createSyntheticData.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 286,
   "metadata": {},
   "outputs": [],
   "source": [
    "import random\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from datetime import date\n",
    "\n",
    "df = pd.DataFrame()\n",
    "\n",
    "anoatual = 2022\n",
    "data_nascimento =\"\" #dia mes ano#\n",
    "ages = []\n",
    "\n",
    "hoje = date.today()\n",
    "hoje_str = hoje.strftime(\"%d/%m/%Y\")\n",
    "data = str(hoje_str).split(\"/\")#mes\n",
    "mes_hoje = int(data[1])\n",
    "ano_hoje = int(data[2])\n",
    "\n",
    "inicio = 0\n",
    "fim = 300\n",
    "numero_usuarias = 3000\n",
    "\n",
    "num15_19 = int (0.01*numero_usuarias)\n",
    "num20_24 = int (0.10*numero_usuarias)\n",
    "num25_29 = int (0.29*numero_usuarias)\n",
    "num30_34 = int (0.38*numero_usuarias)\n",
    "num35_39 = int (0.20*numero_usuarias)\n",
    "num40_44 = int (0.015*numero_usuarias)\n",
    "num45_49 = int (0.005*numero_usuarias)\n",
    "\n",
    "#print(num15_19, num20_24, num25_29, num30_34, num35_39, num40_44, num45_49) \n",
    "#r = num15_19+ num20_24+ num25_29+ num30_34+ num35_39+ num40_44+ num45_49\n",
    "#print(r)\n",
    "\n",
    "\n",
    "for x in range(inicio, num15_19-1):\n",
    "    age = random.randint(15, 19)\n",
    "    ages.append(age)    \n",
    "    data_nascimento = create_data_nascimento(age, anoatual)      \n",
    "    data_diagnostico = create_data_diagnostico(mes_hoje, ano_hoje)\n",
    "    user = { 'Num': str(x),  'Id': 'User' + str(x), 'Document': 'User' + str(x), 'Name' : 'User'+str(x), \n",
    "    'Surname': 'User' + str(x),  'Age' : str(age)  , 'DateBirth': data_nascimento, 'DateDiagnosis': data_diagnostico}\n",
    "    sintomas = create_data_sintomas()\n",
    "    user.update(sintomas)\n",
    "    humors = create_data_humors()\n",
    "    user.update(humors)    \n",
    "    df = df.append(user, ignore_index=True)\n",
    "        \n",
    "\n",
    "for x in range(num15_19, num15_19 + num20_24 -1):\n",
    "    age = random.randint(20, 24)\n",
    "    ages.append(age)\n",
    "    data_nascimento = create_data_nascimento(age, anoatual)      \n",
    "    data_diagnostico = create_data_diagnostico(mes_hoje, ano_hoje)\n",
    "    user = { 'Num': str(x),  'Id': 'User' + str(x), 'Document': 'User' + str(x), 'Name' : 'User'+str(x), \n",
    "    'Surname': 'User' + str(x),  'Age' : str(age)  , 'DateBirth': data_nascimento, 'DateDiagnosis': data_diagnostico}\n",
    "    sintomas = create_data_sintomas()\n",
    "    user.update(sintomas)\n",
    "    humors = create_data_humors()\n",
    "    user.update(humors)    \n",
    "    df = df.append(user, ignore_index=True)\n",
    "\n",
    "#print('x:', x)\n",
    "#print('x:', x, \"size: \", len(ages))\n",
    "\n",
    "for x in range(num20_24, num20_24 + num25_29 -1):\n",
    "    age = random.randint(25, 29)\n",
    "    ages.append(age)    \n",
    "    data_nascimento = create_data_nascimento(age, anoatual)      \n",
    "    data_diagnostico = create_data_diagnostico(mes_hoje, ano_hoje)\n",
    "    user = { 'Num': str(x),  'Id': 'User' + str(x), 'Document': 'User' + str(x), 'Name' : 'User'+str(x), \n",
    "    'Surname': 'User' + str(x),  'Age' : str(age)  , 'DateBirth': data_nascimento, 'DateDiagnosis': data_diagnostico}\n",
    "    sintomas = create_data_sintomas()\n",
    "    user.update(sintomas)\n",
    "    humors = create_data_humors()\n",
    "    user.update(humors)    \n",
    "    df = df.append(user, ignore_index=True)\n",
    "\n",
    "#print('x:', x)\n",
    "#print('x:', x, \"size: \", len(ages))\n",
    "\n",
    "for x in range(num25_29, num25_29 + num30_34 -1):\n",
    "    age = random.randint(30, 34)\n",
    "    ages.append(age)\n",
    "    data_nascimento = create_data_nascimento(age, anoatual)      \n",
    "    data_diagnostico = create_data_diagnostico(mes_hoje, ano_hoje)\n",
    "    user = { 'Num': str(x),  'Id': 'User' + str(x), 'Document': 'User' + str(x), 'Name' : 'User'+str(x), \n",
    "    'Surname': 'User' + str(x),  'Age' : str(age)  , 'DateBirth': data_nascimento, 'DateDiagnosis': data_diagnostico}\n",
    "    sintomas = create_data_sintomas()\n",
    "    user.update(sintomas)\n",
    "    humors = create_data_humors()\n",
    "    user.update(humors)    \n",
    "    df = df.append(user, ignore_index=True)\n",
    "\n",
    "#print('x:', x)\n",
    "#print('x:', x, \"size: \", len(ages))\n",
    "\n",
    "for x in range(num30_34, num30_34 + num35_39 -1):\n",
    "    age = random.randint(35, 39)\n",
    "    ages.append(age)\n",
    "    data_nascimento = create_data_nascimento(age, anoatual)      \n",
    "    data_diagnostico = create_data_diagnostico(mes_hoje, ano_hoje)\n",
    "    user = { 'Num': str(x),  'Id': 'User' + str(x), 'Document': 'User' + str(x), 'Name' : 'User'+str(x), \n",
    "    'Surname': 'User' + str(x),  'Age' : str(age)  , 'DateBirth': data_nascimento, 'DateDiagnosis': data_diagnostico}\n",
    "    sintomas = create_data_sintomas()\n",
    "    user.update(sintomas)\n",
    "    humors = create_data_humors()\n",
    "    user.update(humors)    \n",
    "    df = df.append(user, ignore_index=True)\n",
    "\n",
    "#print('x:', x)\n",
    "#print('x:', x, \"size: \", len(ages))\n",
    "\n",
    "for x in range(num35_39, num35_39 + num40_44 -1):\n",
    "    age = random.randint(40, 44)\n",
    "    ages.append(age)\n",
    "    data_nascimento = create_data_nascimento(age, anoatual)      \n",
    "    data_diagnostico = create_data_diagnostico(mes_hoje, ano_hoje)\n",
    "    user = { 'Num': str(x),  'Id': 'User' + str(x), 'Document': 'User' + str(x), 'Name' : 'User'+str(x), \n",
    "    'Surname': 'User' + str(x),  'Age' : str(age)  , 'DateBirth': data_nascimento, 'DateDiagnosis': data_diagnostico}\n",
    "    sintomas = create_data_sintomas()\n",
    "    user.update(sintomas)\n",
    "    humors = create_data_humors()\n",
    "    user.update(humors)    \n",
    "    df = df.append(user, ignore_index=True)\n",
    "\n",
    "#print('x:', x)\n",
    "#print('x:', x, \"size: \", len(ages))\n",
    "\n",
    "for x in range(num40_44, num40_44 + num45_49 -1):\n",
    "    age = random.randint(45, 49)\n",
    "    ages.append(age)\n",
    "    data_nascimento = create_data_nascimento(age, anoatual)      \n",
    "    data_diagnostico = create_data_diagnostico(mes_hoje, ano_hoje)\n",
    "    user = { 'Num': str(x),  'Id': 'User' + str(x), 'Document': 'User' + str(x), 'Name' : 'User'+str(x), \n",
    "    'Surname': 'User' + str(x),  'Age' : str(age)  , 'DateBirth': data_nascimento, 'DateDiagnosis': data_diagnostico}\n",
    "    sintomas = create_data_sintomas()\n",
    "    user.update(sintomas)\n",
    "    humors = create_data_humors()\n",
    "    user.update(humors)    \n",
    "    df = df.append(user, ignore_index=True)\n",
    "\n",
    "#print('x:', x)\n",
    "#print('x:', x, \"size: \", len(ages))\n",
    "\n",
    "#user"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 288,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3 30 87 114 60 4 1\n",
      "299\n"
     ]
    }
   ],
   "source": [
    "numero_usuarias = 300\n",
    "\n",
    "num15_19 = int (0.01*numero_usuarias)\n",
    "num20_24 = int (0.10*numero_usuarias)\n",
    "num25_29 = int (0.29*numero_usuarias)\n",
    "num30_34 = int (0.38*numero_usuarias)\n",
    "num35_39 = int (0.20*numero_usuarias)\n",
    "num40_44 = int (0.015*numero_usuarias)\n",
    "num45_49 = int (0.005*numero_usuarias)\n",
    "\n",
    "print(num15_19, num20_24, num25_29, num30_34, num35_39, num40_44, num45_49) \n",
    "r = num15_19+ num20_24+ num25_29+ num30_34+ num35_39+ num40_44+ num45_49\n",
    "print(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 289,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Num</th>\n",
       "      <th>Id</th>\n",
       "      <th>Document</th>\n",
       "      <th>Name</th>\n",
       "      <th>Surname</th>\n",
       "      <th>Age</th>\n",
       "      <th>DateBirth</th>\n",
       "      <th>DateDiagnosis</th>\n",
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       "      <th>Appetite</th>\n",
       "      <th>...</th>\n",
       "      <th>Emotional</th>\n",
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       "      <th>Excited</th>\n",
       "      <th>Focused</th>\n",
       "      <th>Frisky</th>\n",
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       "      <th>Happy</th>\n",
       "      <th>InLove</th>\n",
       "      <th>Irritable</th>\n",
       "      <th>Moody</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>User0</td>\n",
       "      <td>User0</td>\n",
       "      <td>User0</td>\n",
       "      <td>User0</td>\n",
       "      <td>17</td>\n",
       "      <td>25/2/2005</td>\n",
       "      <td>6/4/2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mild</td>\n",
       "      <td>...</td>\n",
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       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>User1</td>\n",
       "      <td>User1</td>\n",
       "      <td>User1</td>\n",
       "      <td>User1</td>\n",
       "      <td>18</td>\n",
       "      <td>22/9/2004</td>\n",
       "      <td>8/7/2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mild</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>User2</td>\n",
       "      <td>User2</td>\n",
       "      <td>User2</td>\n",
       "      <td>User2</td>\n",
       "      <td>18</td>\n",
       "      <td>15/9/2004</td>\n",
       "      <td>25/2/2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>User3</td>\n",
       "      <td>User3</td>\n",
       "      <td>User3</td>\n",
       "      <td>User3</td>\n",
       "      <td>16</td>\n",
       "      <td>13/11/2006</td>\n",
       "      <td>30/3/2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>User4</td>\n",
       "      <td>User4</td>\n",
       "      <td>User4</td>\n",
       "      <td>User4</td>\n",
       "      <td>15</td>\n",
       "      <td>6/8/2007</td>\n",
       "      <td>15/2/2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mild</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2987</th>\n",
       "      <td>54</td>\n",
       "      <td>User54</td>\n",
       "      <td>User54</td>\n",
       "      <td>User54</td>\n",
       "      <td>User54</td>\n",
       "      <td>45</td>\n",
       "      <td>8/9/1977</td>\n",
       "      <td>5/3/2022</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>Mild</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2988</th>\n",
       "      <td>55</td>\n",
       "      <td>User55</td>\n",
       "      <td>User55</td>\n",
       "      <td>User55</td>\n",
       "      <td>User55</td>\n",
       "      <td>45</td>\n",
       "      <td>24/6/1977</td>\n",
       "      <td>12/2/2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Mild</td>\n",
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       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2989</th>\n",
       "      <td>56</td>\n",
       "      <td>User56</td>\n",
       "      <td>User56</td>\n",
       "      <td>User56</td>\n",
       "      <td>User56</td>\n",
       "      <td>47</td>\n",
       "      <td>9/4/1975</td>\n",
       "      <td>25/7/2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2990</th>\n",
       "      <td>57</td>\n",
       "      <td>User57</td>\n",
       "      <td>User57</td>\n",
       "      <td>User57</td>\n",
       "      <td>User57</td>\n",
       "      <td>47</td>\n",
       "      <td>29/5/1975</td>\n",
       "      <td>4/7/2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2991</th>\n",
       "      <td>58</td>\n",
       "      <td>User58</td>\n",
       "      <td>User58</td>\n",
       "      <td>User58</td>\n",
       "      <td>User58</td>\n",
       "      <td>49</td>\n",
       "      <td>8/6/1973</td>\n",
       "      <td>12/1/2022</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2992 rows × 43 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Num      Id Document    Name Surname Age   DateBirth DateDiagnosis  \\\n",
       "0      0   User0    User0   User0   User0  17   25/2/2005      6/4/2022   \n",
       "1      1   User1    User1   User1   User1  18   22/9/2004      8/7/2022   \n",
       "2      2   User2    User2   User2   User2  18   15/9/2004     25/2/2022   \n",
       "3      3   User3    User3   User3   User3  16  13/11/2006     30/3/2022   \n",
       "4      4   User4    User4   User4   User4  15    6/8/2007     15/2/2022   \n",
       "...   ..     ...      ...     ...     ...  ..         ...           ...   \n",
       "2987  54  User54   User54  User54  User54  45    8/9/1977      5/3/2022   \n",
       "2988  55  User55   User55  User55  User55  45   24/6/1977     12/2/2022   \n",
       "2989  56  User56   User56  User56  User56  47    9/4/1975     25/7/2022   \n",
       "2990  57  User57   User57  User57  User57  47   29/5/1975      4/7/2022   \n",
       "2991  58  User58   User58  User58  User58  49    8/6/1973     12/1/2022   \n",
       "\n",
       "          Acne Appetite  ... Emotional Energetic Excited Focused Frisky  \\\n",
       "0          NaN     Mild  ...         0         1       0       0      1   \n",
       "1          NaN     Mild  ...         1         0       0       0      1   \n",
       "2          NaN      NaN  ...         0         0       0       0      0   \n",
       "3          NaN      NaN  ...         0         1       0       1      0   \n",
       "4          NaN     Mild  ...         0         0       0       0      1   \n",
       "...        ...      ...  ...       ...       ...     ...     ...    ...   \n",
       "2987  Moderate     Mild  ...         1         0       0       0      1   \n",
       "2988       NaN     Mild  ...         0         0       0       0      1   \n",
       "2989       NaN      NaN  ...         1         0       0       0      0   \n",
       "2990       NaN      NaN  ...         0         1       0       0      1   \n",
       "2991       NaN      NaN  ...         0         0       0       1      1   \n",
       "\n",
       "     Frustated Happy InLove Irritable Moody  \n",
       "0            1     0      0         1     1  \n",
       "1            1     0      0         1     1  \n",
       "2            1     1      0         1     1  \n",
       "3            0     0      0         0     1  \n",
       "4            0     0      1         1     0  \n",
       "...        ...   ...    ...       ...   ...  \n",
       "2987         0     0      0         1     1  \n",
       "2988         0     1      1         1     0  \n",
       "2989         0     0      1         0     1  \n",
       "2990         1     0      0         1     0  \n",
       "2991         0     1      0         0     0  \n",
       "\n",
       "[2992 rows x 43 columns]"
      ]
     },
     "execution_count": 289,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "def create_data_diagnostico(mes_hoje, ano_hoje):     \n",
    "    dia_diag = random.randint(1, 30)\n",
    "    mes_diag = random.randint(1, mes_hoje)\n",
    "    data_diagnostico = str(dia_diag)+'/'+str(mes_diag)+'/'+str(ano_hoje)\n",
    "    return data_diagnostico    \n",
    "    \n",
    "\n",
    "def create_data_nascimento(age, anoatual): \n",
    "    ano = anoatual-age\n",
    "    mes = random.randint(1, 12)\n",
    "    dia = random.randint(1, 30)\n",
    "    data_nascimento = str(dia)+'/'+str(mes)+'/'+str(ano)\n",
    "    return data_nascimento\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_data_sintomas():     \n",
    "    sintomas ={'Acne': np.nan, 'Appetite': np.nan, 'Backache': np.nan, 'Bloating': np.nan, 'Constipation': np.nan,\n",
    "        'Cramps': np.nan, 'Diarrhea': np.nan, 'Nausea': np.nan, 'PainDuringSex': np.nan, \n",
    "        'PelvicPain': np.nan, 'SexDrive': np.nan, 'Sick': np.nan, 'SoreBreasts': np.nan, \n",
    "        'VaginalPain': np.nan, 'Dizziness': np.nan, 'Fatigue': np.nan, 'Headache': np.nan, \n",
    "        'HotFlashes': np.nan, 'Indigestion':np.nan, 'Insomnia': np.nan, 'Migraine': np.nan}\n",
    "\n",
    "    sintomas_indice = {0: 'PelvicPain', 1: 'Appetite', 2:'SexDrive', 3: 'Bloating', \n",
    "            4:'Constipation', 5:'VaginalPain', 6:'Diarrhea', 7:'Nausea', \n",
    "            8:'PainDuringSex', 9:'Migraine', 10:'Dizziness', 11:'Sick', \n",
    "            12:'HotFlashes', 13:'Indigestion',  \n",
    "            14:'Acne', 15:'Backache', 16:'Cramps', 17:'SoreBreasts', \n",
    "            18:'Fatigue', 19:'Headache', 20:'Insomnia'}\n",
    "\n",
    "    sintomas_prob = {'PelvicPain': 0.036, 'Appetite':0.036, 'SexDrive':0.036, 'Bloating': 0.036, \n",
    "            'Constipation':0.036, 'VaginalPain':0.036, 'Diarrhea':0.036, 'Nausea':0.036, \n",
    "            'PainDuringSex': 0.036 , 'Migraine':0.036, 'Dizziness': 0.036, 'Sick': 0.036, \n",
    "            'HotFlashes': 0.036, 'Indigestion': 0.036, \n",
    "            'Acne': 0.071, 'Backache':0.071, 'Cramps':0.071, 'SoreBreasts':0.071, \n",
    "            'Fatigue': 0.071, 'Headache':0.071, 'Insomnia':0.070}\n",
    "                         \n",
    "    numero_sintomas = random.randint(3, 8)\n",
    "\n",
    "    rnd_sintomas = np.random.choice([0, 1, 2, 3 , 4, 5, 6, 7, 8 ,9, 10, 11, 12, 13, \n",
    "                      14, 15, 16, 17, 18, 19, 20], \n",
    "                 p=[0.036, 0.036, 0.036, 0.036, 0.036, 0.036, 0.036,\n",
    "                    0.036 ,0.036 ,0.036, 0.036, 0.036, 0.036, 0.036, \n",
    "                    0.071, 0.071, 0.071, 0.071, 0.071, 0.071, 0.070], size=numero_sintomas)\n",
    "\n",
    "    lista_sintomas = list(dict.fromkeys(rnd_sintomas))\n",
    "    #print(lista_sintomas)  \n",
    "    \n",
    "    #for key in lista_sintomas:    \n",
    "        #print(key, 'corresponds to', sintomas_indice[key], ': ', sintomas_prob[sintomas_indice[key]])\n",
    "    niveis = len(lista_sintomas)\n",
    "    nivel_sintoma = {'Mild':0.3, 'Moderate': 0.45, 'Severe':0.25}\n",
    "    nivel_indice = {0: 'Mild', 1:'Moderate', 2:'Severe'}\n",
    "    rnd_nivel = np.random.choice([0, 1, 2], p=[0.3, 0.45, 0.25],size=niveis)\n",
    "\n",
    "\n",
    "    i=0\n",
    "    for key  in rnd_nivel:\n",
    "        #print(sintomas_indice[lista_sintomas[i]], ':', nivel_indice[key] )        \n",
    "        sintomas.update({sintomas_indice[lista_sintomas[i]]: nivel_indice[key]}) \n",
    "        i=i+1\n",
    "\n",
    "    return sintomas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Acne': nan,\n",
       " 'Appetite': nan,\n",
       " 'Backache': 'Mild',\n",
       " 'Bloating': nan,\n",
       " 'Constipation': nan,\n",
       " 'Cramps': nan,\n",
       " 'Diarrhea': nan,\n",
       " 'Nausea': nan,\n",
       " 'PainDuringSex': 'Severe',\n",
       " 'PelvicPain': nan,\n",
       " 'SexDrive': nan,\n",
       " 'Sick': nan,\n",
       " 'SoreBreasts': 'Moderate',\n",
       " 'VaginalPain': nan,\n",
       " 'Dizziness': nan,\n",
       " 'Fatigue': 'Mild',\n",
       " 'Headache': nan,\n",
       " 'HotFlashes': nan,\n",
       " 'Indigestion': 'Moderate',\n",
       " 'Insomnia': 'Mild',\n",
       " 'Migraine': nan}"
      ]
     },
     "execution_count": 195,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "create_data_sintomas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_data_humors():\n",
    "    numero_humor = random.randint(5, 8)\n",
    "\n",
    "    humor_indice = {0:'Angry', 1:'Anxious', 2:'Calm', 3:'Depressed', 4:'Emotional',\n",
    "         5:'Energetic', 6:'Excited', 7:'Focused', 8:'Frisky', 9:'Frustated', \n",
    "         10:'Happy', 11:'InLove', 12:'Irritable', 13:'Moody'}\n",
    "\n",
    "    humor = {'Angry': 0.05, 'Anxious':0.1, 'Calm':0.05, 'Depressed': 0.1, 'Emotional':0.1, \n",
    "         'Energetic':0.05, 'Excited':0.05, 'Focused':0.05, 'Frisky': 0.0625 , \n",
    "         'Frustated': 0.0625, 'Happy': 0.0625, 'InLove': 0.0625,\n",
    "         'Irritable': 0.1, 'Moody': 0.1}\n",
    "    \n",
    "    rnd_humor = np.random.choice([0, 1, 2, 3 , 4, 5, 6, 7, 8 ,9, 10, 11, 12, 13],                      \n",
    "                 p=[0.05, 0.1, 0.05, 0.1, 0.1, 0.05, 0.05, 0.05, 0.0625, 0.0625, 0.0625, 0.0625, 0.1, 0.1],                              \n",
    "                             size=numero_humor)\n",
    "\n",
    "    humores = {'Angry':'0', 'Anxious':'0', 'Calm':'0', 'Depressed':'0', 'Emotional':'0', \n",
    "        'Energetic':'0', 'Excited':'0', 'Focused':'0', 'Frisky':'0', \n",
    "        'Frustated':'0', 'Happy':'0', 'InLove':'0', 'Irritable':'0', 'Moody':'0'} \n",
    "\n",
    "    lista_humores = list(dict.fromkeys(rnd_humor))    \n",
    "    #print(lista_humores)\n",
    "\n",
    "    #for key in lista_humores:\n",
    "        #print(key, 'corresponds to', humor_indice[key], ': ' ,humor[humor_indice[key]])\n",
    "    \n",
    "    i=0\n",
    "    for key  in lista_humores:\n",
    "        #print(humor_indice[lista_humores[i]], ':', [1] )        \n",
    "        humores.update({humor_indice[lista_humores[i]]: str(1)}) \n",
    "        i=i+1    \n",
    "    return humores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Angry': '1',\n",
       " 'Anxious': '1',\n",
       " 'Calm': '0',\n",
       " 'Depressed': '0',\n",
       " 'Emotional': '1',\n",
       " 'Energetic': '0',\n",
       " 'Excited': '0',\n",
       " 'Focused': '0',\n",
       " 'Frisky': '0',\n",
       " 'Frustated': '0',\n",
       " 'Happy': '0',\n",
       " 'InLove': '0',\n",
       " 'Irritable': '1',\n",
       " 'Moody': '0'}"
      ]
     },
     "execution_count": 223,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "create_data_humors()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "def create_data_diagnostico(mes_hoje, ano_hoje):     \n",
    "    dia_diag = random.randint(1, 30)\n",
    "    mes_diag = random.randint(1, mes_hoje)\n",
    "    data_diagnostico = str(dia_diag)+'/'+str(mes_diag)+'/'+str(ano_hoje)\n",
    "    return data_diagnostico    \n",
    "    \n",
    "\n",
    "def create_data_nascimento(age, anoatual): \n",
    "    ano = anoatual-age\n",
    "    mes = random.randint(1, 12)\n",
    "    dia = random.randint(1, 30)\n",
    "    data_nascimento = str(dia)+'/'+str(mes)+'/'+str(ano)\n",
    "    return data_nascimento\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'30/7/2022'"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "create_data_diagnostico(8, 2022)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'22/10/1989'"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "create_data_nascimento(33, 2022)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original DataFrame:\n",
      "         date\n",
      "0  17/05/2002\n",
      "1  16/02/1990\n",
      "2  25/09/1980\n",
      "3  11/05/2000\n",
      "4  17/09/1986\n",
      "\n",
      "New DataFrame:\n",
      "         date day month  year\n",
      "0  17/05/2002  17    05  2002\n",
      "1  16/02/1990  16    02  1990\n",
      "2  25/09/1980  25    09  1980\n",
      "3  11/05/2000  11    05  2000\n",
      "4  17/09/1986  17    09  1986\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "df = pd.DataFrame({\n",
    "      'date': ['17/05/2002','16/02/1990','25/09/1980','11/05/2000','17/09/1986']\n",
    "   })\n",
    "print(\"Original DataFrame:\")\n",
    "print(df)\n",
    "df[[\"day\", \"month\", \"year\"]] = df[\"date\"].str.split(\"/\", expand = True)\n",
    "print(\"\\nNew DataFrame:\")\n",
    "print(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   Num      Id Document    Name Surname  Age   DateBirth DateDiagnosis  Acne  \\\n",
      "0    3  User03   User03  User03  User03   25  01/01/1997    05/07/2022   NaN   \n",
      "\n",
      "   Appetite  ... Emotional  Energetic  Excited  Focused  Frisky  Frustated  \\\n",
      "0       NaN  ...         0          0        0        0       0          1   \n",
      "\n",
      "   Happy  InLove  Irritable  Moody  \n",
      "0      0       0          1      0  \n",
      "\n",
      "[1 rows x 43 columns]\n"
     ]
    }
   ],
   "source": [
    "data = {\n",
    "    'Num': [3],  'Id': ['User03'], 'Document': ['User03'], 'Name': ['User03'], \n",
    "    'Surname': ['User03'], 'Age':[25], 'DateBirth':['01/01/1997'], 'DateDiagnosis':['05/07/2022'],\n",
    "    'Acne':[np.nan], 'Appetite':[np.nan], 'Backache':['Mild'], 'Bloating':[np.nan], 'Constipation':[np.nan],\n",
    "    'Cramps':[np.nan], 'Diarrhea':[np.nan], 'Nausea':[np.nan], 'PainDuringSex':[np.nan], \n",
    "    'PelvicPain':[np.nan], 'SexDrive':[np.nan], 'Sick':[np.nan], 'SoreBreasts':[np.nan], \n",
    "    'VaginalPain':[np.nan], 'Dizziness':[np.nan], 'Fatigue':[np.nan], 'Headache':['Severe'], \n",
    "    'HotFlashes':[np.nan], 'Indigestion':['Moderate'], 'Insomnia':['Mild'], 'Migraine':[np.nan], \n",
    "    'Angry':[0], 'Anxious':[1], 'Calm':[0], 'Depressed':[0], 'Emotional':[0], \n",
    "    'Energetic':[0], 'Excited':[0], 'Focused':[0], 'Frisky':[0], \n",
    "    'Frustated':[1], 'Happy':[0], 'InLove':[0], 'Irritable':[1], 'Moody':[0]\n",
    "}\n",
    "df2 = pd.DataFrame(data)\n",
    "print(df2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "data = {\n",
    "    'Num': [0],  'Id': ['User0'], 'Document': ['User0'], 'Name': ['User0'], \n",
    "    'Surname': ['User03'], 'Age':[25], 'DateBirth':['01/01/1997'], 'DateDiagnosis':['05/07/2022'],\n",
    "    'Acne':[np.nan], 'Appetite':[np.nan], 'Backache':['Mild'], 'Bloating':[np.nan], \n",
    "    'Constipation':[np.nan], 'Cramps':[np.nan], 'Diarrhea':[np.nan], 'Nausea':[np.nan], \n",
    "    'PainDuringSex':[np.nan], 'PelvicPain':[np.nan], 'SexDrive':[np.nan], 'Sick':[np.nan], \n",
    "    'SoreBreasts':[np.nan], 'VaginalPain':[np.nan], 'Dizziness':[np.nan], 'Fatigue':[np.nan], \n",
    "    'Headache':['Severe'], 'HotFlashes':[np.nan], 'Indigestion':['Moderate'], \n",
    "    'Insomnia':['Mild'], 'Migraine':[np.nan], \n",
    "    'Angry':[0], 'Anxious':[1], 'Calm':[0], 'Depressed':[0], 'Emotional':[0], \n",
    "    'Energetic':[0], 'Excited':[0], 'Focused':[0], 'Frisky':[0], \n",
    "    'Frustated':[1], 'Happy':[0], 'InLove':[0], 'Irritable':[1], 'Moody':[0]\n",
    "}"
   ]
  }
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