Mental Health Analyzer.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "d3149c70-eeb0-45e6-89c0-f318734ea111",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "0514d1e8-7ea5-46e9-9581-86d921fdf55a",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"Mental_health_dset.csv\") \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "3400c9c6-1f52-4270-a0a5-8af6f31797e3",
   "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>feeling.nervous</th>\n",
       "      <th>panic</th>\n",
       "      <th>breathing.rapidly</th>\n",
       "      <th>sweating</th>\n",
       "      <th>trouble.in.concentration</th>\n",
       "      <th>having.trouble.in.sleeping</th>\n",
       "      <th>having.trouble.with.work</th>\n",
       "      <th>hopelessness</th>\n",
       "      <th>anger</th>\n",
       "      <th>over.react</th>\n",
       "      <th>...</th>\n",
       "      <th>weight.gain</th>\n",
       "      <th>material.possessions</th>\n",
       "      <th>introvert</th>\n",
       "      <th>popping.up.stressful.memory</th>\n",
       "      <th>having.nightmares</th>\n",
       "      <th>avoids.people.or.activities</th>\n",
       "      <th>feeling.negative</th>\n",
       "      <th>trouble.concentrating</th>\n",
       "      <th>blamming.yourself</th>\n",
       "      <th>Disorder</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>Anxiety</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>Depression</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>...</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>Loneliness</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>Stress</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>...</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>Normal</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  feeling.nervous panic breathing.rapidly sweating trouble.in.concentration  \\\n",
       "0             yes   yes               yes      yes                      yes   \n",
       "1              no    no                no       no                       no   \n",
       "2              no    no                no       no                       no   \n",
       "3              no    no                no       no                       no   \n",
       "4              no    no                no       no                       no   \n",
       "\n",
       "  having.trouble.in.sleeping having.trouble.with.work hopelessness anger  \\\n",
       "0                        yes                       no           no    no   \n",
       "1                         no                      yes          yes   yes   \n",
       "2                         no                       no           no    no   \n",
       "3                         no                       no           no    no   \n",
       "4                         no                       no           no    no   \n",
       "\n",
       "  over.react  ... weight.gain material.possessions introvert  \\\n",
       "0         no  ...          no                   no        no   \n",
       "1        yes  ...          no                   no        no   \n",
       "2         no  ...         yes                  yes       yes   \n",
       "3         no  ...          no                   no        no   \n",
       "4         no  ...          no                   no        no   \n",
       "\n",
       "  popping.up.stressful.memory having.nightmares avoids.people.or.activities  \\\n",
       "0                          no                no                          no   \n",
       "1                          no                no                          no   \n",
       "2                          no                no                          no   \n",
       "3                         yes               yes                         yes   \n",
       "4                          no                no                          no   \n",
       "\n",
       "  feeling.negative trouble.concentrating blamming.yourself    Disorder  \n",
       "0               no                    no                no     Anxiety  \n",
       "1               no                    no                no  Depression  \n",
       "2               no                    no                no  Loneliness  \n",
       "3              yes                   yes               yes      Stress  \n",
       "4               no                    no                no      Normal  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "e499f8d8-d043-46b2-beef-e995ac1669c0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\HafeezCS\\AppData\\Local\\Temp\\ipykernel_9280\\1274556580.py:8: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n",
      "  df[col] = df[col].replace(mapping)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       feeling.nervous  panic  breathing.rapidly  sweating  \\\n",
      "0                    1      1                  1         1   \n",
      "1                    0      0                  0         0   \n",
      "2                    0      0                  0         0   \n",
      "3                    0      0                  0         0   \n",
      "4                    0      0                  0         0   \n",
      "...                ...    ...                ...       ...   \n",
      "40955                1      1                  1         1   \n",
      "40956                0      0                  0         0   \n",
      "40957                0      0                  0         0   \n",
      "40958                0      0                  0         0   \n",
      "40959                0      0                  0         0   \n",
      "\n",
      "       trouble.in.concentration  having.trouble.in.sleeping  \\\n",
      "0                             1                           1   \n",
      "1                             0                           0   \n",
      "2                             0                           0   \n",
      "3                             0                           0   \n",
      "4                             0                           0   \n",
      "...                         ...                         ...   \n",
      "40955                         1                           1   \n",
      "40956                         0                           0   \n",
      "40957                         0                           0   \n",
      "40958                         0                           0   \n",
      "40959                         0                           0   \n",
      "\n",
      "       having.trouble.with.work  hopelessness  anger  over.react  ...  \\\n",
      "0                             0             0      0           0  ...   \n",
      "1                             1             1      1           1  ...   \n",
      "2                             0             0      0           0  ...   \n",
      "3                             0             0      0           0  ...   \n",
      "4                             0             0      0           0  ...   \n",
      "...                         ...           ...    ...         ...  ...   \n",
      "40955                         0             0      0           0  ...   \n",
      "40956                         1             1      1           1  ...   \n",
      "40957                         0             0      0           0  ...   \n",
      "40958                         0             0      0           0  ...   \n",
      "40959                         0             0      0           0  ...   \n",
      "\n",
      "       weight.gain  material.possessions  introvert  \\\n",
      "0                0                     0          0   \n",
      "1                0                     0          0   \n",
      "2                1                     1          1   \n",
      "3                0                     0          0   \n",
      "4                0                     0          0   \n",
      "...            ...                   ...        ...   \n",
      "40955            0                     0          0   \n",
      "40956            0                     0          0   \n",
      "40957            1                     1          1   \n",
      "40958            0                     0          0   \n",
      "40959            0                     0          0   \n",
      "\n",
      "       popping.up.stressful.memory  having.nightmares  \\\n",
      "0                                0                  0   \n",
      "1                                0                  0   \n",
      "2                                0                  0   \n",
      "3                                1                  1   \n",
      "4                                0                  0   \n",
      "...                            ...                ...   \n",
      "40955                            0                  0   \n",
      "40956                            0                  0   \n",
      "40957                            0                  0   \n",
      "40958                            1                  1   \n",
      "40959                            0                  0   \n",
      "\n",
      "       avoids.people.or.activities  feeling.negative  trouble.concentrating  \\\n",
      "0                                0                 0                      0   \n",
      "1                                0                 0                      0   \n",
      "2                                0                 0                      0   \n",
      "3                                1                 1                      1   \n",
      "4                                0                 0                      0   \n",
      "...                            ...               ...                    ...   \n",
      "40955                            0                 0                      0   \n",
      "40956                            0                 0                      0   \n",
      "40957                            0                 0                      0   \n",
      "40958                            1                 1                      1   \n",
      "40959                            0                 0                      0   \n",
      "\n",
      "       blamming.yourself    Disorder  \n",
      "0                      0     Anxiety  \n",
      "1                      0  Depression  \n",
      "2                      0  Loneliness  \n",
      "3                      1      Stress  \n",
      "4                      0      Normal  \n",
      "...                  ...         ...  \n",
      "40955                  0     Anxiety  \n",
      "40956                  0  Depression  \n",
      "40957                  0  Loneliness  \n",
      "40958                  1      Stress  \n",
      "40959                  0      Normal  \n",
      "\n",
      "[40960 rows x 25 columns]\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "\n",
    "mapping = {'yes': 1, 'no': 0}\n",
    "\n",
    "\n",
    "for col in df.columns:\n",
    "    df[col] = df[col].replace(mapping)\n",
    "\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "8796212f-be97-4aa0-ad0b-127a04defdac",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       feeling.nervous  panic  breathing.rapidly  sweating  \\\n",
      "0                    1      1                  1         1   \n",
      "1                    0      0                  0         0   \n",
      "2                    0      0                  0         0   \n",
      "3                    0      0                  0         0   \n",
      "4                    0      0                  0         0   \n",
      "...                ...    ...                ...       ...   \n",
      "40955                1      1                  1         1   \n",
      "40956                0      0                  0         0   \n",
      "40957                0      0                  0         0   \n",
      "40958                0      0                  0         0   \n",
      "40959                0      0                  0         0   \n",
      "\n",
      "       trouble.in.concentration  having.trouble.in.sleeping  \\\n",
      "0                             1                           1   \n",
      "1                             0                           0   \n",
      "2                             0                           0   \n",
      "3                             0                           0   \n",
      "4                             0                           0   \n",
      "...                         ...                         ...   \n",
      "40955                         1                           1   \n",
      "40956                         0                           0   \n",
      "40957                         0                           0   \n",
      "40958                         0                           0   \n",
      "40959                         0                           0   \n",
      "\n",
      "       having.trouble.with.work  hopelessness  anger  over.react  ...  \\\n",
      "0                             0             0      0           0  ...   \n",
      "1                             1             1      1           1  ...   \n",
      "2                             0             0      0           0  ...   \n",
      "3                             0             0      0           0  ...   \n",
      "4                             0             0      0           0  ...   \n",
      "...                         ...           ...    ...         ...  ...   \n",
      "40955                         0             0      0           0  ...   \n",
      "40956                         1             1      1           1  ...   \n",
      "40957                         0             0      0           0  ...   \n",
      "40958                         0             0      0           0  ...   \n",
      "40959                         0             0      0           0  ...   \n",
      "\n",
      "       weight.gain  material.possessions  introvert  \\\n",
      "0                0                     0          0   \n",
      "1                0                     0          0   \n",
      "2                1                     1          1   \n",
      "3                0                     0          0   \n",
      "4                0                     0          0   \n",
      "...            ...                   ...        ...   \n",
      "40955            0                     0          0   \n",
      "40956            0                     0          0   \n",
      "40957            1                     1          1   \n",
      "40958            0                     0          0   \n",
      "40959            0                     0          0   \n",
      "\n",
      "       popping.up.stressful.memory  having.nightmares  \\\n",
      "0                                0                  0   \n",
      "1                                0                  0   \n",
      "2                                0                  0   \n",
      "3                                1                  1   \n",
      "4                                0                  0   \n",
      "...                            ...                ...   \n",
      "40955                            0                  0   \n",
      "40956                            0                  0   \n",
      "40957                            0                  0   \n",
      "40958                            1                  1   \n",
      "40959                            0                  0   \n",
      "\n",
      "       avoids.people.or.activities  feeling.negative  trouble.concentrating  \\\n",
      "0                                0                 0                      0   \n",
      "1                                0                 0                      0   \n",
      "2                                0                 0                      0   \n",
      "3                                1                 1                      1   \n",
      "4                                0                 0                      0   \n",
      "...                            ...               ...                    ...   \n",
      "40955                            0                 0                      0   \n",
      "40956                            0                 0                      0   \n",
      "40957                            0                 0                      0   \n",
      "40958                            1                 1                      1   \n",
      "40959                            0                 0                      0   \n",
      "\n",
      "       blamming.yourself  Disorder  \n",
      "0                      0         0  \n",
      "1                      0         1  \n",
      "2                      0         2  \n",
      "3                      1         4  \n",
      "4                      0         3  \n",
      "...                  ...       ...  \n",
      "40955                  0         0  \n",
      "40956                  0         1  \n",
      "40957                  0         2  \n",
      "40958                  1         4  \n",
      "40959                  0         3  \n",
      "\n",
      "[40960 rows x 25 columns]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.preprocessing import LabelEncoder\n",
    "\n",
    "\n",
    "le = LabelEncoder()\n",
    "\n",
    "\n",
    "df['Disorder'] = le.fit_transform(df['Disorder'])\n",
    "\n",
    "\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "99e8c447-9756-4fe8-be3e-b9ba46090f39",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 2, 4, 3])"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Disorder'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "60130f85-b3f2-44cb-b25b-e670dc5eefb6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(df)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "b72186d6-d4d7-427a-bb0d-4ca4cc8cd4f6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Disorder', ylabel='Count'>"
      ]
     },
     "execution_count": 36,
     "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": [
    "sns.histplot(data=df, x=\"Disorder\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "775b37a5-25a7-4639-87f7-6a023b357a4c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "correlation = df.corr()  \n",
    "sns.heatmap(correlation, annot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "2d4791e5-e3d4-498e-92f4-d59b1f0915ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='feeling.nervous', ylabel='Disorder'>"
      ]
     },
     "execution_count": 38,
     "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": [
    "sns.scatterplot(x=\"feeling.nervous\", y=\"Disorder\", data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "3b41e601-2259-4b6c-bec6-3e3a36cf6971",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='panic', ylabel='Disorder'>"
      ]
     },
     "execution_count": 39,
     "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": [
    "sns.scatterplot(x=\"panic\", y=\"Disorder\", data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "ab9219ad-2fd4-4c6b-827d-a0fe86ef31d6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='having.trouble.in.sleeping', ylabel='Disorder'>"
      ]
     },
     "execution_count": 40,
     "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": [
    "sns.scatterplot(x=\"having.trouble.in.sleeping\", y=\"Disorder\", data=df)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "fd6e18af-d706-4c3b-8921-850658b0818f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Disorder', ylabel='having.trouble.in.sleeping'>"
      ]
     },
     "execution_count": 41,
     "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": [
    "sns.scatterplot(x=\"Disorder\", y=\"having.trouble.in.sleeping\", data=df)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "f0b1e2a5-c591-49d6-99fb-8e70df9c88b6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Disorder', ylabel='panic'>"
      ]
     },
     "execution_count": 42,
     "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": [
    "sns.barplot(x=\"Disorder\", y=\"panic\", data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "51fcfdbd-428d-4d2f-a960-23f9eb223992",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Disorder', ylabel='having.trouble.in.sleeping'>"
      ]
     },
     "execution_count": 43,
     "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": [
    "sns.barplot(x=\"Disorder\", y=\"having.trouble.in.sleeping\", data=df)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "c4c9eb75-e792-45d8-9f4c-902d5f07c889",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LinearRegression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "24d2127a-4ae5-4ac4-b97a-bae2db68b931",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(df.drop('Disorder', axis=1),  \n",
    "                                                    df['Disorder'],\n",
    "                                                    test_size=0.4, \n",
    "                                                    random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "deeff033-cfec-4e64-b602-51532f83a683",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = LinearRegression()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "da3d2e3b-f62c-43eb-a9d1-cf2670042291",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-2 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-2 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-2 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-2 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-2 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LinearRegression()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;LinearRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.5/modules/generated/sklearn.linear_model.LinearRegression.html\">?<span>Documentation for LinearRegression</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>LinearRegression()</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "955c12ab-afbd-4ee6-977f-27194d82a5c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = model.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "a12bb77e-294f-419b-84cf-339b3973fec3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean Squared Error: 4.764269199927925e-31\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import mean_squared_error\n",
    "mse = mean_squared_error(y_test, y_pred)\n",
    "print(f\"Mean Squared Error: {mse}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "50edaf33-4bce-4655-9b2c-06e46dde0a5d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 1.00\n"
     ]
    }
   ],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "model = LogisticRegression()\n",
    "model.fit(X_train, y_train)\n",
    "\n",
    "\n",
    "y_pred = model.predict(X_test)\n",
    "\n",
    "accuracy = accuracy_score(y_test, y_pred)\n",
    "print(f\"Accuracy: {accuracy:.2f}\") "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "137dcf0c-5ca6-4f09-be28-511665441878",
   "metadata": {},
   "outputs": [],
   "source": [
    "import joblib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "a2af6c1d-08d1-4c6a-a238-b6e77c3e2917",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Disorder.joblib']"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joblib.dump(model, 'Disorder.joblib')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "4d8db8df-3f8a-4aec-a910-230da4a18062",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = joblib.load('Disorder.joblib')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "840a5c5d-43b6-45c9-a249-cc9123255eaf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predictions: [3]\n"
     ]
    }
   ],
   "source": [
    "def Disorder(new_data):\n",
    "    \"\"\"\n",
    "    Predict mental health diagnosis for new data.\n",
    "    \n",
    "    Parameters:\n",
    "    new_data (pd.DataFrame): A DataFrame containing the new data for prediction\n",
    "    \n",
    "    Returns:\n",
    "    np.array: Array of predictions\n",
    "    \"\"\"\n",
    "    predictions = model.predict(new_data)\n",
    "    return predictions\n",
    "\n",
    "new_data = pd.DataFrame({\n",
    "    'feeling.nervous': [1],\n",
    "    'panic': [0],\n",
    "    'breathing.rapidly': [1],\n",
    "    'sweating': [0],\n",
    "    'trouble.in.concentration': [0],\n",
    "    'having.trouble.in.sleeping': [0],\n",
    "    'having.trouble.with.work': [0],\n",
    "    'hopelessness': [0],\n",
    "    'anger': [0],\n",
    "    'over.react': [0],\n",
    "    'change.in.eating': [0],\n",
    "    'suicidal.thought': [0],\n",
    "    'feeling.tired': [0],\n",
    "    'close.friend': [0],\n",
    "    'social.media.addiction': [0],\n",
    "    'weight.gain': [0],\n",
    "    'material.possessions': [0],\n",
    "    'introvert': [0],\n",
    "    'popping.up.stressful.memory': [0],\n",
    "    'having.nightmares': [0],\n",
    "    'avoids.people.or.activities': [0],\n",
    "    'feeling.negative': [0],\n",
    "    'trouble.concentrating': [0],\n",
    "    'blamming.yourself': [0]\n",
    "})\n",
    "\n",
    "# Get predictions\n",
    "predictions = Disorder(new_data)\n",
    "print(\"Predictions:\", predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "2aef9dab-bf3a-4cb9-a044-9005dd85bccc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predictions: [3]\n"
     ]
    }
   ],
   "source": [
    "\n",
    "\n",
    "def disorder_prediction(new_data):\n",
    "    \"\"\"\n",
    "    Predict mental health diagnosis for new data.\n",
    "    \n",
    "    Parameters:\n",
    "    new_data (pd.DataFrame): A DataFrame containing the new data for prediction\n",
    "    \n",
    "    Returns:\n",
    "    np.array: Array of predictions\n",
    "    \"\"\"\n",
    "    predictions = model.predict(new_data)\n",
    "    return predictions\n",
    "\n",
    "# Example usage\n",
    "def main():\n",
    "\n",
    "    new_data = pd.DataFrame({\n",
    "        'feeling.nervous': [1],\n",
    "        'panic': [0],\n",
    "        'breathing.rapidly': [1],\n",
    "        'sweating': [0],\n",
    "        'trouble.in.concentration': [0],\n",
    "        'having.trouble.in.sleeping': [0],\n",
    "        'having.trouble.with.work': [0],\n",
    "        'hopelessness': [0],\n",
    "        'anger': [0],\n",
    "        'over.react': [0],\n",
    "        'change.in.eating': [0],\n",
    "        'suicidal.thought': [0],\n",
    "        'feeling.tired': [0],\n",
    "        'close.friend': [0],\n",
    "        'social.media.addiction': [0],\n",
    "        'weight.gain': [0],\n",
    "        'material.possessions': [0],\n",
    "        'introvert': [0],\n",
    "        'popping.up.stressful.memory': [0],\n",
    "        'having.nightmares': [0],\n",
    "        'avoids.people.or.activities': [0],\n",
    "        'feeling.negative': [0],\n",
    "        'trouble.concentrating': [0],\n",
    "        'blamming.yourself': [0]\n",
    "    })\n",
    "\n",
    "    # Get predictions\n",
    "    predictions = disorder_prediction(new_data)\n",
    "    print(\"Predictions:\", predictions)\n",
    "\n",
    "if __name__ == \"__main__\":\n",
    "    main()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4fd4cb1d-5c2d-4c20-8938-33c646979d72",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Welcome to the Mental Health Disorder Predictor!\n",
      "\n",
      "Enter your symptoms:\n"
     ]
    }
   ],
   "source": [
    "\n",
    "\n",
    "def disorder_prediction(new_data):\n",
    "    \"\"\"\n",
    "    Predict mental health diagnosis for new data.\n",
    "    \n",
    "    Parameters:\n",
    "    new_data (pd.DataFrame): A DataFrame containing the new data for prediction\n",
    "    \n",
    "    Returns:\n",
    "    np.array: Array of predictions\n",
    "    \"\"\"\n",
    "    predictions = model.predict(new_data)\n",
    "    return predictions\n",
    "\n",
    "def get_user_input():\n",
    " \n",
    "    questions = {\n",
    "        'feeling.nervous': \"Are you feeling nervous? (0 for No, 1 for Yes): \",\n",
    "        'panic': \"Are you experiencing panic? (0 for No, 1 for Yes): \",\n",
    "        'breathing.rapidly': \"Are you breathing rapidly? (0 for No, 1 for Yes): \",\n",
    "        'sweating': \"Are you sweating? (0 for No, 1 for Yes): \",\n",
    "        'trouble.in.concentration': \"Are you having trouble in concentration? (0 for No, 1 for Yes): \",\n",
    "        'having.trouble.in.sleeping': \"Are you having trouble in sleeping? (0 for No, 1 for Yes): \",\n",
    "        'having.trouble.with.work': \"Are you having trouble with work? (0 for No, 1 for Yes): \",\n",
    "        'hopelessness': \"Are you feeling hopelessness? (0 for No, 1 for Yes): \",\n",
    "        'anger': \"Are you feeling anger? (0 for No, 1 for Yes): \",\n",
    "        'over.react': \"Do you over-react? (0 for No, 1 for Yes): \",\n",
    "        'change.in.eating': \"Have you experienced change in eating habits? (0 for No, 1 for Yes): \",\n",
    "        'suicidal.thought': \"Do you have suicidal thoughts? (0 for No, 1 for Yes): \",\n",
    "        'feeling.tired': \"Are you feeling tired? (0 for No, 1 for Yes): \",\n",
    "        'close.friend': \"Do you have a close friend? (0 for No, 1 for Yes): \",\n",
    "        'social.media.addiction': \"Do you have social media addiction? (0 for No, 1 for Yes): \",\n",
    "        'weight.gain': \"Have you experienced weight gain? (0 for No, 1 for Yes): \",\n",
    "        'material.possessions': \"Are you obsessed with material possessions? (0 for No, 1 for Yes): \",\n",
    "        'introvert': \"Are you introverted? (0 for No, 1 for Yes): \",\n",
    "        'popping.up.stressful.memory': \"Are you experiencing popping up stressful memory? (0 for No, 1 for Yes): \",\n",
    "        'having.nightmares': \"Are you having nightmares? (0 for No, 1 for Yes): \",\n",
    "        'avoids.people.or.activities': \"Do you avoid people or activities? (0 for No, 1 for Yes): \",\n",
    "        'feeling.negative': \"Are you feeling negative? (0 for No, 1 for Yes): \",\n",
    "        'trouble.concentrating': \"Are you having trouble concentrating? (0 for No, 1 for Yes): \",\n",
    "        'blamming.yourself': \"Are you blaming yourself? (0 for No, 1 for Yes): \"\n",
    "    }\n",
    "\n",
    "\n",
    "    user_data = {}\n",
    "    for feature, question in questions.items():\n",
    "        response = input(question)\n",
    "        user_data[feature] = [int(response)]\n",
    "\n",
    "\n",
    "    new_data = pd.DataFrame(user_data)\n",
    "    return new_data\n",
    "\n",
    "def main():\n",
    "    print(\"Welcome to the Mental Health Disorder Predictor!\")\n",
    "    \n",
    "    while True:\n",
    "        print(\"\\nEnter your symptoms:\")\n",
    "        new_data = get_user_input()\n",
    "\n",
    "\n",
    "        predictions = disorder_prediction(new_data)\n",
    "        print(\"\\nPredictions:\", predictions)\n",
    "\n",
    "\n",
    "        choice = input(\"\\nDo you want to continue? (yes/no): \").lower()\n",
    "        if choice != 'yes':\n",
    "            break\n",
    "\n",
    "    print(\"Thank you for using the Mental Health Disorder Predictor!\")\n",
    "\n",
    "if __name__ == \"__main__\":\n",
    "    main()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "569028e9-7f1b-42ef-876b-0d593aeaf879",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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