0   University                Yes   \n",
       "1   University                Yes   \n",
       "2   University                Yes   \n",
       "3   University                Yes   \n",
       "4   University                Yes   \n",
       "\n",
       "                                      Platforms_Used             Time_Spent  \\\n",
       "0  Facebook, Twitter, Instagram, YouTube, Discord...  Between 2 and 3 hours   \n",
       "1  Facebook, Twitter, Instagram, YouTube, Discord...      More than 5 hours   \n",
       "2            Facebook, Instagram, YouTube, Pinterest  Between 3 and 4 hours   \n",
       "3                                Facebook, Instagram      More than 5 hours   \n",
       "4                       Facebook, Instagram, YouTube  Between 2 and 3 hours   \n",
       "\n",
       "   Distraction_1  ...  SelfEsteem_2  SelfEsteem_3  Depression_1  Depression_2  \\\n",
       "0              5  ...             0             2             5             4   \n",
       "1              4  ...             4             1             5             4   \n",
       "2              3  ...             0             1             4             2   \n",
       "3              4  ...             4             2             4             3   \n",
       "4              3  ...             0             3             4             4   \n",
       "\n",
       "   Depression_3  Distraction Total  Stress Total  Self Esteem Total  \\\n",
       "0             5                 18             4                  4   \n",
       "1             5                 15             7                 10   \n",
       "2             5                 11             6                  4   \n",
       "3             2                 12             6                 11   \n",
       "4             1                 17             9                  6   \n",
       "\n",
       "   Depression Total  Total  \n",
       "0                14     40  \n",
       "1                14     46  \n",
       "2                11     32  \n",
       "3                 9     38  \n",
       "4                 9     41  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "distraction = ['Distraction_1', 'Distraction_2', 'Distraction_3', 'Distraction_4']\n",
    "df['Distraction Total'] = df[distraction].sum(axis=1)\n",
    "\n",
    "Stress = ['Stress_1', 'Stress_2']\n",
    "df['Stress Total'] = df[Stress].sum(axis=1)\n",
    "\n",
    "SelfEsteem = ['SelfEsteem_1', 'SelfEsteem_2','SelfEsteem_3']\n",
    "df['Self Esteem Total'] = df[SelfEsteem].sum(axis=1)\n",
    "\n",
    "Depression = ['Depression_1', 'Depression_2','Depression_3']\n",
    "df['Depression Total'] = df[Depression].sum(axis=1)\n",
    "\n",
    "Total = ['Distraction Total', 'Stress Total','Self Esteem Total','Depression Total']\n",
    "df['Total'] = df[Total].sum(axis=1)\n",
    "\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b918f2bc",
   "metadata": {},
   "source": [
    "Previously, it was established that the \"Total \" indicates magnitude of individual experiencing negative symptoms of mental health. A total  of 59 is the highest an individual can obtain from the questionnaire, which would indicate that the individual is definitely experiencing negative symptoms in some aspect of mental health, based on binary classification.\n",
    "\n",
    "We will introduce a new variable, which is defined as whether we think that the individual is experiencing mental health disease symptoms in some aspect, and whether we are recommending the participant to get a mental health checkup or not.\n",
    "\n",
    "A participant with a score of 3 out of 5 on every question on the questionnaire suggests that they are are experiencing slight to moderate symptoms in every aspect of mental health.\n",
    "\n",
    "Therefore, we assign a rational value of 40 to be the point where we can reliably say that the individual is very likely to be suffering severely from some symptoms, and thus we highly recommend a mental health checkup.\n",
    "\n",
    "An Outcome of 0 means that individual is not confirmed to be experiencing severe mental health symptoms. Therefore we do not think the individual needs to go to get a mental health check up.\n",
    "\n",
    "An Outcome of 1 means that the individual definitely experiencing some severe negative symptoms of mental health. They are recommended to go to get a mental health check up."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "06c2a0c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Timestamp</th>\n",
       "      <th>Age</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Relationship_Status</th>\n",
       "      <th>Occupation</th>\n",
       "      <th>Affiliations</th>\n",
       "      <th>Social_Media_User?</th>\n",
       "      <th>Platforms_Used</th>\n",
       "      <th>Time_Spent</th>\n",
       "      <th>Distraction_1</th>\n",
       "      <th>...</th>\n",
       "      <th>SelfEsteem_3</th>\n",
       "      <th>Depression_1</th>\n",
       "      <th>Depression_2</th>\n",
       "      <th>Depression_3</th>\n",
       "      <th>Distraction Total</th>\n",
       "      <th>Stress Total</th>\n",
       "      <th>Self Esteem Total</th>\n",
       "      <th>Depression Total</th>\n",
       "      <th>Total</th>\n",
       "      <th>New Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4/18/2022 19:18:47</td>\n",
       "      <td>21</td>\n",
       "      <td>Male</td>\n",
       "      <td>In a relationship</td>\n",
       "      <td>University Student</td>\n",
       "      <td>University</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Facebook, Twitter, Instagram, YouTube, Discord...</td>\n",
       "      <td>Between 2 and 3 hours</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>18</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>14</td>\n",
       "      <td>40</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4/18/2022 19:19:28</td>\n",
       "      <td>21</td>\n",
       "      <td>Female</td>\n",
       "      <td>Single</td>\n",
       "      <td>University Student</td>\n",
       "      <td>University</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Facebook, Twitter, Instagram, YouTube, Discord...</td>\n",
       "      <td>More than 5 hours</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>15</td>\n",
       "      <td>7</td>\n",
       "      <td>10</td>\n",
       "      <td>14</td>\n",
       "      <td>46</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4/18/2022 19:25:59</td>\n",
       "      <td>21</td>\n",
       "      <td>Female</td>\n",
       "      <td>Single</td>\n",
       "      <td>University Student</td>\n",
       "      <td>University</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Facebook, Instagram, YouTube, Pinterest</td>\n",
       "      <td>Between 3 and 4 hours</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>11</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>11</td>\n",
       "      <td>32</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4/18/2022 19:29:43</td>\n",
       "      <td>21</td>\n",
       "      <td>Female</td>\n",
       "      <td>Single</td>\n",
       "      <td>University Student</td>\n",
       "      <td>University</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Facebook, Instagram</td>\n",
       "      <td>More than 5 hours</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>12</td>\n",
       "      <td>6</td>\n",
       "      <td>11</td>\n",
       "      <td>9</td>\n",
       "      <td>38</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4/18/2022 19:33:31</td>\n",
       "      <td>21</td>\n",
       "      <td>Female</td>\n",
       "      <td>Single</td>\n",
       "      <td>University Student</td>\n",
       "      <td>University</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Facebook, Instagram, YouTube</td>\n",
       "      <td>Between 2 and 3 hours</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>41</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Timestamp  Age     Sex Relationship_Status          Occupation  \\\n",
       "0  4/18/2022 19:18:47   21    Male   In a relationship  University Student   \n",
       "1  4/18/2022 19:19:28   21  Female              Single  University Student   \n",
       "2  4/18/2022 19:25:59   21  Female              Single  University Student   \n",
       "3  4/18/2022 19:29:43   21  Female              Single  University Student   \n",
       "4  4/18/2022 19:33:31   21  Female              Single  University Student   \n",
       "\n",
       "  Affiliations Social_Media_User?  \\\n",
       "0   University                Yes   \n",
       "1   University                Yes   \n",
       "2   University                Yes   \n",
       "3   University                Yes   \n",
       "4   University                Yes   \n",
       "\n",
       "                                      Platforms_Used             Time_Spent  \\\n",
       "0  Facebook, Twitter, Instagram, YouTube, Discord...  Between 2 and 3 hours   \n",
       "1  Facebook, Twitter, Instagram, YouTube, Discord...      More than 5 hours   \n",
       "2            Facebook, Instagram, YouTube, Pinterest  Between 3 and 4 hours   \n",
       "3                                Facebook, Instagram      More than 5 hours   \n",
       "4                       Facebook, Instagram, YouTube  Between 2 and 3 hours   \n",
       "\n",
       "   Distraction_1  ...  SelfEsteem_3  Depression_1  Depression_2  Depression_3  \\\n",
       "0              5  ...             2             5             4             5   \n",
       "1              4  ...             1             5             4             5   \n",
       "2              3  ...             1             4             2             5   \n",
       "3              4  ...             2             4             3             2   \n",
       "4              3  ...             3             4             4             1   \n",
       "\n",
       "   Distraction Total  Stress Total  Self Esteem Total  Depression Total  \\\n",
       "0                 18             4                  4                14   \n",
       "1                 15             7                 10                14   \n",
       "2                 11             6                  4                11   \n",
       "3                 12             6                 11                 9   \n",
       "4                 17             9                  6                 9   \n",
       "\n",
       "   Total  New Score  \n",
       "0     40          1  \n",
       "1     46          1  \n",
       "2     32          0  \n",
       "3     38          0  \n",
       "4     41          1  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def map_score(score):\n",
    "  if score < 40:\n",
    "    return \"0\"\n",
    "  elif score >= 40:\n",
    "    return \"1\"\n",
    "\n",
    "df['New Score']= df['Total'].apply(lambda score: map_score(score))\n",
    "df['New Score'] = df['New Score'].astype('int64')\n",
    "\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "778b26da",
   "metadata": {},
   "source": [
    "Data Visualization: Now we are going visualize parts of our data since we finished cleaning it. We are first going to compare all four totals with the number of hours spent on social media. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "ecc504b3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Time_Spent', ylabel='Mean Distraction Score'>"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Let's see the mean Distraction score of each Time group of participa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "1a3e560f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Time_Spent', ylabel='Mean Stress Score'>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Let's see the mean stress score of each Time group of participants\n",
    "\n",
    "df.groupby('Time_Spent')['Stress Total'].mean().sort_values(ascending=True).plot.bar(ylabel='Mean Stress Score')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "fb697dc9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Time_Spent', ylabel='Mean Self Esteem Score'>"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Let's see the mean self esteem score of each Time group of participants\n",
    "\n",
    "df.groupby('Time_Spent')['Self Esteem Total'].mean().sort_values(ascending=True).plot.bar(ylabel='Mean Self Esteem Score')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "6f26df2d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Time_Spent', ylabel='Mean Depression Score'>"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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l2SkpKapSpYok6csvv9S9996rRx99VE2aNFGLFi2Mhjtx4oSaNGmihIQEfffdd4qMjNSePXsUERFh9HsAAIBz+V1mQkNDdezYMUVHR2vx4sWe1ZiCBQvq/PnzRsO98sorqlChgqZOnerZVrFiRaPfAQAAnM3vw0ytWrVS79691bt3b+3atUvt2rWTJG3bts140fj666/VqFEj/fOf/1RkZKTq16+vyZMnX/FnMjIylJaW5vUCAAD5l99l5u2331bjxo31xx9/6PPPP1eJEiUkSevWrVPXrl2Nhtu7d6/effddVa1aVYsWLVKfPn3Ur18/ffTRR9n+zMsvv6yiRYt6XhUqVDCaCQAA5C1+H2aKiIi47FOzhw8fbiTQf3O73WrUqJHGjBkjSapfv762bdumd999V927d7/szzz33HMaNGiQ531aWhqFBgCAfMzvlZmFCxcqKSnJ8/7tt99WvXr1dP/99+vEiRNGw0VFRSk2NtZrW82aNZWcnJztz4SEhCg8PNzrBQAA8i+/y8xTTz3lOQ9ly5YtevLJJ9W2bVvt3bvXa0XEhCZNmmjnzp1e23bt2sWN+wAAgIffh5n27dvnWS35/PPPddddd2nMmDFav3692rZtazTcwIEDFR8frzFjxqhz585as2aNJk2apEmTJhn9HgAA4Fx+r8wEBwfr3LlzkqTvv/9erVu3liQVL17c+JVDN954o+bNm6dZs2apdu3aGjlypCZMmKAHHnjA6PcAAADn8ntl5tZbb9WgQYPUpEkTrVmzRnPmzJH01+Gf8uXLGw9411136a677jL+6wIAgPzB75WZiRMnKjAwUHPnztW7776rcuXKSZK+++473XHHHcYDAgAAXInfKzPR0dH69ttvs2z/z3/+YyQQAACAP/xemZGkPXv26IUXXlDXrl119OhRSX9dsr1t2zaj4QAAAK7G7zKTmJioOnXq6Oeff9YXX3yhM2fOSJI2b96soUOHGg8IAABwJX6XmWeffVajRo3SkiVLFBwc7NmekJCgn376yWg4AACAq/G7zGzZskUdO3bMsr1UqVI6duyYkVAAAAC+8rvMRERE6MiRI1m2b9iwwXNlEwAAQG7xu8zcf//9euaZZ5SamiqXyyW3262VK1dq8ODB2T78EQAAIKf4XWZGjx6t6OholStXTmfOnFFsbKyaNWum+Ph4vfDCCzmREQAAIFt+3WfGsiwdPnxYkydP1siRI7V+/Xq53W7Vr19fVatWzamMAAAA2fK7zFStWlXbtm1T1apVVbly5ZzKBQAA4BO/DjMFBASoatWqXLUEAADyDL/PmRk3bpyeeuopbd26NSfyAAAA+MXvZzN169ZN586dU1xcnIKDg1WoUCGv/cePHzcWDgAA4Gr8LjMTJkzIgRgAAADXxu8y06NHj5zIAQAAcE38LjOSlJmZqXnz5mnHjh1yuVyqWbOmOnTooMDAa/rlAAAArpnf7WPr1q3q0KGDUlNTVb16dUnSrl27VKpUKX399deqU6eO8ZAAAADZ8ftqpt69e6tWrVo6ePCg1q9fr/Xr1yslJUV169bVo48+mhMZAQAAsuX3ysymTZu0du1aFStWzLOtWLFiGj16tG688Uaj4QAAAK7G75WZ6tWr6/fff8+y/ejRo6pSpYqRUAAAAL7yu8yMGTNG/fr109y5c3Xw4EEdPHhQc+fO1YABA/TKK68oLS3N8wIAAMhpfh9muuuuuyRJnTt3lsvlkvTXM5sk6e677/a8d7lcyszMNJUTAADgsvwuM8uXL8+JHAAAANfE7zLTvHnznMgBAABwTfw+Z0aSfvzxR3Xr1k3x8fE6dOiQJGnGjBlKSkoyGg4AAOBq/C4zn3/+udq0aaNChQpp/fr1ysjIkCSdPn1aY8aMMR4QAADgSvwuM6NGjdJ7772nyZMnKygoyLM9Pj5e69evNxoOAADgavwuMzt37lSzZs2ybA8PD9fJkydNZAIAAPCZ32UmKipKu3fvzrI9KSlJlStXNhIKAADAV36Xmccee0z9+/fXzz//LJfLpcOHD2vmzJkaPHiw+vbtmxMZAQAAsuX3pdlPP/20Tp06pYSEBKWnp6tZs2YKCQnR4MGD9a9//SsnMgIAAGTL7zIjSaNHj9bzzz+v7du3y+12KzY2VqGhoaazAQAAXNU1lRnLsnTu3DlVqlRJJUqUMJ0JAADAZ36dM5Oamqru3burWLFiKl26tCIjI1WsWDH16tXrsk/SBgAAyGk+r8ykpaUpPj5eZ86cUc+ePVWjRg1ZlqXt27dr1qxZSkpK0vr16zncBAAAcpXPZeaNN95QgQIFtG3bNpUqVcpr3wsvvKAmTZrozTff1JAhQ4yHBAAAyI7Ph5nmz5+vIUOGZCkykhQZGannnntO33zzjdFwAAAAV+Nzmdm1a5fi4+Oz3R8fH6+dO3caCQUAAOArn8tMWlqaIiIist0fERGhtLQ0E5kAAAB85nOZsSxLAQHZf9zlcsmyLCOhAAAAfOXzCcCWZalatWpyuVzZ7gcAAMhtPpeZqVOn5mQOAACAa+JzmenRo0dO5gAAALgmfj81GwAAIC+hzAAAAEejzAAAAEejzAAAAEejzAAAAEfz+Wqmv2VmZmratGlaunSpjh49Krfb7bV/2bJlxsIBAABcjd9lpn///po2bZratWun2rVrZ3sTPQAAgNzgd5mZPXu2Pv30U7Vt2zYn8gAAAPjF73NmgoODVaVKlZzIAgAA4De/y8yTTz6pN954g2cxAQCAPMHvw0xJSUlavny5vvvuO9WqVUtBQUFe+7/44gtj4f7Xyy+/rCFDhqh///6aMGFCjn0PAABwDr/LTEREhDp27JgTWa7ol19+0aRJk1S3bt1c/24AAJB3+V1m7Hh69pkzZ/TAAw9o8uTJGjVqVK5/PwAAyLsccdO8J554Qu3atdPtt99+1c9mZGQoLS3N6wUAAPIvv1dmJGnu3Ln69NNPlZycrAsXLnjtW79+vZFgf5s9e7bWr1+vX375xafPv/zyyxo+fLjRDAAAIO/ye2XmzTffVM+ePRUZGakNGzbopptuUokSJbR3717deeedRsOlpKSof//++vjjj1WwYEGffua5557TqVOnPK+UlBSjmQAAQN7id5l55513NGnSJE2cOFHBwcF6+umntWTJEvXr10+nTp0yGm7dunU6evSoGjZsqMDAQAUGBioxMVFvvvmmAgMDlZmZmeVnQkJCFB4e7vUCAAD5l9+HmZKTkxUfHy9JKlSokE6fPi1JevDBB3XLLbdo4sSJxsLddttt2rJli9e2nj17qkaNGnrmmWdUoEABY98FAACcye8yU6ZMGR07dkwxMTGKiYnR6tWrFRcXp3379hm/kV5YWJhq167tta1IkSIqUaJElu0AAOD/Jr8PM7Vs2VLffPONJOnhhx/WwIED1apVK3Xp0sWW+88AAID/2/xemZk0aZLcbrckqU+fPipevLiSkpJ09913q0+fPsYD/q8ffvghx78DAAA4h99lJiAgQAEB/39Bp3PnzurcubPRUAAAAL66ppvm/fjjj+rWrZsaN26sQ4cOSZJmzJihpKQko+EAAACuxu8y8/nnn6tNmzYqVKiQNmzYoIyMDEnS6dOnNWbMGOMBAQAArsTvMjNq1Ci99957mjx5stcTs+Pj443f/RcAAOBq/C4zO3fuVLNmzbJsDw8P18mTJ01kAgAA8JnfZSYqKkq7d+/Osj0pKUmVK1c2EgoAAMBXfpeZxx57TP3799fPP/8sl8ulw4cPa+bMmRo8eLD69u2bExkBAACy5fel2U8//bROnTqlhIQEpaenq1mzZgoJCdHgwYP1r3/9KycyAgAAZMvvMiNJo0eP1vPPP6/t27fL7XYrNjZWoaGhprMBAABc1TWVGUkqXLiwGjVqZDILAACA33wuM7169fLpcx9++OE1hwEAAPCXz2Vm2rRpiomJUf369Y0/HRsAAOBa+Vxm+vTpo9mzZ2vv3r3q1auXunXrpuLFi+dkNgAAgKvy+dLsd955R0eOHNEzzzyjb775RhUqVFDnzp21aNEiVmoAAIBt/LrPTEhIiLp27aolS5Zo+/btqlWrlvr27auYmBidOXMmpzICAABk65qemi1JLpdLLpdLlmXJ7XabzAQAAOAzv8pMRkaGZs2apVatWql69erasmWLJk6cqOTkZO4zAwAAbOHzCcB9+/bV7NmzFR0drZ49e2r27NkqUaJETmYDAAC4Kp/LzHvvvafo6GhVqlRJiYmJSkxMvOznvvjiC2PhAAAArsbnMtO9e3e5XK6czAIAAOA3v26aBwAAkNdc89VMAAAAeQFlBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOBplBgAAOFqeLjMvv/yybrzxRoWFhSkyMlL33HOPdu7caXcsAACQh+TpMpOYmKgnnnhCq1ev1pIlS3Tp0iW1bt1aZ8+etTsaAADIIwLtDnAlCxcu9Ho/depURUZGat26dWrWrJlNqQAAQF6Sp8vM/zp16pQkqXjx4tl+JiMjQxkZGZ73aWlpOZ4LAADYJ08fZvpvlmVp0KBBuvXWW1W7du1sP/fyyy+raNGinleFChVyMSUAAMhtjikz//rXv7R582bNmjXrip977rnndOrUKc8rJSUllxICAAA7OOIw07///W99/fXXWrFihcqXL3/Fz4aEhCgkJCSXkgEAALvl6TJjWZb+/e9/a968efrhhx9UqVIluyMBAIA8Jk+XmSeeeEKffPKJvvrqK4WFhSk1NVWSVLRoURUqVMjmdAAAIC/I0+fMvPvuuzp16pRatGihqKgoz2vOnDl2RwMAAHlEnl6ZsSzL7ggAACCPy9MrMwAAAFdDmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI5GmQEAAI7miDLzzjvvqFKlSipYsKAaNmyoH3/80e5IAAAgj8jzZWbOnDkaMGCAnn/+eW3YsEFNmzbVnXfeqeTkZLujAQCAPCDPl5nx48fr4YcfVu/evVWzZk1NmDBBFSpU0Lvvvmt3NAAAkAcE2h3gSi5cuKB169bp2Wef9dreunVrrVq16rI/k5GRoYyMDM/7U6dOSZLS0tKMZnNnnDP66+UE07/nnOCEOUrM0hQnzFFilqY4YY4SszTF9Bz//vUsy7r6h6087NChQ5Yka+XKlV7bR48ebVWrVu2yPzN06FBLEi9evHjx4sUrH7xSUlKu2hfy9MrM31wul9d7y7KybPvbc889p0GDBnneu91uHT9+XCVKlMj2Z+yWlpamChUqKCUlReHh4XbHcTRmaQ6zNIM5msMszXHCLC3L0unTp1W2bNmrfjZPl5mSJUuqQIECSk1N9dp+9OhRlS5d+rI/ExISopCQEK9tERERORXRqPDw8Dz7L5XTMEtzmKUZzNEcZmlOXp9l0aJFffpcnj4BODg4WA0bNtSSJUu8ti9ZskTx8fE2pQIAAHlJnl6ZkaRBgwbpwQcfVKNGjdS4cWNNmjRJycnJ6tOnj93RAABAHpDny0yXLl107NgxjRgxQkeOHFHt2rW1YMECxcTE2B3NmJCQEA0dOjTL4TH4j1mawyzNYI7mMEtz8tssXZblyzVPAAAAeVOePmcGAADgaigzAADA0SgzAADA0SgzAADA0SgzuezixYtKSEjQrl277I6SL5w/f17nzv3/Z5YcOHBAEyZM0OLFi21M5UzM0gzmaA6zzDlpaWn68ssvtWPHDrujmHHdD1CC30qWLGnt2rXL7hj5QqtWrax3333XsizLOnHihFW6dGmrfPnyVsGCBa133nnH5nTOwizNYI7mMEtz/vnPf1pvvfWWZVmWde7cOatq1apWUFCQFRgYaM2dO9fmdNePlRkbdO/eXVOmTLE7Rr6wfv16NW3aVJI0d+5clS5dWgcOHNBHH32kN9980+Z0zsIszWCO5jBLc1asWOGZ5bx582RZlk6ePKk333xTo0aNsjnd9cvzN83Ljy5cuKAPPvhAS5YsUaNGjVSkSBGv/ePHj7cpmfOcO3dOYWFhkqTFixerU6dOCggI0C233KIDBw7YnM5ZmKUZzNEcZmnOqVOnVLx4cUnSwoUL9Y9//EOFCxdWu3bt9NRTT9mc7vqxMmODrVu3qkGDBgoPD9euXbu0YcMGz2vjxo12x3OUKlWq6Msvv1RKSooWLVqk1q1bS/rrYaR5+eFpeRGzNIM5msMszalQoYJ++uknnT17VgsXLvTM8sSJEypYsKDN6Qyw+zgXcD0+++wzKygoyAoICLBatWrl2T5mzBjrjjvusDGZ8zBLM5ijOczSnLffftsKDAy0IiIirLi4OCszM9OyLMt68803rRYtWtic7vrxOAM4Xmpqqo4cOaK4uDgFBPy12LhmzRqFh4erRo0aNqdzFmZpBnM0h1mas27dOiUnJ6tVq1YKDQ2VJM2fP18RERFq0qSJzemuD2XGBgkJCXK5XNnuX7ZsWS6mca5Lly6pYMGC2rhxo2rXrm13HEdjlmYwR3OYpTkXL15U9erV9e233yo2NtbuODmCE4BtUK9ePa/3Fy9e1MaNG7V161b16NHDnlAOFBgYqJiYGGVmZtodxfGYpRnM0RxmaU5QUJAyMjKu+Jdop2NlJg8ZNmyYzpw5o9dee83uKI4xdepUffbZZ/r44489Z+rj2jBLM5ijOczSnLFjx+rXX3/VBx98oMDA/LeOQZnJQ3bv3q2bbrpJx48ftzuKY9SvX1+7d+/WxYsXFRMTk+Uy9/Xr19uUzHmYpRnM0RxmaU7Hjh21dOlShYaGqk6dOllm+cUXX9iUzIz8V88c7Keffsofl8jlonvuucfuCPkGszSDOZrDLM2JiIjQP/7xD7tj5BhWZmzQqVMnr/eWZenIkSNau3atXnzxRQ0dOtSmZAAAOA8rMzYoWrSo1/uAgABVr15dI0aM8NzICAAA+IaVGThaQEDAFc/Q50oI3zFLM5ijOczSnEqVKl1xlnv37s3FNOaxMmOjdevWaceOHXK5XIqNjVX9+vXtjuQ48+bN83p/8eJFbdiwQdOnT9fw4cNtSuVMzNIM5mgOszRnwIABXu//nuXChQvzxbOZWJmxwdGjR3Xffffphx9+UEREhCzL0qlTp5SQkKDZs2erVKlSdkd0vE8++URz5szRV199ZXcUx2OWZjBHc5ilOW+//bbWrl2rqVOn2h3lulBmbNClSxft2bNHM2bMUM2aNSVJ27dvV48ePVSlShXNmjXL5oTOt2fPHtWtW1dnz561O4rjMUszmKM5zNKcvXv3ql69ekpLS7M7ynXhMJMNFi5cqO+//95TZCQpNjZWb7/9NicAG3D+/Hm99dZbKl++vN1RHI9ZmsEczWGWZs2dOzdf3JCQMmMDt9utoKCgLNuDgoLkdrttSORcxYoV8zqpzbIsnT59WoULF9bHH39sYzLnYZZmMEdzmKU59evXzzLL1NRU/fHHH3rnnXdsTGYGh5ls0KFDB508eVKzZs1S2bJlJUmHDh3SAw88oGLFimU56Q3Zmz59utf7gIAAlSpVSjfffLOKFStmUypnYpZmMEdzmKU5/3vC9N+zbNGiRb54+jhlxgYpKSnq0KGDtm7dqgoVKsjlcik5OVl16tTRV199xfIpAAB+oMzYaMmSJfr1119lWZZiY2N1++232x3JkU6ePKkpU6Z4Xebeq1evLDcnxNUxSzOYoznM0pzMzEx9+eWXXrNs3769ChQoYHe060aZgaOtXbtWbdq0UaFChXTTTTfJsiytXbtW58+f1+LFi9WgQQO7IzoGszSDOZrDLM3ZvXu32rZtq0OHDql69eqyLEu7du1ShQoVNH/+fN1www12R7wulJlc9Oabb/r0uX79+uVwkvyjadOmqlKliiZPnux5rP2lS5fUu3dv7d27VytWrLA5oXMwSzOYoznM0py2bdvKsizNnDnTc/XSsWPH1K1bNwUEBGj+/Pk2J7w+lJlcVKlSJa/3KSkpioqK8vwhlSSXy+X420rnpkKFCmnDhg1ZTmDbvn27GjVqpHPnztmUzHmYpRnM0RxmaU6RIkW0evVq1alTx2v7pk2b1KRJE505c8amZGZwaXYu2rdvn9f7sLAwJSYmqnLlyjYlcr7w8HAlJydn+Y9dSkqKwsLCbErlTMzSDOZoDrM0JyQkRKdPn86y/cyZMwoODrYhkVkBdgcArkeXLl308MMPa86cOUpJSdHBgwc1e/Zs9e7dW127drU7nqMwSzOYoznM0py77rpLjz76qH7++WdZliXLsrR69Wr16dNH7du3tzve9bNgm9DQUGvPnj12x3C0jIwMq1+/flZwcLAVEBBgBQQEWCEhIdaAAQOs9PR0u+M5CrM0gzmawyzNOXHihNW+fXvL5XJZwcHBnpnec8891smTJ+2Od904Z8ZGYWFh2rRpE4eZDDh37pz27Nkjy7JUpUoVFS5c2O5IjsUszWCO5jBLc3777TevW4JUqVLF7khGUGZy0f8+yKt8+fJKSkpSxYoVvbaHh4fnYioAAJyNMpOLAgICsjwb43LvMzMz7YjnSGfPntXYsWO1dOlSHT16NMuzrbgyzHfM0gzmaA6zNCczM1PTpk3LdpbLli2zKZkZXM2Ui5YvX253hHynd+/eSkxM1IMPPqioqCivcgj/MEszmKM5zNKc/v37a9q0aWrXrp1q166d72bJygwcLSIiQvPnz1eTJk3sjuJ4zNIM5mgOszSnZMmS+uijj9S2bVu7o+QILs2GoxUrVsxzN0tcH2ZpBnM0h1maExwcnG9O9r0cygwcbeTIkXrppZe4E6gBzNIM5mgOszTnySef1BtvvKH8ejCGw0xwnPr163sd7929e7csy1LFihUVFBTk9dn169fndjxHYZZmMEdzmKU5nTp18nq/bNkyFS9eXLVq1coyyy+++CI3oxnHCcBwnHvuucfuCPkGszSDOZrDLM0pWrSo1/uOHTvalCTnsTIDAAAcjZUZG3DvBAAAzKHM2IB7JwAAYA6HmWzAvRMAADCHS7NtwL0TAAAwhzJjA+6dAPzfweI3kPM4zGSD+vXrex5nz70Trt358+e1bt06FS9eXLGxsV770tPT9emnn6p79+42pXOWHTt2aPXq1WrcuLFq1KihX3/9VW+88YYyMjLUrVs3tWzZ0u6IjhUcHKxNmzapZs2adkdxrBMnTmj69On67bffFBUVpR49eqhChQp2x3Kkixcvav78+Z5ZduzYUUWKFLE71nWjzNhg+PDhV9w/dOjQXEriXLt27VLr1q2VnJwsl8ulpk2batasWYqKipIk/f777ypbtixPIPfBwoUL1aFDB4WGhurcuXOaN2+eunfvrri4OFmWpcTERC1atIhCcxWDBg267PY33nhD3bp1U4kSJSRJ48ePz81YjlS2bFlt2bJFJUqU0L59+xQfHy9JqlOnjnbs2KHTp09r9erVqlGjhs1J8774+HgtWLBAERER+uOPP3Tbbbdp586diomJUUpKiiIjI7Vq1SqVK1fO7qjXhTIDR+rYsaMuXbqkqVOn6uTJkxo0aJC2bt2qH374QdHR0ZQZP8THx6tly5YaNWqUZs+erb59++rxxx/X6NGjJUnPP/+8fvnlFy1evNjmpHlbQECA4uLiFBER4bU9MTFRjRo1UpEiReRyubRs2TJ7AjpIQECAUlNTFRkZqa5duyo1NVXz589X4cKFlZGRoXvvvVcFCxbUZ599ZnfUPO+/Z/noo4/ql19+0XfffacyZcro2LFjat++vWrUqKEpU6bYHfX6WIADRUZGWps3b/ba1rdvXys6Otras2ePlZqaagUEBNiUzlnCw8Ot3377zbIsy8rMzLQCAwOtdevWefZv2bLFKl26tF3xHGPMmDFWpUqVrKVLl3ptDwwMtLZt22ZTKmdyuVzW77//blmWddmZrl692ipfvrwd0Rznv2dZrVo169tvv/Xav3z5cqtixYp2RDOKE4BtkJmZqddee0033XSTypQpo+LFi3u9cHXnz59XYKD3bZLefvtttW/fXs2bN9euXbtsSuZsAQEBKliwoNfqQlhYmE6dOmVfKId47rnnNGfOHD3++OMaPHiwLl68aHckR/v7/lsZGRkqXbq0177SpUvrjz/+sCOWI/09y5MnT6pSpUpe+ypVqqQjR47YEcsoyowNhg8frvHjx6tz5846deqUBg0apE6dOikgIEDDhg2zO54j1KhRQ2vXrs2y/a233lKHDh3Uvn17G1I5U8WKFbV7927P+59++knR0dGe9ykpKZ5zkXBlN954o9atW6c//vhDjRo10pYtW7gp5jW67bbb1KBBA6WlpWX5y0lycrJKlixpUzLneeihh9SpUyddvHhRBw4c8Np35MiRLIdGnYg7ANtg5syZmjx5stq1a6fhw4era9euuuGGG1S3bl2tXr1a/fr1sztintexY0fNmjVLDz74YJZ9EydOlNvt1nvvvWdDMud5/PHHvc4tql27ttf+7777jpN//RAaGqrp06dr9uzZatWqFedtXYP/vQiicOHCXu+/+eYbNW3aNDcjOVaPHj08/9yhQwedOXPGa//nn3+uevXq5XIq8zgB2AZFihTRjh07FB0draioKM2fP18NGjTQ3r17Vb9+fZb0gXzi4MGDWrdunW6//fZ8cfkr8p+zZ8+qQIECKliwoN1RrguHmWxQvnx5zzHKKlWqeK4S+eWXXxQSEmJnNAAGlS9fXh06dKDIIM8qUqSI44uMRJmxRceOHbV06VJJUv/+/fXiiy+qatWq6t69u3r16mVzOgAAnIXDTHnAzz//rJUrV6pKlSqcuAoAgJ8oMwAAwNE4zAQAAByNS7PhOF9//bXPn+Ww3ZUxSzOYoznMMuecPHlSa9as0dGjR+V2u732Of2hvBxmguMEBHgvKLpcLv33v8b/fZMy7vFxZczSDOZoDrPMGd98840eeOABnT17VmFhYV5zdLlcOn78uI3prh+HmeA4brfb81q8eLHq1aun7777TidPntSpU6e0YMECNWjQQAsXLrQ7ap7HLM1gjuYwy5zx5JNPqlevXjp9+rROnjypEydOeF5OLzKSeNCknTIyMqyUlBTrwIEDXi/4rlatWtaPP/6YZfuKFSusGjVq2JDIuZilGczRHGZpTuHCha09e/bYHSPHcM6MDX777Tf16tVLq1at8tpuWZZcLhdLp37Ys2ePihYtmmV70aJFtX///twP5GDM0gzmaA6zNKdNmzZau3atKleubHeUHME5MzZo0qSJAgMD9eyzzyoqKirLg+ji4uJsSuY8zZo1U1BQkD7++GPPwxBTU1P14IMP6sKFC0pMTLQ5oXMwSzOYoznM0pwpU6ZoxIgR6tmzp+rUqaOgoCCv/U4/mZoyY4MiRYpo3bp1qlGjht1RHG/37t3q2LGjdu7c6XnSc3JysqpVq6Yvv/xSVapUsTmhczBLM5ijOczSnP89sfq/5YcjApQZG9x44436z3/+o1tvvdXuKPmCZVlasmSJfv31V1mWpdjYWN1+++1ZVrxwdczSDOZoDrOELygzNli2bJleeOEFjRkz5rLLfeHh4TYlAwDAeSgzNvh7ue9//2bBCcDXZunSpVq6dOllbwT14Ycf2pTKmZilGczRHGZpztmzZ5WYmKjk5GRduHDBa1+/fv1sSmUGVzPZYPny5XZHyDeGDx+uESNGqFGjRpc9mRq+Y5ZmMEdzmKU5GzZsUNu2bXXu3DmdPXtWxYsX159//qnChQsrMjLS8WWGlRk4WlRUlMaNG6cHH3zQ7iiOxyzNYI7mMEtzWrRooWrVqundd99VRESENm3apKCgIHXr1k39+/dXp06d7I54XViZsdG5c+cuu9xXt25dmxI5z4ULFxQfH293jHyBWZrBHM1hluZs3LhR77//vgoUKKACBQooIyNDlStX1rhx49SjRw/HlxkeZ2CDP/74Q3fddZfCwsJUq1Yt1a9f3+sF3/Xu3VuffPKJ3THyBWZpBnM0h1maExQU5DlMV7p0aSUnJ0v66waEf/+zk7EyY4MBAwboxIkTWr16tRISEjRv3jz9/vvvGjVqlF5//XW74zlKenq6Jk2apO+//15169bNcmXY+PHjbUrmPMzSDOZoDrM0p379+lq7dq2qVaumhIQEvfTSS/rzzz81Y8YM1alTx+54141zZmwQFRWlr776SjfddJPCw8M9/4J9/fXXGjdunJKSkuyO6BgJCQnZ7nO5XFq2bFkupnE2ZmkGczSHWZqzdu1anT59WgkJCfrjjz/Uo0cPJSUlqUqVKpo6darj7zxPmbFBeHi4Nm/erIoVK6pixYqaOXOmmjRpon379qlWrVo6d+6c3REBAHAMzpmxQfXq1bVz505JUr169fT+++/r0KFDeu+99zzPHwEAAL5hZcYGM2fO1MWLF/XQQw9pw4YNatOmjY4dO6bg4GBNmzZNXbp0sTuio/zyyy/67LPPLntl2BdffGFTKmdilmYwR3OYpRm///67Bg8e7LkB4f/+r9/pN2vlBGAbPPDAA55/rl+/vvbv369ff/1V0dHRKlmypI3JnGf27Nnq3r27WrdurSVLlqh169b67bfflJqaqo4dO9odz1GYpRnM0Rxmac5DDz2k5ORkvfjii/nzBoQW4GB16tSxJk6caFmWZYWGhlp79uyx3G639cgjj1gvvfSSzemchVmawRzNYZbmhIaGWhs2bLA7Ro7hMJMNMjMzNW3atGyfN8IZ+r4rUqSItm3bpooVK6pkyZJavny56tSpox07dqhly5Y6cuSI3REdg1mawRzNYZbmxMbGaubMmfn2XmacAGyD/v37q3///srMzFTt2rUVFxfn9YLvihcvrtOnT0uSypUrp61bt0qSTp48yVVhfmKWZjBHc5ilORMmTNCzzz6r/fv32x0lR3DOjA1mz56tTz/9VG3btrU7iuM1bdpUS5YsUZ06ddS5c2f1799fy5Yt05IlS3TbbbfZHc9RmKUZzNEcZnl9ihUr5nVuzNmzZ3XDDTeocOHCWW5AePz48dyOZxSHmWxQtmxZ/fDDD6pWrZrdURzv+PHjSk9PV9myZeV2u/Xaa695bgT14osvqlixYnZHdAxmaQZzNIdZXp/p06f7/NkePXrkYJKcR5mxweuvv669e/dq4sSJ+e+McgAAchllJpf87xNJly1bpuLFi6tWrVpZlvu4dwIAwKQCBQroyJEjioyM9Np+7NgxRUZGcp8Z+KZo0aJe77lHAgAgt2S3bpGRkaHg4OBcTmMeZSaXTJ061e4IAID/Y958801Jfz2Y84MPPlBoaKhnX2ZmplasWKEaNWrYFc8YDjPZoGXLlvriiy8UERHhtT0tLU333HMP95kBABhRqVIlSdKBAwdUvnx5FShQwLMvODhYFStW1IgRI3TzzTfbFdEIyowNAgIClJqamuXY5dGjR1WuXDldvHjRpmQAkHft27dPFSpUUGAgBxX8lZCQoC+++CLfXgHGTfNy0ebNm7V582ZJ0vbt2z3vN2/erA0bNmjKlCkqV66czSnzhz179qhly5Z2x3CMI0eO6OOPP9aCBQuyPMzv7NmzGjFihE3JnGXJkiUaOnSoZ3V1xYoVuvPOO9WyZUsONRtQvXp1/fbbb3bHcKTly5fn2yIjsTKTqwICAjyXYl9u7IUKFdJbb72lXr165Xa0fGfTpk1q0KCB48/Qzw2//PKLWrduLbfbrYsXL6p8+fKaN2+eatWqJemvp+2WLVuWWV7Fxx9/rJ49e6pu3bratWuX3nrrLQ0cOFD33nuvLMvSjBkzNHPmTN177712R83z/vfqz7999dVXatmypcLCwiRx5Sf+P9bqctG+fftkWZYqV66sNWvWqFSpUp59wcHBioyM9Dqeiez9fVJbdg4dOpRLSZxvyJAh6tSpkyZPnqyzZ8/q2WefVfPmzbVkyZJ8+xyXnPD666/r9ddfV79+/bR06VLdfffdGj16tAYOHCjpr2fjTJgwgTLjgy+//FLNmjXznO/x30JDQ7NcHQqwMgNHCggIUFRUVLaXFF64cEGpqamsJvigePHiWr16tdcdqceNG6exY8dq0aJFio6OZmXGB6GhodqyZYvnf8DBwcFau3at6tatK0nauXOnmjRpoj///NPOmI4we/ZsPfXUUxoxYoR69uzp2R4UFKRNmzYpNjbWxnTIi1iZgSPFxMTolVdeUefOnS+7f+PGjWrYsGEup3Ku9PR0r/dPP/20AgIC1Lp1a3344Yc2pXKWoKAgr/ONQkJCvC6DDQ4O1vnz5+2I5jj33XefGjdurG7duunbb7/VBx98kK/P98D14wRgOFLDhg21bt26bPe7XK5sbxIFb7Vr19aqVauybB88eLCGDBmirl272pDKeapUqaJff/3V8/7QoUNeh0n27Nmj8uXL2xHNkWJiYpSYmKjatWsrLi5OixYt4vEv1+nHH39Ut27d1LhxY8+h+BkzZigpKcnmZNePMgNHGjFihP75z39muz82Nlb79u3LxUTO1b17d61cufKy+/5e6o+Ojs7lVM4zZMgQr9WD8PBwr//5rl27NtuVRFxeQECAhg8frlmzZunxxx/nUOd1+Pzzz9WmTRsVKlRIGzZsUEZGhiTp9OnTGjNmjM3prh/nzAAA8rwzZ85oz549qlmzZr64/X5uq1+/vgYOHKju3bsrLCxMmzZtUuXKlbVx40bdcccdSk1NtTvidWFlxgYpKSk6ePCg5/2aNWs0YMAATZo0ycZUAJB3hYaGKi4ujiJzjXbu3KlmzZpl2R4eHq6TJ0/mfiDDKDM2uP/++7V8+XJJUmpqqlq1aqU1a9ZoyJAh3JwMAGBcVFSUdu/enWV7UlKSKleubEMisygzNti6datuuukmSdKnn37qOQHzk08+0bRp0+wNBwDIdx577DH1799fP//8s1wulw4fPqyZM2dq8ODB6tu3r93xrhuXZtvg4sWLCgkJkSR9//33at++vSSpRo0aOnLkiJ3RAAD50NNPP61Tp04pISFB6enpatasmUJCQjR48GD961//sjvedeMEYBvcfPPNSkhIULt27dS6dWutXr1acXFxWr16te69916v82kAALgemZmZSkpKUp06dVSwYEFt375dbrdbsbGxXvdCcjLKjA1++OEHdezYUWlpaerRo4fnpmRDhgzRr7/+yvNG/LR06VItXbpUR48eldvt9trHDd/8wyzNYI7mMEszChYsqB07dlz2ERH5AYeZbNCiRQv9+eefSktL87ovxaOPPqrChQvbmMx5hg8frhEjRqhRo0aKioriplrXgVmawRzNYZbm1KlTR3v37s23ZYaVGRucP39elmV5isuBAwc0b9481axZU23atLE5nbNERUVp3LhxevDBB+2O4njM0gzmaA6zNGfx4sV65plnNHLkSDVs2FBFihTx2h8eHm5TMjNYmbFBhw4d1KlTJ/Xp00cnT57UzTffrKCgIP35558aP368Hn/8cbsjOsaFCxcUHx9vd4x8gVmawRzNYZbm3HHHHZKk9u3be61wWZYll8vl+Lsrc2m2DdavX6+mTZtKkubOnavSpUvrwIED+uijj/Tmm2/anM5ZevfurU8++cTuGPkCszSDOZrDLM1Zvny557Vs2TLP6+/3TsfKjA3OnTunsLAwSX8t/XXq1EkBAQG65ZZbdODAAZvTOUt6eromTZqk77//XnXr1lVQUJDX/vHjx9uUzHmYpRnM0RxmaU7z5s3tjpCjKDM2qFKlir788kt17NhRixYt0sCBAyVJR48edfxxy9y2efNm1atXT9JfNyP8b5ws6B9maQZzNIdZmnXy5ElNmTJFO3bskMvlUmxsrHr16qWiRYvaHe26cQKwDebOnav7779fmZmZatmypZYsWSJJevnll7VixQp99913NicEAOQna9eu9Tw1+6abbpJlWVq7dq3Onz+vxYsXq0GDBnZHvC6UGZukpqbqyJEjiouLU0DAX6curVmzRuHh4apRo4bN6Zxn9+7d2rNnj5o1a6ZChQp5TmqD/5ilGczRHGZ5/Zo2baoqVapo8uTJCgz866DMpUuX1Lt3b+3du1crVqywOeH1oczYiD+g1+/YsWPq3Lmzli9fLpfLpd9++02VK1fWww8/rIiICL3++ut2R3QMZmkGczSHWZpTqFAhbdiwIctflrdv365GjRrp3LlzNiUzg6uZbHDs2DHddtttqlatmtq2bet5HlPv3r315JNP2pzOWQYOHKigoCAlJyd73XCwS5cuWrhwoY3JnIdZmsEczWGW5oSHhys5OTnL9pSUFM8FKU5GmbEBf0DNWbx4sV555RWVL1/ea3vVqlW5MsxPzNIM5mgOszSnS5cuevjhhzVnzhylpKTo4MGDmj17tnr37q2uXbvaHe+6cTWTDRYvXqxFixbxB9SAs2fPXvYREH/++afnyeTwDbM0gzmawyzNee211+RyudS9e3ddunRJkhQUFKTHH39cY8eOtTnd9WNlxgb8ATWnWbNm+uijjzzvXS6X3G63Xn31VSUkJNiYzHmYpRnM0RxmaU5wcLDeeOMNnThxQhs3btSGDRt0/Phx/ec//8kX/9/hBGAbtGvXTg0aNNDIkSMVFhamzZs3KyYmRvfdd5/cbrfmzp1rd0TH2L59u1q0aKGGDRtq2bJlat++vbZt26bjx49r5cqVuuGGG+yO6BjM0gzmaA6zhK8oMzbgD6hZqampeuedd7R+/Xq53W41aNBATzzxhKKiouyO5jjM0gzmaA6zvD69evXy6XMffvhhDifJWZQZm6Smpurdd9/VunXr+AMKAMgRAQEBiomJUf369XWl/93PmzcvF1OZR5nJQ1JSUjR06FDHN+Tc9uOPP+r999/X3r179dlnn6lcuXKaMWOGKlWqpFtvvdXueI7CLM1gjuYwy+vTt29fzZ49W9HR0erVq5e6deum4sWL2x3LOE4AzkOOHz+u6dOn2x3DUT7//HPPLbrXr1+vjIwMSdLp06c1ZswYm9M5C7M0gzmawyyv3zvvvKMjR47omWee0TfffKMKFSqoc+fOWrRo0RVXahzHQp6xceNGKyAgwO4YjlKvXj1r+vTplmVZVmhoqLVnzx7Lsixrw4YNVunSpe2M5jjM0gzmaA6zNG///v3WsGHDrMqVK1sVKlSwTp8+bXckI1iZgaPt3LlTzZo1y7I9PDxcJ0+ezP1ADsYszWCO5jBL81wul1wulyzLktvttjuOMZQZOFpUVJR2796dZXtSUpIqV65sQyLnYpZmMEdzmKUZGRkZmjVrllq1aqXq1atry5YtmjhxopKTkxUaGmp3PCO4A3Au6tSp0xX38zcN/z322GPq37+/PvzwQ7lcLh0+fFg//fSTBg8erJdeesnueI7CLM1gjuYwy+v33ycA9+zZU7Nnz1aJEiXsjmUcVzPlop49e/r0ualTp+Zwkvzl+eef13/+8x+lp6dLkkJCQjR48GCNHDnS5mTOwyzNYI7mMMvrExAQoOjoaNWvX18ulyvbz33xxRe5mMo8ygzyhXPnzmn79u1yu92KjY3NN0undmCWZjBHc5jltXvooYeuWGL+5vS/RFNm4GhLlixRkyZNLvusK/iHWZrBHM1hlvAVZQaOFh4eroyMDDVs2FDNmzdXixYt1KRJE/7mdg2YpRnM0RxmCV9RZuBomZmZWrNmjRITE/XDDz9o1apVSk9PV4MGDdSiRYt88Wj73MIszWCO5jBL+Ioyg3xl69ateu211zRz5ky53W5lZmbaHcmxmKUZzNEcZonsUGbgaDt27PD8rS0xMVGZmZm69dZb1aJFCzVv3lxxcXF2R3QMZmkGczSHWcJXlBk4WkBAgEqVKqUBAwaoffv2qlWrlt2RHItZmsEczWGW8BVlBo42YMAArVixQtu2bVO9evXUokULtWjRQk2bNuUkQT8xSzOYoznMEr6izCBfOHnypH788UclJiYqMTFRW7ZsUb169bR69Wq7ozkOszSDOZrDLHE1PJsJ+YLb7dalS5d04cIFZWRk6OLFi9q/f7/dsRyJWZrBHM1hlrgaVmbgaP369VNiYqK2bdum4sWLq1mzZp6l6Nq1a9sdz1GYpRnM0RxmCV/xoEk42uHDh/XII4/wHzcDmKUZzNEcZglfsTIDR1uxYoXi4+MVGOjdyy9duqRVq1apWbNmNiVzHmZpBnM0h1nCV5QZOFqBAgV05MgRRUZGem0/duyYIiMjuamWH5ilGczRHGYJX3ECMBzNsqzLPhH22LFjKlKkiA2JnItZmsEczWGW8BXnzMCROnXqJElyuVx66KGHFBIS4tmXmZmpzZs3Kz4+3q54jsIszWCO5jBL+IsyA0cqWrSopL/+5hYWFqZChQp59gUHB+uWW27RI488Ylc8R2GWZjBHc5gl/MU5M3C04cOHa/DgwSw5G8AszWCO5jBL+IoyA8e7dOmSfvjhB+3Zs0f333+/wsLCdPjwYYWHh3PLcz8xSzOYoznMEr6gzMDRDhw4oDvuuEPJycnKyMjQrl27VLlyZQ0YMEDp6el677337I7oGMzSDOZoDrOEr7iaCY7Wv39/NWrUSCdOnPA6rt6xY0ctXbrUxmTOwyzNYI7mMEv4ihOA4WhJSUlauXKlgoODvbbHxMTo0KFDNqVyJmZpBnM0h1nCV6zMwNHcbvdlb5x18OBBhYWF2ZDIuZilGczRHGYJX1Fm4GitWrXShAkTPO9dLpfOnDmjoUOHqm3btvYFcyBmaQZzNIdZwlecAAxHO3z4sBISElSgQAH99ttvatSokX777TeVLFlSK1asyHIbdGSPWZrBHM1hlvAVZQaOd/78ec2ePVvr1q2T2+1WgwYN9MADD3idMAjfMEszmKM5zBK+oMwAAABH42omONqxY8dUokQJSVJKSoomT56s8+fP6+6771azZs1sTucszNIM5mgOs4TPLMCBNm/ebMXExFgBAQFW9erVrQ0bNlilS5e2QkNDrfDwcKtAgQLWvHnz7I7pCMzSDOZoDrOEv7iaCY709NNPq06dOkpMTFSLFi101113qW3btjp16pROnDihxx57TGPHjrU7piMwSzOYoznMEn6zu00B16JEiRLWpk2bLMuyrNOnT1sul8v65ZdfPPt37NhhFS1a1KZ0zsIszWCO5jBL+IuVGTjS8ePHVaZMGUlSaGioihQpouLFi3v2FytWTKdPn7YrnqMwSzOYoznMEv6izMCxXC7XFd/Dd8zSDOZoDrOEP7iaCY710EMPKSQkRJKUnp6uPn36qEiRIpKkjIwMO6M5DrM0gzmawyzhD+4zA0fq2bOnT5+bOnVqDidxPmZpBnM0h1nCX5QZAADgaJwzAwAAHI0yAwAAHI0yAwAAHI0yAwAAHI0yAwAAHI0yA+C6DBs2TPXq1bM7BoD/wygzALLlcrmu+HrooYc0ePBgLV261NacZ8+e1TPPPKPKlSurYMGCKlWqlFq0aKFvv/0217O0aNFCAwYMyPXvBf4v4w7AALJ15MgRzz/PmTNHL730knbu3OnZVqhQIYWGhio0NNSOeB59+vTRmjVrNHHiRMXGxurYsWNatWqVjh07ZmsuALmDlRkA2SpTpoznVbRoUblcrizb/vcw00MPPaR77rlHY8aMUenSpRUREaHhw4fr0qVLeuqpp1S8eHGVL19eH374odd3HTp0SF26dFGxYsVUokQJdejQQfv37/cp5zfffKMhQ4aobdu2qlixoho2bKh///vf6tGjh+czFStW1MiRI3X//fcrNDRUZcuW1VtvveX165w6dUqPPvqoIiMjFR4erpYtW2rTpk2e/X//XmfMmKGKFSuqaNGiuu+++zwPPXzooYeUmJioN954w7N65evvAcC1o8wAMG7ZsmU6fPiwVqxYofHjx2vYsGG66667VKxYMf3888/q06eP+vTpo5SUFEnSuXPnlJCQoNDQUK1YsUJJSUkKDQ3VHXfcoQsXLlz1+8qUKaMFCxZc9UnKr776qurWrav169frueee08CBA7VkyRJJkmVZateunVJTU7VgwQKtW7dODRo00G233abjx497fo09e/boyy+/1Lfffqtvv/1WiYmJGjt2rCTpjTfeUOPGjfXII4/oyJEjOnLkiCpUqHCtYwTgKwsAfDB16lSraNGiWbYPHTrUiouL87zv0aOHFRMTY2VmZnq2Va9e3WratKnn/aVLl6wiRYpYs2bNsizLsqZMmWJVr17dcrvdns9kZGRYhQoVshYtWnTVbImJiVb58uWtoKAgq1GjRtaAAQOspKQkr8/ExMRYd9xxh9e2Ll26WHfeeadlWZa1dOlSKzw83EpPT/f6zA033GC9//77nt9r4cKFrbS0NM/+p556yrr55ps975s3b27179//qpkBmMPKDADjatWqpYCA//+fl9KlS6tOnTqe9wUKFFCJEiV09OhRSdK6deu0e/duhYWFec7BKV68uNLT07Vnz56rfl+zZs20d+9eLV26VP/4xz+0bds2NW3aVCNHjvT6XOPGjbO837FjhyfDmTNnVKJECU+G0NBQ7du3zytDxYoVFRYW5nkfFRXl+X0AsAcnAAMwLigoyOu9y+W67Da32y1JcrvdatiwoWbOnJnl1ypVqpTP39m0aVM1bdpUzz77rEaNGqURI0bomWeeUXBwcLY/53K5PBmioqL0ww8/ZPlMRETEFX9vf/8+ANiDMgPAdg0aNNCcOXM8J96aEBsbq0uXLik9Pd1TZlavXu31mdWrV6tGjRqeDKmpqQoMDFTFihWv+XuDg4OVmZl5zT8PwH8cZgJguwceeEAlS5ZUhw4d9OOPP2rfvn1KTExU//79dfDgwav+fIsWLfT+++9r3bp12r9/vxYsWKAhQ4YoISHBqxytXLlS48aN065du/T222/rs88+U//+/SVJt99+uxo3bqx77rlHixYt0v79+7Vq1Sq98MILWrt2rc+/l4oVK+rnn3/W/v379eeff7JqA+QCygwA2xUuXFgrVqxQdHS0OnXqpJo1a6pXr146f/68Tys1bdq00fTp09W6dWvVrFlT//73v9WmTRt9+umnXp978skntW7dOtWvX18jR47U66+/rjZt2kj663DRggUL1KxZM/Xq1UvVqlXTfffdp/3796t06dI+/14GDx6sAgUKKDY2VqVKlVJycrJ/wwDgN5dlWZbdIQAgp1WsWFEDBgzg7rxAPsTKDAAAcDTKDIA8778vlf7f148//mh3PAA24zATgDxv9+7d2e4rV66cChUqlItpAOQ1lBkAAOBoHGYCAACORpkBAACORpkBAACORpkBAACORpkBAACORpkBAACORpkBAACORpkBAACO9v8AYnXGF6XQb/0AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Let's see the mean Depression score of each Time group of participants\n",
    "\n",
    "df.groupby('Time_Spent')['Depression Total'].mean().sort_values(ascending=True).plot.bar(ylabel='Mean Depression Score')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "423e2f19",
   "metadata": {},
   "source": [
    "As we can see, this shows a clear increase over time in all four categories as time spent on social media increases. This matches our hypothesis from the beginning. \n",
    "\n",
    "Our next visualization will be a heatmap that will show correlation from all groups of data from the dataset. This will help illustrate which values may be related to each other.\n",
    "\n",
    "Now we will convert the 'Time Spent\" column from string to integer. This is necessary because heatmaps correlations can be drawn only from numerical values.\n",
    "\n",
    "This is done by assigning the various 'Time Spent' groups to number based strings, and then converting the whole column from object type to int64.\n",
    "\n",
    "'Less than an Hour' = 0\n",
    "\n",
    "'Between 1 and 2 hours' = 1\n",
    "\n",
    "'Between 2 and 3 hours' = 2\n",
    "\n",
    "'Between 3 and 4 hours' = 3\n",
    "\n",
    "'Between 4 and 5 hours' = 4\n",
    "\n",
    "'More than 5 hours' = 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "29fc8865",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/lb/xh4rrgvs6fx0fw4f8jv1nnwr0000gn/T/ipykernel_69931/796332681.py:8: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
      "  df.corr()\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>Time_Spent</th>\n",
       "      <th>Distraction_1</th>\n",
       "      <th>Distraction_2</th>\n",
       "      <th>Stress_1</th>\n",
       "      <th>Distraction_3</th>\n",
       "      <th>Stress_2</th>\n",
       "      <th>Distraction_4</th>\n",
       "      <th>SelfEsteem_1</th>\n",
       "      <th>SelfEsteem_2</th>\n",
       "      <th>SelfEsteem_3</th>\n",
       "      <th>Depression_1</th>\n",
       "      <th>Depression_2</th>\n",
       "      <th>Depression_3</th>\n",
       "      <th>Distraction Total</th>\n",
       "      <th>Stress Total</th>\n",
       "      <th>Self Esteem Total</th>\n",
       "      <th>Depression Total</th>\n",
       "      <th>Total</th>\n",
       "      <th>New Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Age</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.361760</td>\n",
       "      <td>-0.225191</td>\n",
       "      <td>-0.232057</td>\n",
       "      <td>-0.125738</td>\n",
       "      <td>-0.224444</td>\n",
       "      <td>-0.288705</td>\n",
       "      <td>-0.264529</td>\n",
       "      <td>-0.092542</td>\n",
       "      <td>-0.012974</td>\n",
       "      <td>-0.039000</td>\n",
       "      <td>-0.303666</td>\n",
       "      <td>-0.241454</td>\n",
       "      <td>-0.161311</td>\n",
       "      <td>-0.301539</td>\n",
       "      <td>-0.253520</td>\n",
       "      <td>-0.071719</td>\n",
       "      <td>-0.301396</td>\n",
       "      <td>-0.306438</td>\n",
       "      <td>-0.188698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Time_Spent</th>\n",
       "      <td>-0.361760</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.393532</td>\n",
       "      <td>0.380818</td>\n",
       "      <td>0.400058</td>\n",
       "      <td>0.342524</td>\n",
       "      <td>0.326245</td>\n",
       "      <td>0.321685</td>\n",
       "      <td>0.200610</td>\n",
       "      <td>-0.044285</td>\n",
       "      <td>0.109225</td>\n",
       "      <td>0.330489</td>\n",
       "      <td>0.292408</td>\n",
       "      <td>0.174660</td>\n",
       "      <td>0.454950</td>\n",
       "      <td>0.442023</td>\n",
       "      <td>0.128569</td>\n",
       "      <td>0.339560</td>\n",
       "      <td>0.443113</td>\n",
       "      <td>0.342279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Distraction_1</th>\n",
       "      <td>-0.225191</td>\n",
       "      <td>0.393532</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.463353</td>\n",
       "      <td>0.359031</td>\n",
       "      <td>0.365491</td>\n",
       "      <td>0.252082</td>\n",
       "      <td>0.288829</td>\n",
       "      <td>0.148203</td>\n",
       "      <td>-0.073300</td>\n",
       "      <td>0.144519</td>\n",
       "      <td>0.315478</td>\n",
       "      <td>0.359379</td>\n",
       "      <td>0.260496</td>\n",
       "      <td>0.649231</td>\n",
       "      <td>0.371636</td>\n",
       "      <td>0.102528</td>\n",
       "      <td>0.400586</td>\n",
       "      <td>0.521741</td>\n",
       "      <td>0.387532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Distraction_2</th>\n",
       "      <td>-0.232057</td>\n",
       "      <td>0.380818</td>\n",
       "      <td>0.463353</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.513354</td>\n",
       "      <td>0.607419</td>\n",
       "      <td>0.343307</td>\n",
       "      <td>0.527745</td>\n",
       "      <td>0.288504</td>\n",
       "      <td>-0.039471</td>\n",
       "      <td>0.270144</td>\n",
       "      <td>0.379444</td>\n",
       "      <td>0.389132</td>\n",
       "      <td>0.255362</td>\n",
       "      <td>0.836695</td>\n",
       "      <td>0.520835</td>\n",
       "      <td>0.248794</td>\n",
       "      <td>0.437179</td>\n",
       "      <td>0.689977</td>\n",
       "      <td>0.532291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Stress_1</th>\n",
       "      <td>-0.125738</td>\n",
       "      <td>0.400058</td>\n",
       "      <td>0.359031</td>\n",
       "      <td>0.513354</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.514801</td>\n",
       "      <td>0.347036</td>\n",
       "      <td>0.469440</td>\n",
       "      <td>0.320973</td>\n",
       "      <td>-0.071484</td>\n",
       "      <td>0.245925</td>\n",
       "      <td>0.328969</td>\n",
       "      <td>0.384770</td>\n",
       "      <td>0.166601</td>\n",
       "      <td>0.593437</td>\n",
       "      <td>0.816542</td>\n",
       "      <td>0.237581</td>\n",
       "      <td>0.372431</td>\n",
       "      <td>0.629110</td>\n",
       "      <td>0.480991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Distraction_3</th>\n",
       "      <td>-0.224444</td>\n",
       "      <td>0.342524</td>\n",
       "      <td>0.365491</td>\n",
       "      <td>0.607419</td>\n",
       "      <td>0.514801</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.462673</td>\n",
       "      <td>0.662768</td>\n",
       "      <td>0.286120</td>\n",
       "      <td>-0.000193</td>\n",
       "      <td>0.172585</td>\n",
       "      <td>0.407667</td>\n",
       "      <td>0.479993</td>\n",
       "      <td>0.291147</td>\n",
       "      <td>0.840468</td>\n",
       "      <td>0.595182</td>\n",
       "      <td>0.224080</td>\n",
       "      <td>0.502587</td>\n",
       "      <td>0.722904</td>\n",
       "      <td>0.534717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Stress_2</th>\n",
       "      <td>-0.288705</td>\n",
       "      <td>0.326245</td>\n",
       "      <td>0.252082</td>\n",
       "      <td>0.343307</td>\n",
       "      <td>0.347036</td>\n",
       "      <td>0.462673</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.545904</td>\n",
       "      <td>0.414301</td>\n",
       "      <td>0.025925</td>\n",
       "      <td>0.208847</td>\n",
       "      <td>0.588757</td>\n",
       "      <td>0.430348</td>\n",
       "      <td>0.327367</td>\n",
       "      <td>0.516115</td>\n",
       "      <td>0.824778</td>\n",
       "      <td>0.319667</td>\n",
       "      <td>0.575959</td>\n",
       "      <td>0.691219</td>\n",
       "      <td>0.528841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Distraction_4</th>\n",
       "      <td>-0.264529</td>\n",
       "      <td>0.321685</td>\n",
       "      <td>0.288829</td>\n",
       "      <td>0.527745</td>\n",
       "      <td>0.469440</td>\n",
       "      <td>0.662768</td>\n",
       "      <td>0.545904</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.371156</td>\n",
       "      <td>-0.031259</td>\n",
       "      <td>0.242035</td>\n",
       "      <td>0.509794</td>\n",
       "      <td>0.503196</td>\n",
       "      <td>0.354676</td>\n",
       "      <td>0.806598</td>\n",
       "      <td>0.619064</td>\n",
       "      <td>0.282592</td>\n",
       "      <td>0.584886</td>\n",
       "      <td>0.759081</td>\n",
       "      <td>0.554625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SelfEsteem_1</th>\n",
       "      <td>-0.092542</td>\n",
       "      <td>0.200610</td>\n",
       "      <td>0.148203</td>\n",
       "      <td>0.288504</td>\n",
       "      <td>0.320973</td>\n",
       "      <td>0.286120</td>\n",
       "      <td>0.414301</td>\n",
       "      <td>0.371156</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.174706</td>\n",
       "      <td>0.417328</td>\n",
       "      <td>0.417801</td>\n",
       "      <td>0.374242</td>\n",
       "      <td>0.193716</td>\n",
       "      <td>0.354574</td>\n",
       "      <td>0.448542</td>\n",
       "      <td>0.791269</td>\n",
       "      <td>0.418397</td>\n",
       "      <td>0.626037</td>\n",
       "      <td>0.523482</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SelfEsteem_2</th>\n",
       "      <td>-0.012974</td>\n",
       "      <td>-0.044285</td>\n",
       "      <td>-0.073300</td>\n",
       "      <td>-0.039471</td>\n",
       "      <td>-0.071484</td>\n",
       "      <td>-0.000193</td>\n",
       "      <td>0.025925</td>\n",
       "      <td>-0.031259</td>\n",
       "      <td>0.174706</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.059882</td>\n",
       "      <td>-0.000205</td>\n",
       "      <td>-0.018440</td>\n",
       "      <td>-0.028299</td>\n",
       "      <td>-0.044930</td>\n",
       "      <td>-0.027141</td>\n",
       "      <td>0.587849</td>\n",
       "      <td>-0.020824</td>\n",
       "      <td>0.142928</td>\n",
       "      <td>0.184559</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SelfEsteem_3</th>\n",
       "      <td>-0.039000</td>\n",
       "      <td>0.109225</td>\n",
       "      <td>0.144519</td>\n",
       "      <td>0.270144</td>\n",
       "      <td>0.245925</td>\n",
       "      <td>0.172585</td>\n",
       "      <td>0.208847</td>\n",
       "      <td>0.242035</td>\n",
       "      <td>0.417328</td>\n",
       "      <td>-0.059882</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.272125</td>\n",
       "      <td>0.278575</td>\n",
       "      <td>0.128898</td>\n",
       "      <td>0.268411</td>\n",
       "      <td>0.276828</td>\n",
       "      <td>0.634105</td>\n",
       "      <td>0.287855</td>\n",
       "      <td>0.460550</td>\n",
       "      <td>0.345309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Depression_1</th>\n",
       "      <td>-0.303666</td>\n",
       "      <td>0.330489</td>\n",
       "      <td>0.315478</td>\n",
       "      <td>0.379444</td>\n",
       "      <td>0.328969</td>\n",
       "      <td>0.407667</td>\n",
       "      <td>0.588757</td>\n",
       "      <td>0.509794</td>\n",
       "      <td>0.417801</td>\n",
       "      <td>-0.000205</td>\n",
       "      <td>0.272125</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.494976</td>\n",
       "      <td>0.374726</td>\n",
       "      <td>0.517190</td>\n",
       "      <td>0.560748</td>\n",
       "      <td>0.336350</td>\n",
       "      <td>0.797818</td>\n",
       "      <td>0.711736</td>\n",
       "      <td>0.549812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Depression_2</th>\n",
       "      <td>-0.241454</td>\n",
       "      <td>0.292408</td>\n",
       "      <td>0.359379</td>\n",
       "      <td>0.389132</td>\n",
       "      <td>0.384770</td>\n",
       "      <td>0.479993</td>\n",
       "      <td>0.430348</td>\n",
       "      <td>0.503196</td>\n",
       "      <td>0.374242</td>\n",
       "      <td>-0.018440</td>\n",
       "      <td>0.278575</td>\n",
       "      <td>0.494976</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.319247</td>\n",
       "      <td>0.552374</td>\n",
       "      <td>0.496885</td>\n",
       "      <td>0.307441</td>\n",
       "      <td>0.762613</td>\n",
       "      <td>0.691740</td>\n",
       "      <td>0.585355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Depression_3</th>\n",
       "      <td>-0.161311</td>\n",
       "      <td>0.174660</td>\n",
       "      <td>0.260496</td>\n",
       "      <td>0.255362</td>\n",
       "      <td>0.166601</td>\n",
       "      <td>0.291147</td>\n",
       "      <td>0.327367</td>\n",
       "      <td>0.354676</td>\n",
       "      <td>0.193716</td>\n",
       "      <td>-0.028299</td>\n",
       "      <td>0.128898</td>\n",
       "      <td>0.374726</td>\n",
       "      <td>0.319247</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.370687</td>\n",
       "      <td>0.301956</td>\n",
       "      <td>0.142356</td>\n",
       "      <td>0.756710</td>\n",
       "      <td>0.520352</td>\n",
       "      <td>0.407279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Distraction Total</th>\n",
       "      <td>-0.301539</td>\n",
       "      <td>0.454950</td>\n",
       "      <td>0.649231</td>\n",
       "      <td>0.836695</td>\n",
       "      <td>0.593437</td>\n",
       "      <td>0.840468</td>\n",
       "      <td>0.516115</td>\n",
       "      <td>0.806598</td>\n",
       "      <td>0.354574</td>\n",
       "      <td>-0.044930</td>\n",
       "      <td>0.268411</td>\n",
       "      <td>0.517190</td>\n",
       "      <td>0.552374</td>\n",
       "      <td>0.370687</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.675489</td>\n",
       "      <td>0.278873</td>\n",
       "      <td>0.615386</td>\n",
       "      <td>0.862263</td>\n",
       "      <td>0.643356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Stress Total</th>\n",
       "      <td>-0.253520</td>\n",
       "      <td>0.442023</td>\n",
       "      <td>0.371636</td>\n",
       "      <td>0.520835</td>\n",
       "      <td>0.816542</td>\n",
       "      <td>0.595182</td>\n",
       "      <td>0.824778</td>\n",
       "      <td>0.619064</td>\n",
       "      <td>0.448542</td>\n",
       "      <td>-0.027141</td>\n",
       "      <td>0.276828</td>\n",
       "      <td>0.560748</td>\n",
       "      <td>0.496885</td>\n",
       "      <td>0.301956</td>\n",
       "      <td>0.675489</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.340012</td>\n",
       "      <td>0.579075</td>\n",
       "      <td>0.804781</td>\n",
       "      <td>0.615526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Self Esteem Total</th>\n",
       "      <td>-0.071719</td>\n",
       "      <td>0.128569</td>\n",
       "      <td>0.102528</td>\n",
       "      <td>0.248794</td>\n",
       "      <td>0.237581</td>\n",
       "      <td>0.224080</td>\n",
       "      <td>0.319667</td>\n",
       "      <td>0.282592</td>\n",
       "      <td>0.791269</td>\n",
       "      <td>0.587849</td>\n",
       "      <td>0.634105</td>\n",
       "      <td>0.336350</td>\n",
       "      <td>0.307441</td>\n",
       "      <td>0.142356</td>\n",
       "      <td>0.278873</td>\n",
       "      <td>0.340012</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.332931</td>\n",
       "      <td>0.603186</td>\n",
       "      <td>0.520563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Depression Total</th>\n",
       "      <td>-0.301396</td>\n",
       "      <td>0.339560</td>\n",
       "      <td>0.400586</td>\n",
       "      <td>0.437179</td>\n",
       "      <td>0.372431</td>\n",
       "      <td>0.502587</td>\n",
       "      <td>0.575959</td>\n",
       "      <td>0.584886</td>\n",
       "      <td>0.418397</td>\n",
       "      <td>-0.020824</td>\n",
       "      <td>0.287855</td>\n",
       "      <td>0.797818</td>\n",
       "      <td>0.762613</td>\n",
       "      <td>0.756710</td>\n",
       "      <td>0.615386</td>\n",
       "      <td>0.579075</td>\n",
       "      <td>0.332931</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.824045</td>\n",
       "      <td>0.659655</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Total</th>\n",
       "      <td>-0.306438</td>\n",
       "      <td>0.443113</td>\n",
       "      <td>0.521741</td>\n",
       "      <td>0.689977</td>\n",
       "      <td>0.629110</td>\n",
       "      <td>0.722904</td>\n",
       "      <td>0.691219</td>\n",
       "      <td>0.759081</td>\n",
       "      <td>0.626037</td>\n",
       "      <td>0.142928</td>\n",
       "      <td>0.460550</td>\n",
       "      <td>0.711736</td>\n",
       "      <td>0.691740</td>\n",
       "      <td>0.520352</td>\n",
       "      <td>0.862263</td>\n",
       "      <td>0.804781</td>\n",
       "      <td>0.603186</td>\n",
       "      <td>0.824045</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.785546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Score</th>\n",
       "      <td>-0.188698</td>\n",
       "      <td>0.342279</td>\n",
       "      <td>0.387532</td>\n",
       "      <td>0.532291</td>\n",
       "      <td>0.480991</td>\n",
       "      <td>0.534717</td>\n",
       "      <td>0.528841</td>\n",
       "      <td>0.554625</td>\n",
       "      <td>0.523482</td>\n",
       "      <td>0.184559</td>\n",
       "      <td>0.345309</td>\n",
       "      <td>0.549812</td>\n",
       "      <td>0.585355</td>\n",
       "      <td>0.407279</td>\n",
       "      <td>0.643356</td>\n",
       "      <td>0.615526</td>\n",
       "      <td>0.520563</td>\n",
       "      <td>0.659655</td>\n",
       "      <td>0.785546</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Age  Time_Spent  Distraction_1  Distraction_2  \\\n",
       "Age                1.000000   -0.361760      -0.225191      -0.232057   \n",
       "Time_Spent        -0.361760    1.000000       0.393532       0.380818   \n",
       "Distraction_1     -0.225191    0.393532       1.000000       0.463353   \n",
       "Distraction_2     -0.232057    0.380818       0.463353       1.000000   \n",
       "Stress_1          -0.125738    0.400058       0.359031       0.513354   \n",
       "Distraction_3     -0.224444    0.342524       0.365491       0.607419   \n",
       "Stress_2          -0.288705    0.326245       0.252082       0.343307   \n",
       "Distraction_4     -0.264529    0.321685       0.288829       0.527745   \n",
       "SelfEsteem_1      -0.092542    0.200610       0.148203       0.288504   \n",
       "SelfEsteem_2      -0.012974   -0.044285      -0.073300      -0.039471   \n",
       "SelfEsteem_3      -0.039000    0.109225       0.144519       0.270144   \n",
       "Depression_1      -0.303666    0.330489       0.315478       0.379444   \n",
       "Depression_2      -0.241454    0.292408       0.359379       0.389132   \n",
       "Depression_3      -0.161311    0.174660       0.260496       0.255362   \n",
       "Distraction Total -0.301539    0.454950       0.649231       0.836695   \n",
       "Stress Total      -0.253520    0.442023       0.371636       0.520835   \n",
       "Self Esteem Total -0.071719    0.128569       0.102528       0.248794   \n",
       "Depression Total  -0.301396    0.339560       0.400586       0.437179   \n",
       "Total             -0.306438    0.443113       0.521741       0.689977   \n",
       "New Score         -0.188698    0.342279       0.387532       0.532291   \n",
       "\n",
       "                   Stress_1  Distraction_3  Stress_2  Distraction_4  \\\n",
       "Age               -0.125738      -0.224444 -0.288705      -0.264529   \n",
       "Time_Spent         0.400058       0.342524  0.326245       0.321685   \n",
       "Distraction_1      0.359031       0.365491  0.252082       0.288829   \n",
       "Distraction_2      0.513354       0.607419  0.343307       0.527745   \n",
       "Stress_1           1.000000       0.514801  0.347036       0.469440   \n",
       "Distraction_3      0.514801       1.000000  0.462673       0.662768   \n",
       "Stress_2           0.347036       0.462673  1.000000       0.545904   \n",
       "Distraction_4      0.469440       0.662768  0.545904       1.000000   \n",
       "SelfEsteem_1       0.320973       0.286120  0.414301       0.371156   \n",
       "SelfEsteem_2      -0.071484      -0.000193  0.025925      -0.031259   \n",
       "SelfEsteem_3       0.245925       0.172585  0.208847       0.242035   \n",
       "Depression_1       0.328969       0.407667  0.588757       0.509794   \n",
       "Depression_2       0.384770       0.479993  0.430348       0.503196   \n",
       "Depression_3       0.166601       0.291147  0.327367       0.354676   \n",
       "Distraction Total  0.593437       0.840468  0.516115       0.806598   \n",
       "Stress Total       0.816542       0.595182  0.824778       0.619064   \n",
       "Self Esteem Total  0.237581       0.224080  0.319667       0.282592   \n",
       "Depression Total   0.372431       0.502587  0.575959       0.584886   \n",
       "Total              0.629110       0.722904  0.691219       0.759081   \n",
       "New Score          0.480991       0.534717  0.528841       0.554625   \n",
       "\n",
       "                   SelfEsteem_1  SelfEsteem_2  SelfEsteem_3  Depression_1  \\\n",
       "Age                   -0.092542     -0.012974     -0.039000     -0.303666   \n",
       "Time_Spent             0.200610     -0.044285      0.109225      0.330489   \n",
       "Distraction_1          0.148203     -0.073300      0.144519      0.315478   \n",
       "Distraction_2          0.288504     -0.039471      0.270144      0.379444   \n",
       "Stress_1               0.320973     -0.071484      0.245925      0.328969   \n",
       "Distraction_3          0.286120     -0.000193      0.172585      0.407667   \n",
       "Stress_2               0.414301      0.025925      0.208847      0.588757   \n",
       "Distraction_4          0.371156     -0.031259      0.242035      0.509794   \n",
       "SelfEsteem_1           1.000000      0.174706      0.417328      0.417801   \n",
       "SelfEsteem_2           0.174706      1.000000     -0.059882     -0.000205   \n",
       "SelfEsteem_3           0.417328     -0.059882      1.000000      0.272125   \n",
       "Depression_1           0.417801     -0.000205      0.272125      1.000000   \n",
       "Depression_2           0.374242     -0.018440      0.278575      0.494976   \n",
       "Depression_3           0.193716     -0.028299      0.128898      0.374726   \n",
       "Distraction Total      0.354574     -0.044930      0.268411      0.517190   \n",
       "Stress Total           0.448542     -0.027141      0.276828      0.560748   \n",
       "Self Esteem Total      0.791269      0.587849      0.634105      0.336350   \n",
       "Depression Total       0.418397     -0.020824      0.287855      0.797818   \n",
       "Total                  0.626037      0.142928      0.460550      0.711736   \n",
       "New Score              0.523482      0.184559      0.345309      0.549812   \n",
       "\n",
       "                   Depression_2  Depression_3  Distraction Total  \\\n",
       "Age                   -0.241454     -0.161311          -0.301539   \n",
       "Time_Spent             0.292408      0.174660           0.454950   \n",
       "Distraction_1          0.359379      0.260496           0.649231   \n",
       "Distraction_2          0.389132      0.255362           0.836695   \n",
       "Stress_1               0.384770      0.166601           0.593437   \n",
       "Distraction_3          0.479993      0.291147           0.840468   \n",
       "Stress_2               0.430348      0.327367           0.516115   \n",
       "Distraction_4          0.503196      0.354676           0.806598   \n",
       "SelfEsteem_1           0.374242      0.193716           0.354574   \n",
       "SelfEsteem_2          -0.018440     -0.028299          -0.044930   \n",
       "SelfEsteem_3           0.278575      0.128898           0.268411   \n",
       "Depression_1           0.494976      0.374726           0.517190   \n",
       "Depression_2           1.000000      0.319247           0.552374   \n",
       "Depression_3           0.319247      1.000000           0.370687   \n",
       "Distraction Total      0.552374      0.370687           1.000000   \n",
       "Stress Total           0.496885      0.301956           0.675489   \n",
       "Self Esteem Total      0.307441      0.142356           0.278873   \n",
       "Depression Total       0.762613      0.756710           0.615386   \n",
       "Total                  0.691740      0.520352           0.862263   \n",
       "New Score              0.585355      0.407279           0.643356   \n",
       "\n",
       "                   Stress Total  Self Esteem Total  Depression Total  \\\n",
       "Age                   -0.253520          -0.071719         -0.301396   \n",
       "Time_Spent             0.442023           0.128569          0.339560   \n",
       "Distraction_1          0.371636           0.102528          0.400586   \n",
       "Distraction_2          0.520835           0.248794          0.437179   \n",
       "Stress_1               0.816542           0.237581          0.372431   \n",
       "Distraction_3          0.595182           0.224080          0.502587   \n",
       "Stress_2               0.824778           0.319667          0.575959   \n",
       "Distraction_4          0.619064           0.282592          0.584886   \n",
       "SelfEsteem_1           0.448542           0.791269          0.418397   \n",
       "SelfEsteem_2          -0.027141           0.587849         -0.020824   \n",
       "SelfEsteem_3           0.276828           0.634105          0.287855   \n",
       "Depression_1           0.560748           0.336350          0.797818   \n",
       "Depression_2           0.496885           0.307441          0.762613   \n",
       "Depression_3           0.301956           0.142356          0.756710   \n",
       "Distraction Total      0.675489           0.278873          0.615386   \n",
       "Stress Total           1.000000           0.340012          0.579075   \n",
       "Self Esteem Total      0.340012           1.000000          0.332931   \n",
       "Depression Total       0.579075           0.332931          1.000000   \n",
       "Total                  0.804781           0.603186          0.824045   \n",
       "New Score              0.615526           0.520563          0.659655   \n",
       "\n",
       "                      Total  New Score  \n",
       "Age               -0.306438  -0.188698  \n",
       "Time_Spent         0.443113   0.342279  \n",
       "Distraction_1      0.521741   0.387532  \n",
       "Distraction_2      0.689977   0.532291  \n",
       "Stress_1           0.629110   0.480991  \n",
       "Distraction_3      0.722904   0.534717  \n",
       "Stress_2           0.691219   0.528841  \n",
       "Distraction_4      0.759081   0.554625  \n",
       "SelfEsteem_1       0.626037   0.523482  \n",
       "SelfEsteem_2       0.142928   0.184559  \n",
       "SelfEsteem_3       0.460550   0.345309  \n",
       "Depression_1       0.711736   0.549812  \n",
       "Depression_2       0.691740   0.585355  \n",
       "Depression_3       0.520352   0.407279  \n",
       "Distraction Total  0.862263   0.643356  \n",
       "Stress Total       0.804781   0.615526  \n",
       "Self Esteem Total  0.603186   0.520563  \n",
       "Depression Total   0.824045   0.659655  \n",
       "Total              1.000000   0.785546  \n",
       "New Score          0.785546   1.000000  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df['Time_Spent'] == 'Less than an Hour', 'Time_Spent'] = 0\n",
    "df.loc[df['Time_Spent'] == 'Between 1 and 2 hours', 'Time_Spent'] = 1\n",
    "df.loc[df['Time_Spent'] == 'Between 2 and 3 hours', 'Time_Spent'] = 2\n",
    "df.loc[df['Time_Spent'] == 'Between 3 and 4 hours', 'Time_Spent'] = 3\n",
    "df.loc[df['Time_Spent'] == 'Between 4 and 5 hours', 'Time_Spent'] = 4\n",
    "df.loc[df['Time_Spent'] == 'More than 5 hours', 'Time_Spent'] = 5\n",
    "df['Time_Spent'] = df['Time_Spent'].astype('int64')\n",
    "df.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "b4ceb45c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/lb/xh4rrgvs6fx0fw4f8jv1nnwr0000gn/T/ipykernel_69931/1688253363.py:2: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
      "  corr = df.corr()\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(figsize=(20, 10))\n",
    "corr = df.corr()\n",
    "sns.heatmap(corr, ax=ax, annot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7869da06",
   "metadata": {},
   "source": [
    "MODELS: Now for the machine learning component. We are going to run two seperate KNN Classifiers comparing various sets of data. This will help show if time spent is truly related to stress total. \n",
    "\n",
    "Following that, we will see if there are other factors that negatively affect depression. Therefore, we are going to look at the correlation betweeen age and depression.\n",
    "\n",
    "Then we are going to run a hiearchical clustering to analyze the four data totals seperately and see how they overall relate to each other. This will also illustrate if our grouping when cleaning the data set was correct. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "bd3f1c38",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Following code details the KNN Classifier Creation\n",
    "\n",
    "X = df[[\"Time_Spent\"]]\n",
    "Y = df[\"Stress Total\"]\n",
    "\n",
    "# Train,test,split data (20% segmented for testing)\n",
    "x_train, x_test, y_train, y_test = train_test_split(X, Y, test_size = 0.2, random_state = 42) \n",
    "\n",
    "# Function used to create the kNN model (default k=5)\n",
    "model = KNeighborsClassifier()\n",
    "\n",
    "# Model incorporating train data\n",
    "model.fit(x_train, y_train)\n",
    "\n",
    "# Predictions\n",
    "predictions = model.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "a3b2f3d3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sklearn's accuracy score for Stress Total: 0.17525773195876287\n"
     ]
    }
   ],
   "source": [
    "# Accuracy Score of Predictions\n",
    "from sklearn.metrics import accuracy_score\n",
    "print(\"sklearn's accuracy score for Stress Total:\", accuracy_score(y_test, predictions))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "9b5935d4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "accuracy score when k=1: 0.16494845360824742\n",
      "accuracy score when k=10: 0.17525773195876287\n",
      "accuracy score when k=100: 0.17525773195876287\n"
     ]
    }
   ],
   "source": [
    "# Model when k=1\n",
    "model1 = KNeighborsClassifier(1)\n",
    "model1.fit(x_train, y_train)\n",
    "predictions1 = model1.predict(x_test)\n",
    "\n",
    "# Model when k=10\n",
    "model10 = KNeighborsClassifier(10)\n",
    "model10.fit(x_train, y_train)\n",
    "predictions10 = model10.predict(x_test)\n",
    "\n",
    "# Model when k=100\n",
    "model100 = KNeighborsClassifier(100)\n",
    "model100.fit(x_train, y_train)\n",
    "predictions100 = model100.predict(x_test)\n",
    "\n",
    "print(\"accuracy score when k=1:\", accuracy_score(y_test, predictions1))\n",
    "print(\"accuracy score when k=10:\", accuracy_score(y_test, predictions10))\n",
    "print(\"accuracy score when k=100:\", accuracy_score(y_test, predictions100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "f2177511",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Determining accurary of model with amount of neighbors between 1 and 100 (inclusive)\n",
    "x1 = list(range(1,101))\n",
    "list_1 = []\n",
    "accuracy = []\n",
    "for k in x1:\n",
    "    model = KNeighborsClassifier(n_neighbors=k)\n",
    "    model.fit(x_train, y_train)\n",
    "    \n",
    "    predictions = model.predict(x_test)\n",
    "    \n",
    "    accuracy.append(accuracy_score(y_test, predictions))\n",
    "    list_1.append(accuracy)\n",
    "    \n",
    "    \n",
    "plt.figure(figsize=(20, 10))\n",
    "plt.plot(accuracy, color='r', label='Accuracy')\n",
    "plt.title('kNN Model Accuracy for K values')\n",
    "plt.xlabel('K Number of Neighbors')\n",
    "plt.ylabel('Accuracy')\n",
    "plt.xticks()\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3fa0b17",
   "metadata": {},
   "source": [
    "The accuracy shows that they may be related but they may not have as much correlation as we anticipated. Now we are moving onto the second classifier."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d8c2852",
   "metadata": {},
   "source": [
    "SECOND KNN CLASSIFIER"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "d311c064",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Making the KNN Classifier\n",
    "X= df[[\"Age\"]]\n",
    "Y= df[\"Depression Total\"]\n",
    "# 20% testing size\n",
    "x_train, x_test, y_train, y_test = train_test_split(X,Y, test_size = 0.2, random_state = 42)\n",
    "\n",
    "model = KNeighborsClassifier()\n",
    "\n",
    "# TODO fit the model using the train data\n",
    "model.fit(x_train, y_train)\n",
    "# TODO store the predictions for the test sets\n",
    "predictions = model.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "aae51f8e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sklearn's accuracy score for Depression Total: 0.061855670103092786\n"
     ]
    }
   ],
   "source": [
    "# TODO find the accuracy score of your predictions\n",
    "from sklearn.metrics import accuracy_score\n",
    "print(\"sklearn's accuracy score for Depression Total:\", accuracy_score(y_test, predictions))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "5021b29f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "accuracy score when k=1: 0.08247422680412371\n",
      "accuracy score when k=10: 0.08247422680412371\n",
      "accuracy score when k=100: 0.1958762886597938\n"
     ]
    }
   ],
   "source": [
    "# Model when k=1\n",
    "model1 = KNeighborsClassifier(1)\n",
    "model1.fit(x_train, y_train)\n",
    "predictions1 = model1.predict(x_test)\n",
    "\n",
    "# Model when k=10\n",
    "model10 = KNeighborsClassifier(10)\n",
    "model10.fit(x_train, y_train)\n",
    "predictions10 = model10.predict(x_test)\n",
    "\n",
    "# Model when k=100\n",
    "model100 = KNeighborsClassifier(100)\n",
    "model100.fit(x_train, y_train)\n",
    "predictions100 = model100.predict(x_test)\n",
    "\n",
    "print(\"accuracy score when k=1:\", accuracy_score(y_test, predictions1))\n",
    "print(\"accuracy score when k=10:\", accuracy_score(y_test, predictions10))\n",
    "print(\"accuracy score when k=100:\", accuracy_score(y_test, predictions100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "9bc55c2f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# accuracy of the model with each value of k from 1-30 inclusive\n",
    "x1 = list(range(1,31))\n",
    "list1 = []\n",
    "accuracy = []\n",
    "for k in x1:\n",
    "    model = KNeighborsClassifier(n_neighbors=k)\n",
    "    model.fit(x_train, y_train)\n",
    "    predictions = model.predict(x_test)\n",
    "    accuracy.append(accuracy_score(y_test, predictions))\n",
    "    list1.append(accuracy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "f9acc207",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot of the accuracy array\n",
    "plt.figure(figsize=(10,6))\n",
    "plt.plot(accuracy, color ='b', label = 'Accuracy')\n",
    "plt.title('K Model Accuracy')\n",
    "plt.xlabel('Neighbors, K')\n",
    "plt.ylabel('Accuracy')\n",
    "plt.xticks()\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f0c0141",
   "metadata": {},
   "source": [
    "This shows that there is some correlation between age and depression. Therefore, there may be other factors that exist outside of social media usage that affect a person's mental health, especially depression. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "047aa574",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#hierarchial clustering\n",
    "from sklearn import datasets\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from scipy.cluster.hierarchy import dendrogram, linkage\n",
    "from matplotlib import pyplot as plt\n",
    "selected_columns = [\"Distraction Total\", \"Stress Total\", \"Self Esteem Total\", \"Depression Total\"]\n",
    "new_df= df[selected_columns]\n",
    "\n",
    "new_df = StandardScaler().fit_transform(new_df)\n",
    "\n",
    "clusterMatrix= linkage(new_df, method=\"ward\")\n",
    "plt.figure(figsize=(20, 6))\n",
    "dendrogram(clusterMatrix)\n",
    "\n",
    "plt.title('Dendrogram for Social Media Dataset')\n",
    "plt.xlabel('Data Points')\n",
    "plt.ylabel('Distance')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42e38131",
   "metadata": {},
   "source": [
    "Write-up:\n",
    "Overall, we analyzed a set of data about social media usage and mental health. We cleaned the data and broke it up into four seperate categories. We assigned a score to each category as well. Then we created two visualization that illustrated parts of our data. The first one showed correlations between each category and time spent on social media. This was what we anticipated from the beginning. The second one was a heatmap that showed the correlation score between all the specifc data columns in the set. Finally, we moved onto the machine learning model aspect of the project. We created two seperate KNN Classifier machine learning model comparing “age” and “depression” and \"time spent\" and \"stress total\" using 20% of the dataset for testing.  We then proceeded to fit the training data, model predictions, and output the accuracy score.  Increasing neighbors, as k increases, in turn increases accuracy scores. To visualize this phenomenon, a K Model Accuracy graph was implemented to illustrate the nonlinear increase of accuracy as neighbors increased. Finally, we created a dendrogram using hierarchial clustering to show how the data was grouped. This illustrated that we did group the data into the appropriate categories. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "84d31bb6",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}