investigate-a-dataset-project.ipynb

{
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  {
   "cell_type": "markdown",
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   "source": [
    "\n",
    "# Project: Investigate a Dataset (No show up appointment)\n",
    "\n",
    "## Table of Contents\n",
    "<ul>\n",
    "<li><a href=\"#intro\">Introduction</a></li>\n",
    "<li><a href=\"#wrangling\">Data Wrangling</a></li>\n",
    "<li><a href=\"#eda\">Exploratory Data Analysis</a></li>\n",
    "<li><a href=\"#conclusions\">Conclusions</a></li>\n",
    "</ul>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='intro'></a>\n",
    "## Introduction\n",
    "\n",
    "> This dataset collects informationfrom 100k medical appointments inBrazil and is focused on the questionof whether or not patients show upfor their appointment. A number ofcharacteristics about the patient areincluded in each row.●‘Scheduled Day’ tells us on what day the patient set up their appointment.●‘Neighborhood’ indicates thelocation of the hospital.●‘Scholarship’ indicateswhether or not the patient isenrolled in Brasilian welfare program Bolsa Família.●Be careful about the encoding of the last column: it says ‘No’ ifthe patient showed up to their appointment, and ‘Yes’ if they did not show up.\n",
    "\n",
    "<li>Does people who have a scholarship not show up in their appointments?</li>\n",
    "<li> Are no-show appointments associated with a certain gender?</li>\n",
    "<li> Are chronic illnesses like hypertension and diabetes affecting patient's absences?</li>\n",
    "<li> Is alcoholism a prominent factor in patient's absences? Are the absences frequent?</li>\n",
    "<li> Do SMS reminders decrease the number of absences?</li>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='wrangling'></a>\n",
    "## Data Wrangling\n",
    "\n",
    "<li> Convert ScheduledDay and AppointmentDay from 'object' dtype to 'datetime64 </li>\n",
    "<li> Removed AppointmenID as this information is not useful. </li>\n",
    "\n",
    "\n",
    "### General Properties"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PatientId</th>\n",
       "      <th>AppointmentID</th>\n",
       "      <th>Gender</th>\n",
       "      <th>ScheduledDay</th>\n",
       "      <th>AppointmentDay</th>\n",
       "      <th>Age</th>\n",
       "      <th>Neighbourhood</th>\n",
       "      <th>Scholarship</th>\n",
       "      <th>Hipertension</th>\n",
       "      <th>Diabetes</th>\n",
       "      <th>Alcoholism</th>\n",
       "      <th>Handcap</th>\n",
       "      <th>SMS_received</th>\n",
       "      <th>No-show</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2.987250e+13</td>\n",
       "      <td>5642903</td>\n",
       "      <td>F</td>\n",
       "      <td>2016-04-29T18:38:08Z</td>\n",
       "      <td>2016-04-29T00:00:00Z</td>\n",
       "      <td>62</td>\n",
       "      <td>JARDIM DA PENHA</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>No</td>\n",
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       "      <td>M</td>\n",
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       "      <td>2016-04-29T00:00:00Z</td>\n",
       "      <td>56</td>\n",
       "      <td>JARDIM DA PENHA</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>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.262962e+12</td>\n",
       "      <td>5642549</td>\n",
       "      <td>F</td>\n",
       "      <td>2016-04-29T16:19:04Z</td>\n",
       "      <td>2016-04-29T00:00:00Z</td>\n",
       "      <td>62</td>\n",
       "      <td>MATA DA PRAIA</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>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8.679512e+11</td>\n",
       "      <td>5642828</td>\n",
       "      <td>F</td>\n",
       "      <td>2016-04-29T17:29:31Z</td>\n",
       "      <td>2016-04-29T00:00:00Z</td>\n",
       "      <td>8</td>\n",
       "      <td>PONTAL DE CAMBURI</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>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8.841186e+12</td>\n",
       "      <td>5642494</td>\n",
       "      <td>F</td>\n",
       "      <td>2016-04-29T16:07:23Z</td>\n",
       "      <td>2016-04-29T00:00:00Z</td>\n",
       "      <td>56</td>\n",
       "      <td>JARDIM DA PENHA</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      PatientId  AppointmentID Gender          ScheduledDay  \\\n",
       "0  2.987250e+13        5642903      F  2016-04-29T18:38:08Z   \n",
       "1  5.589978e+14        5642503      M  2016-04-29T16:08:27Z   \n",
       "2  4.262962e+12        5642549      F  2016-04-29T16:19:04Z   \n",
       "3  8.679512e+11        5642828      F  2016-04-29T17:29:31Z   \n",
       "4  8.841186e+12        5642494      F  2016-04-29T16:07:23Z   \n",
       "\n",
       "         AppointmentDay  Age      Neighbourhood  Scholarship  Hipertension  \\\n",
       "0  2016-04-29T00:00:00Z   62    JARDIM DA PENHA            0             1   \n",
       "1  2016-04-29T00:00:00Z   56    JARDIM DA PENHA            0             0   \n",
       "2  2016-04-29T00:00:00Z   62      MATA DA PRAIA            0             0   \n",
       "3  2016-04-29T00:00:00Z    8  PONTAL DE CAMBURI            0             0   \n",
       "4  2016-04-29T00:00:00Z   56    JARDIM DA PENHA            0             1   \n",
       "\n",
       "   Diabetes  Alcoholism  Handcap  SMS_received No-show  \n",
       "0         0           0        0             0      No  \n",
       "1         0           0        0             0      No  \n",
       "2         0           0        0             0      No  \n",
       "3         0           0        0             0      No  \n",
       "4         1           0        0             0      No  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load your data and print out a few lines. Perform operations to inspect data\n",
    "#   types and look for instances of missing or possibly errant data.\n",
    "df=pd.read_csv(\"noshowappointments-kagglev2-may-2016.csv\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 110527 entries, 0 to 110526\n",
      "Data columns (total 14 columns):\n",
      " #   Column          Non-Null Count   Dtype  \n",
      "---  ------          --------------   -----  \n",
      " 0   PatientId       110527 non-null  float64\n",
      " 1   AppointmentID   110527 non-null  int64  \n",
      " 2   Gender          110527 non-null  object \n",
      " 3   ScheduledDay    110527 non-null  object \n",
      " 4   AppointmentDay  110527 non-null  object \n",
      " 5   Age             110527 non-null  int64  \n",
      " 6   Neighbourhood   110527 non-null  object \n",
      " 7   Scholarship     110527 non-null  int64  \n",
      " 8   Hipertension    110527 non-null  int64  \n",
      " 9   Diabetes        110527 non-null  int64  \n",
      " 10  Alcoholism      110527 non-null  int64  \n",
      " 11  Handcap         110527 non-null  int64  \n",
      " 12  SMS_received    110527 non-null  int64  \n",
      " 13  No-show         110527 non-null  object \n",
      "dtypes: float64(1), int64(8), object(5)\n",
      "memory usage: 11.8+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['ScheduledDay'] = pd.to_datetime(df['ScheduledDay']).dt.date.astype('datetime64[ns]')\n",
    "df['AppointmentDay'] = pd.to_datetime(df['AppointmentDay']).dt.date.astype('datetime64[ns]')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop('AppointmentID',axis='columns', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 110527 entries, 0 to 110526\n",
      "Data columns (total 13 columns):\n",
      " #   Column          Non-Null Count   Dtype         \n",
      "---  ------          --------------   -----         \n",
      " 0   PatientId       110527 non-null  float64       \n",
      " 1   Gender          110527 non-null  object        \n",
      " 2   ScheduledDay    110527 non-null  datetime64[ns]\n",
      " 3   AppointmentDay  110527 non-null  datetime64[ns]\n",
      " 4   Age             110527 non-null  int64         \n",
      " 5   Neighbourhood   110527 non-null  object        \n",
      " 6   Scholarship     110527 non-null  int64         \n",
      " 7   Hipertension    110527 non-null  int64         \n",
      " 8   Diabetes        110527 non-null  int64         \n",
      " 9   Alcoholism      110527 non-null  int64         \n",
      " 10  Handcap         110527 non-null  int64         \n",
      " 11  SMS_received    110527 non-null  int64         \n",
      " 12  No-show         110527 non-null  object        \n",
      "dtypes: datetime64[ns](2), float64(1), int64(7), object(3)\n",
      "memory usage: 11.0+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Cleaning \n",
    "<li> In this section I removed the negative values in the age column. </li>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
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      "/home/shrouk/anaconda3/envs/tesorflow/lib/python3.7/site-packages/ipykernel_launcher.py:1: FutureWarning: Treating datetime data as categorical rather than numeric in `.describe` is deprecated and will be removed in a future version of pandas. Specify `datetime_is_numeric=True` to silence this warning and adopt the future behavior now.\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n",
      "/home/shrouk/anaconda3/envs/tesorflow/lib/python3.7/site-packages/ipykernel_launcher.py:1: FutureWarning: Treating datetime data as categorical rather than numeric in `.describe` is deprecated and will be removed in a future version of pandas. Specify `datetime_is_numeric=True` to silence this warning and adopt the future behavior now.\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>55.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>9.999816e+14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>115.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           PatientId  Gender         ScheduledDay       AppointmentDay  \\\n",
       "count   1.105270e+05  110527               110527               110527   \n",
       "unique           NaN       2                  111                   27   \n",
       "top              NaN       F  2016-05-03 00:00:00  2016-06-06 00:00:00   \n",
       "freq             NaN   71840                 4238                 4692   \n",
       "first            NaN     NaN  2015-11-10 00:00:00  2016-04-29 00:00:00   \n",
       "last             NaN     NaN  2016-06-08 00:00:00  2016-06-08 00:00:00   \n",
       "mean    1.474963e+14     NaN                  NaN                  NaN   \n",
       "std     2.560949e+14     NaN                  NaN                  NaN   \n",
       "min     3.921784e+04     NaN                  NaN                  NaN   \n",
       "25%     4.172614e+12     NaN                  NaN                  NaN   \n",
       "50%     3.173184e+13     NaN                  NaN                  NaN   \n",
       "75%     9.439172e+13     NaN                  NaN                  NaN   \n",
       "max     9.999816e+14     NaN                  NaN                  NaN   \n",
       "\n",
       "                  Age   Neighbourhood    Scholarship   Hipertension  \\\n",
       "count   110527.000000          110527  110527.000000  110527.000000   \n",
       "unique            NaN              81            NaN            NaN   \n",
       "top               NaN  JARDIM CAMBURI            NaN            NaN   \n",
       "freq              NaN            7717            NaN            NaN   \n",
       "first             NaN             NaN            NaN            NaN   \n",
       "last              NaN             NaN            NaN            NaN   \n",
       "mean        37.088874             NaN       0.098266       0.197246   \n",
       "std         23.110205             NaN       0.297675       0.397921   \n",
       "min         -1.000000             NaN       0.000000       0.000000   \n",
       "25%         18.000000             NaN       0.000000       0.000000   \n",
       "50%         37.000000             NaN       0.000000       0.000000   \n",
       "75%         55.000000             NaN       0.000000       0.000000   \n",
       "max        115.000000             NaN       1.000000       1.000000   \n",
       "\n",
       "             Diabetes     Alcoholism        Handcap   SMS_received No-show  \n",
       "count   110527.000000  110527.000000  110527.000000  110527.000000  110527  \n",
       "unique            NaN            NaN            NaN            NaN       2  \n",
       "top               NaN            NaN            NaN            NaN      No  \n",
       "freq              NaN            NaN            NaN            NaN   88208  \n",
       "first             NaN            NaN            NaN            NaN     NaN  \n",
       "last              NaN            NaN            NaN            NaN     NaN  \n",
       "mean         0.071865       0.030400       0.022248       0.321026     NaN  \n",
       "std          0.258265       0.171686       0.161543       0.466873     NaN  \n",
       "min          0.000000       0.000000       0.000000       0.000000     NaN  \n",
       "25%          0.000000       0.000000       0.000000       0.000000     NaN  \n",
       "50%          0.000000       0.000000       0.000000       0.000000     NaN  \n",
       "75%          0.000000       0.000000       0.000000       1.000000     NaN  \n",
       "max          1.000000       1.000000       4.000000       1.000000     NaN  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe(include='all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>PatientId</th>\n",
       "      <th>Gender</th>\n",
       "      <th>ScheduledDay</th>\n",
       "      <th>AppointmentDay</th>\n",
       "      <th>Age</th>\n",
       "      <th>Neighbourhood</th>\n",
       "      <th>Scholarship</th>\n",
       "      <th>Hipertension</th>\n",
       "      <th>Diabetes</th>\n",
       "      <th>Alcoholism</th>\n",
       "      <th>Handcap</th>\n",
       "      <th>SMS_received</th>\n",
       "      <th>No-show</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>99832</th>\n",
       "      <td>4.659432e+14</td>\n",
       "      <td>F</td>\n",
       "      <td>2016-06-06</td>\n",
       "      <td>2016-06-06</td>\n",
       "      <td>-1</td>\n",
       "      <td>ROMÃO</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>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          PatientId Gender ScheduledDay AppointmentDay  Age Neighbourhood  \\\n",
       "99832  4.659432e+14      F   2016-06-06     2016-06-06   -1         ROMÃO   \n",
       "\n",
       "       Scholarship  Hipertension  Diabetes  Alcoholism  Handcap  SMS_received  \\\n",
       "99832            0             0         0           0        0             0   \n",
       "\n",
       "      No-show  \n",
       "99832      No  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df['Age'] < 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.loc[df['Age'] < 0, 'Age'] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>PatientId</th>\n",
       "      <th>Gender</th>\n",
       "      <th>ScheduledDay</th>\n",
       "      <th>AppointmentDay</th>\n",
       "      <th>Age</th>\n",
       "      <th>Neighbourhood</th>\n",
       "      <th>Scholarship</th>\n",
       "      <th>Hipertension</th>\n",
       "      <th>Diabetes</th>\n",
       "      <th>Alcoholism</th>\n",
       "      <th>Handcap</th>\n",
       "      <th>SMS_received</th>\n",
       "      <th>No-show</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [PatientId, Gender, ScheduledDay, AppointmentDay, Age, Neighbourhood, Scholarship, Hipertension, Diabetes, Alcoholism, Handcap, SMS_received, No-show]\n",
       "Index: []"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df['Age'] < 0] #now there is no -ve values in Age column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PatientId         0\n",
       "Gender            0\n",
       "ScheduledDay      0\n",
       "AppointmentDay    0\n",
       "Age               0\n",
       "Neighbourhood     0\n",
       "Scholarship       0\n",
       "Hipertension      0\n",
       "Diabetes          0\n",
       "Alcoholism        0\n",
       "Handcap           0\n",
       "SMS_received      0\n",
       "No-show           0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='eda'></a>\n",
    "## Exploratory Data Analysis\n",
    "\n",
    "\n",
    "### Plotting the histogram of all numerical features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "#This function for counting the values in a specific column\n",
    "def ValueCount(ColName):\n",
    "    print (df[ColName].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    99666\n",
      "1    10861\n",
      "Name: Scholarship, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "ValueCount('Scholarship')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0      3540\n",
      "1      2273\n",
      "52     1746\n",
      "49     1652\n",
      "53     1651\n",
      "       ... \n",
      "98        6\n",
      "115       5\n",
      "100       4\n",
      "102       2\n",
      "99        1\n",
      "Name: Age, Length: 103, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "ValueCount('Age')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    75045\n",
      "1    35482\n",
      "Name: SMS_received, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "ValueCount('SMS_received')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<AxesSubplot:title={'center':'PatientId'}>,\n",
       "        <AxesSubplot:title={'center':'Age'}>,\n",
       "        <AxesSubplot:title={'center':'Scholarship'}>],\n",
       "       [<AxesSubplot:title={'center':'Hipertension'}>,\n",
       "        <AxesSubplot:title={'center':'Diabetes'}>,\n",
       "        <AxesSubplot:title={'center':'Alcoholism'}>],\n",
       "       [<AxesSubplot:title={'center':'Handcap'}>,\n",
       "        <AxesSubplot:title={'center':'SMS_received'}>, <AxesSubplot:>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.hist(figsize=(20,10),bins=50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Females visit doctors more than males."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Show-up')"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Continue to explore the data to address your additional research\n",
    "#   questions. Add more headers as needed if you have more questions to\n",
    "#   investigate.\n",
    "plt.figure(figsize=(20,9))\n",
    "df.groupby(['Gender'])['Gender'].count().sort_values(ascending=False).plot(kind='bar')\n",
    "plt.title('Male vs Female')\n",
    "plt.ylabel('Show-up')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Females don't show up on their appointments any more than males."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Show-up')"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1440x792 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20, 11))\n",
    "df.groupby(['Gender', 'No-show'])['Gender'].count().unstack('No-show').plot(kind='bar', stacked=True)\n",
    "plt.title('Male vs Female attendace')\n",
    "plt.ylabel('Show-up')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## From the below correlation heatmap it shows that the most correlated factors which are actually slightly correlated for not showing up is:\n",
    "<li> Receiving an SMS! which is so weired! </li>\n",
    "<li> having a handicap </li>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9,5))\n",
    "sns.heatmap(df.copy().corr().round(3), annot = True)\n",
    "plt.title('Correlation heatmap', size='16')\n",
    "plt.xticks(rotation='45');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# (Question 1) Does people who have a scholarship not show up in their appointments?\n",
    "## Most of the people who have a scholarship show up in their appointments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Show-up')"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1440x792 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20, 11))\n",
    "df.groupby(['Scholarship', 'No-show'])['Scholarship'].count().unstack('No-show').plot(kind='bar', stacked=True)\n",
    "plt.title('Scholarship effect')\n",
    "plt.ylabel('Show-up')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# (Question 2) Are chronic illnesses like hypertension and diabetes affecting patient's absences?\n",
    "## Most of the people suffering from hipertension show up in their appointments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Show-up')"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1440x792 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZIAAAETCAYAAAAcboCHAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8vihELAAAACXBIWXMAAAsTAAALEwEAmpwYAAAdm0lEQVR4nO3dfbxVZZ338c8XUFB5KB4iBfXgLZVI5AOhkmCJE1Qmapr4hIre9KCR3egMVo7cMzGjRaOSk2SikWMKISpqCj6MKUUiKGKAJiOKR0kRkNBCBX/zx74Obbabczasvdnuc77v12u/ztrXWtdav7Wz8+W61trrKCIwMzPbUa2qXYCZmdU2B4mZmWXiIDEzs0wcJGZmlomDxMzMMnGQmJlZJg4Sa1YkLZH02WrXkYWk0yXNqcJxPy7pSUkbJI2RtJukuyStl/TrnV2P1Q75eyRWKyS9AJwXEQ/ktZ2d2o7cCccfD+wfEWdU+ljVIGkK8JeI+E56fybwLWBgRGzKsN/xNOPPzTwiMSuJpDbVrmEn2BdYUvD+T1lCxFoGB4k1K5JekHRMWh4vaYakaWm65glJn8rbdi9Jt0laLWmFpDF56xr6/pekvwBfB74LnCLpTUlPpe06SZoiaZWklyX9QFLrtO5sSXMlTZS0Lh3jC3nHOFvS86m2FZJOz++Xt91ASY+nKabHJQ3MW/ewpH+V9Lu0nzmSujby+RwraZGkNyT9XlK/1P4Q8DngmnR+twD/nHe+56btRklals5ntqR98/Z9oKT7Ja2V9Kqk70oaVuxzs+bFQWLN3XDg10Bn4FfAHZJ2kdQKuAt4CugBDAEulDS0oO8M4EPAFODfgGkR0T4iGgJpKrAJ2B84GPg8cF7ePg4DngW6Aj8EpihnD2AS8IWI6AAMBBYVFi+pM3BP2rYL8B/APZK65G12GnAO8BFgV+CiYh+EpEOAG4CvpX39DJglqW1EHA08ClyQzu/UgvOdIul4cqFwItAtbX9L2ncH4AHgPmCv9Hk8GBH3beNzs2bEQWK15o70r+k3JL0B/LSJ7RdGxIyIeJfcL+F2wOHAp4FuEfEvEfFORDwP/BwYkdd3XkTcERHvRcTfCncsqTvwBeDCiHgrIl4DrizYx4sR8fOI2EwudPYEuqd17wF9Je0WEasiIn9aqcGXgOci4qaI2BQRtwDPAF/O2+bGiPhTqnE6cNA2Pov/C/wsIh6LiM0RMRV4O30epfga8O8RsSxNd/0bcFAalRwL/DkifhwRGyNiQ0Q8VuJ+rcY5SKzWHB8RH2p4Ad9sYvuXGhYi4j2gnty/mPcF9ioIpe/y91/yW/Xdhn2BXYBVefv4GbmRQYM/5x3/r2mxfUS8BZxCbspslaR7JH2iyDH2Al4saHuR3CjqfccA/gq0b6TesQXnvHc6Rin2Ba7O67sWUKplb+B/StyPNTMt4QKitWx7Nyyk6ayewCvkpqNWRETvRvoW3tJY+P4lcv+i77ojF6QjYjYwW9JuwA/IjYgGFWz2Crlf4Pn2ITeFtL1eAiZExIQd6Jvf/+bCFWlUcuo2+vnW0GbOIxJr7g6VdGK66+pCcr/4/wDMB/4i6Z/S9yVaS+or6dON7OtVoC4FEhGxCpgD/FhSR0mtJP0fSUc1VZSk7pKOS9dK3gbeBDYX2fQ3wMcknSapjaRTgD7A3SV/An/3c+Drkg5ruE4j6Uvp+kYpJgOXSDownUMnSSendXcDH5V0oaS2kjpIOiyt2+pzs+bH/8Nac3cnuSmkdcCZwIkR8W66ZvFlctcTVgCvA9cDnRrZV8OX8tZIeiItjyR3gXtpOsYMctdBmtIKGEtuxLEWOIoi03QRsYbc9YexwBrgH4FjI+L1Eo5RuK8F5K6TXJNqXQ6cvR39bweuAG5Nd7L9kdw1IiJiA/AP5D7TPwPPkbsLDIp/btaM+AuJ1mzJX4Qz2yk8IjEzs0wcJGZmlomntszMLBOPSMzMLBMHiZmZZdLivpDYtWvXqKurq3YZZmY1ZeHCha9HRLdi61pckNTV1bFgwYJql2FmVlMkFT6qZwtPbZmZWSYOEjMzy8RBYmZmmbS4ayRmZuX27rvvUl9fz8aNG6tdSmbt2rWjZ8+e7LLLLiX3cZCYmWVUX19Phw4dqKurQ1K1y9lhEcGaNWuor6+nV69eJffz1JaZWUYbN26kS5cuNR0iAJLo0qXLdo+sHCRmZmVQ6yHSYEfOw0FiZlYBkhg7duyW9xMnTmT8+PGZ93v22WczY8aMzPspJ18j+aAa39jfV7LtNn59tSuwFqZt27bMnDmTSy65hK5du1a7nIryiMTMrALatGnD6NGjufLKK9+37sUXX2TIkCH069ePIUOGsHLlyqL7GDduHH369KFfv35cdNFFW9ofeeQRBg4cyH777bdldBIRXHzxxfTt25dPfvKTTJs2DYBvfvObzJo1C4ATTjiBUaNGATBlyhS+//3vl+VcHSRmZhVy/vnnc/PNN7N+/dYj4gsuuICRI0eyePFiTj/9dMaMGfO+vmvXruX2229nyZIlLF68eKtf+qtWrWLu3LncfffdjBs3DoCZM2eyaNEinnrqKR544AEuvvhiVq1axeDBg3n00UcBePnll1m6dCkAc+fOZdCgQWU5TweJmVmFdOzYkZEjRzJp0qSt2ufNm8dpp50GwJlnnsncuXOL9m3Xrh3nnXceM2fOZPfdd9+y7vjjj6dVq1b06dOHV199FcgFw6mnnkrr1q3p3r07Rx11FI8//jiDBg3i0UcfZenSpfTp04fu3buzatUq5s2bx8CBA8tyng4SM7MKuvDCC5kyZQpvvfXWNrdpuFNq6NChHHTQQZx33nm0adOG+fPn85WvfIU77riDYcOGbdm+bdu2W5Yb/jjhtv5IYY8ePVi3bh333XcfgwcPZtCgQUyfPp327dvToUOHcpyig8TMrJI6d+7MV7/6VaZMmbKlbeDAgdx6660A3HzzzRx55JEAzJ49m0WLFnH99dfz5ptvsn79er74xS9y1VVXsWjRokaPM3jwYKZNm8bmzZtZvXo1jzzyCAMGDADgiCOO4KqrrtoSJBMnTizbtBb4ri0zs4obO3Ys11xzzZb3kyZNYtSoUfzoRz+iW7du3Hjjje/rs2HDBoYPH87GjRuJiKIX7fOdcMIJzJs3j0996lNI4oc//CEf/ehHARg0aBBz5sxh//33Z99992Xt2rVlDZIW9zfb+/fvHzXx90h8+295+fZfq6Bly5ZxwAEHVLuMsil2PpIWRkT/Ytt7asvMzDJxkJiZWSYOEjMzy8RBYmZmmThIzMwsEweJmZll4iAxM2sGKvXY+lL4C4lmZmVWN+6esu7vhcu/1OQ21XxsvUckZmbNQDkeW7+jKhokkr4jaYmkP0q6RVI7SZ0l3S/pufTzw3nbXyJpuaRnJQ3Naz9U0tNp3SSlJ5xJaitpWmp/TFJdJc/HzOyDLMtj67OoWJBI6gGMAfpHRF+gNTACGAc8GBG9gQfTeyT1SesPBIYBP5XUOu3uWmA00Du9Gh6DeS6wLiL2B64ErqjU+ZiZfdBleWx9FpWe2moD7CapDbA78AowHJia1k8Fjk/Lw4FbI+LtiFgBLAcGSNoT6BgR8yL3YLBfFvRp2NcMYEjDaMXMrCXansfWl0vFgiQiXgYmAiuBVcD6iJgDdI+IVWmbVcBHUpcewEt5u6hPbT3ScmH7Vn0iYhOwHuhSifMxM6sF2/PY+nKp5NTWh8mNGHoBewF7SDqjsS5F2qKR9sb6FNYyWtICSQtWr17deOFmZjVu7NixvP7661veT5o0iRtvvJF+/fpx0003cfXVV5f1eJW8/fcYYEVErAaQNBMYCLwqac+IWJWmrV5L29cDe+f170luKqw+LRe25/epT9NnnYC1hYVExHXAdZB7jHx5Ts/MrLhSbtcttzfffHPLcvfu3fnrX/+65X1dXR0PPfRQxY5dyWskK4HDJe2erlsMAZYBs4Cz0jZnAXem5VnAiHQnVi9yF9Xnp+mvDZIOT/sZWdCnYV8nAQ9FS/sDK2ZmVVaxEUlEPCZpBvAEsAl4ktyooD0wXdK55MLm5LT9EknTgaVp+/MjYnPa3TeAXwC7AfemF8AU4CZJy8mNREZU6nzMzKy4in6zPSIuAy4raH6b3Oik2PYTgAlF2hcAfYu0byQFkZmZVYe/2W5mZpk4SMzMLBMHiZmZZeIgMTOrcRHBkUceyb333rulbfr06QwbNqyRXuXjx8ibmZXb+E5l3t/6RldLYvLkyZx88sl87nOfY/PmzXzve9/jvvvuK28d2+AgMTNrBvr27cuXv/xlrrjiCt566y3OOOMMJkyYwNNPP82mTZsYP348w4cPZ8mSJZxzzjm88847vPfee9x222307t0707EdJGZmzcRll13GIYccwq677sqxxx7L0UcfzQ033MAbb7zBgAEDOOaYY5g8eTLf/va3Of3003nnnXfYvHlz0ztugoPEzKyZ2GOPPTjllFNo374906dP56677mLixIkAbNy4kZUrV3LEEUcwYcIE6uvrOfHEEzOPRsBBYmbWrLRq1YpWrVoREdx22218/OMf32r9AQccwGGHHcY999zD0KFDuf766zn66KOzHTNTbzMz+0AaOnQoP/nJT2h4/OCTTz4JwPPPP89+++3HmDFjOO6441i8eHHmYzlIzMyaoUsvvZR3332Xfv360bdvXy699FIApk2bRt++fTnooIN45plnGDlyZOZjqaU9LLd///6xYMGCapfRtHLfPtjSNXH7pFkWy5Yt44ADDqh2GWVT7HwkLYyI/sW294jEzMwycZCYmVkmDhIzM8vEQWJmVgbN5XrzjpyHg8TMLKN27dqxZs2amg+TiGDNmjW0a9duu/r5C4lmZhn17NmT+vp6Vq9eXe1SMmvXrh09e/bcrj4Okg+ouo2/qnYJzcoL1S7AmrVddtmFXr16VbuMqvHUlpmZZeIgMTOzTBwkZmaWiYPEzMwycZCYmVkmDhIzM8vEQWJmZpk4SMzMLBMHiZmZZeIgMTOzTBwkZmaWiYPEzMwycZCYmVkmDhIzM8vEQWJmZpk4SMzMLBMHiZmZZeIgMTOzTBwkZmaWSUWDRNKHJM2Q9IykZZKOkNRZ0v2Snks/P5y3/SWSlkt6VtLQvPZDJT2d1k2SpNTeVtK01P6YpLpKno+Zmb1fpUckVwP3RcQngE8By4BxwIMR0Rt4ML1HUh9gBHAgMAz4qaTWaT/XAqOB3uk1LLWfC6yLiP2BK4ErKnw+ZmZWoGJBIqkjMBiYAhAR70TEG8BwYGrabCpwfFoeDtwaEW9HxApgOTBA0p5Ax4iYFxEB/LKgT8O+ZgBDGkYrZma2c1RyRLIfsBq4UdKTkq6XtAfQPSJWAaSfH0nb9wBeyutfn9p6pOXC9q36RMQmYD3QpbAQSaMlLZC0YPXq1eU6PzMzo7JB0gY4BLg2Ig4G3iJNY21DsZFENNLeWJ+tGyKui4j+EdG/W7dujVdtZmbbpZJBUg/UR8Rj6f0McsHyapquIv18LW/7vfP69wReSe09i7Rv1UdSG6ATsLbsZ2JmZttUsSCJiD8DL0n6eGoaAiwFZgFnpbazgDvT8ixgRLoTqxe5i+rz0/TXBkmHp+sfIwv6NOzrJOChdB3FzMx2kjYV3v+3gJsl7Qo8D5xDLrymSzoXWAmcDBARSyRNJxc2m4DzI2Jz2s83gF8AuwH3phfkLuTfJGk5uZHIiAqfj5mZFahokETEIqB/kVVDtrH9BGBCkfYFQN8i7RtJQWRmZtXhb7abmVkmDhIzM8vEQWJmZpk4SMzMLBMHiZmZZeIgMTOzTEq+/VfSIcCR5B5B8ruIeKJiVZmZWc0oaUQi6Z/JPWW3C9CV3IMYv1/JwszMrDaUOiI5FTg4fQEQSZcDTwA/qFRhZmZWG0q9RvIC0C7vfVvgf8pejZmZ1ZxSRyRvA0sk3U/uGsk/AHMlTQKIiDEVqs/MzD7gSg2S29OrwcPlL8XMzGpRSUESEVOb3srMzFqikoJE0gqK/+XB/cpekZmZ1ZRSp7byHwXfjtyj2zuXvxwzM6s1Jd21FRFr8l4vR8RVwNGVLc3MzGpBqVNbh+S9bUVuhNKhIhWZmVlNKXVq68d5y5uAFcBXy1+OmZnVmlLv2vpcpQsxM7PatN1P/5V0dyUKMTOz2rQjj5HvUfYqzMysZu1IkDxZ9irMzKxmlfoY+aMl7Q4QEaMqW5KZmdWSUu/aOhuYLGkN8Gh6zY2IdZUqzMzMakOpd22NBJC0F3AS8J/AXqX2NzOz5qvULySeAQwCPgm8DlxDblRiZmYtXKkjiqvI/SGrycB/R8QLlSrIzMxqS6nP2uoKjCL3wMYJkuZLuqmilZmZWU0o9a6tjsA+wL5AHdAJeK9yZZmZWa0odWprbt7rmoior1xJZmZWS0q9a6sfgKQOFPkDV2Zm1nKVOrXVV9KTwB+BpZIWSupb2dLMzKwWlPqIlOuA/xcR+0bEPsDY1GZmZi1cqUGyR0T8d8ObiHgY2KMiFZmZWU0p9WL785IuBRpu+T2D3B+3MjOzFq7UEckooBswE7g9LZ9TqaLMzKx2lHrX1jpgTIVrMTOzGlTqXVsfk3SdpDmSHmp4ldi3taQnG/6yoqTOku6X9Fz6+eG8bS+RtFzSs5KG5rUfKunptG6SJKX2tpKmpfbHJNVt19mbmVlmpU5t/ZrcH7T6PnBx3qsU3waW5b0fBzwYEb2BB9N7JPUBRgAHAsOAn0pqnfpcC4wGeqfXsNR+LrAuIvYHrgSuKLEmMzMrk1KDZFNEXBsR8yNiYcOrqU6SegJfAq7Pax4OTE3LU4Hj89pvjYi3I2IFsBwYIGlPoGNEzIuIAH5Z0KdhXzOAIQ2jFTMz2zkaDZI0DdUZuEvSNyXt2dCW2ptyFfCPbP1cru4RsQog/fxIau8BvJS3XX1q65GWC9u36hMRm4D1QJcS6jIzszJp6mL7QnKPRGn4V/5FBev321ZHSccCr0XEQkmfLaGWYiOJaKS9sT6FtYwmNzXGPvvsU0IpZmZWqqamtk4BPhMRvSKiF/D/yT0m5W6gfxN9PwMcJ+kF4FbgaEn/BbyapqtIP19L29cDe+f17wm8ktp7Fmnfqo+kNuSeSry2sJCIuC4i+kdE/27dujVRtpmZbY+mgmQy8DaApMHAv5O7JrGeJh6REhGXRETPiKgjdxH9oYg4A5gFnJU2Owu4My3PAkakO7F6kbuoPj9Nf22QdHi6/jGyoE/Dvk5Kx/BDJc3MdqKmprZaR0TDv/BPAa6LiNuA2yQt2sFjXg5Ml3QusBI4GSAilkiaDiwFNgHnR8Tm1OcbwC+A3YB70wtgCnCTpOXkRiIjdrAmMzPbQU0GiaQ26UL2ENJ1hhL7bpGezfVwWl6T9lVsuwnAhCLtC4D3PW04IjaSgsjMzKqjqTC4BfitpNeBvwGPAkjan9z0lpmZtXCNBklETJD0ILAnMCfv+kMr4FuVLs7MzD74mpyeiog/FGn7U2XKMTOzWlPqN9vNzMyKcpCYmVkmDhIzM8vEQWJmZpk4SMzMLBMHiZmZZeIgMTOzTBwkZmaWiYPEzMwycZCYmVkmDhIzM8vEQWJmZpk4SMzMLBMHiZmZZeIgMTOzTBwkZmaWiYPEzMwycZCYmVkmDhIzM8vEQWJmZpk4SMzMLBMHiZmZZeIgMTOzTBwkZmaWiYPEzMwycZCYmVkmDhIzM8vEQWJmZpk4SMzMLBMHiZmZZeIgMTOzTBwkZmaWiYPEzMwycZCYmVkmDhIzM8ukTaV2LGlv4JfAR4H3gOsi4mpJnYFpQB3wAvDViFiX+lwCnAtsBsZExOzUfijwC2A34DfAtyMiJLVNxzgUWAOcEhEvVOqczAwY36naFTQv49dXu4LMKjki2QSMjYgDgMOB8yX1AcYBD0ZEb+DB9J60bgRwIDAM+Kmk1mlf1wKjgd7pNSy1nwusi4j9gSuBKyp4PmZmVkTFgiQiVkXEE2l5A7AM6AEMB6amzaYCx6fl4cCtEfF2RKwAlgMDJO0JdIyIeRER5EYg+X0a9jUDGCJJlTonMzN7v51yjURSHXAw8BjQPSJWQS5sgI+kzXoAL+V1q09tPdJyYftWfSJiE7Ae6FKRkzAzs6IqHiSS2gO3ARdGxF8a27RIWzTS3lifwhpGS1ogacHq1aubKtnMzLZDRYNE0i7kQuTmiJiZml9N01Wkn6+l9npg77zuPYFXUnvPIu1b9ZHUBugErC2sIyKui4j+EdG/W7du5Tg1MzNLKhYk6VrFFGBZRPxH3qpZwFlp+Szgzrz2EZLaSupF7qL6/DT9tUHS4WmfIwv6NOzrJOChdB3FzMx2kord/gt8BjgTeFrSotT2XeByYLqkc4GVwMkAEbFE0nRgKbk7vs6PiM2p3zf4++2/96YX5ILqJknLyY1ERlTwfMzMrIiKBUlEzKX4NQyAIdvoMwGYUKR9AdC3SPtGUhCZ2c5Rt/FX1S6hWXmh2gWUgb/ZbmZmmThIzMwsEweJmZll4iAxM7NMHCRmZpaJg8TMzDJxkJiZWSYOEjMzy8RBYmZmmThIzMwsEweJmZll4iAxM7NMHCRmZpaJg8TMzDJxkJiZWSYOEjMzy8RBYmZmmThIzMwsEweJmZll4iAxM7NMHCRmZpaJg8TMzDJxkJiZWSYOEjMzy8RBYmZmmThIzMwsEweJmZll4iAxM7NMHCRmZpaJg8TMzDJxkJiZWSYOEjMzy8RBYmZmmThIzMwsEweJmZll4iAxM7NMHCRmZpaJg8TMzDKp+SCRNEzSs5KWSxpX7XrMzFqamg4SSa2B/wS+APQBTpXUp7pVmZm1LDUdJMAAYHlEPB8R7wC3AsOrXJOZWYvSptoFZNQDeCnvfT1wWOFGkkYDo9PbNyU9uxNqaym6Aq9Xu4im6IpqV2BV4P82y2vfba2o9SBRkbZ4X0PEdcB1lS+n5ZG0ICL6V7sOs0L+b3PnqfWprXpg77z3PYFXqlSLmVmLVOtB8jjQW1IvSbsCI4BZVa7JzKxFqemprYjYJOkCYDbQGrghIpZUuayWxlOG9kHl/zZ3EkW875KCmZlZyWp9asvMzKrMQWJmZpk4SMzMLJOavthuO5ekT5B7ckAPct/XeQWYFRHLqlqYmVWVRyRWEkn/RO4RNALmk7v1WsAtflimfZBJOqfaNTR3vmvLSiLpT8CBEfFuQfuuwJKI6F2dyswaJ2llROxT7TqaM09tWaneA/YCXixo3zOtM6saSYu3tQrovjNraYkcJFaqC4EHJT3H3x+UuQ+wP3BBtYoyS7oDQ4F1Be0Cfr/zy2lZHCRWkoi4T9LHyD26vwe5/4PWA49HxOaqFmcGdwPtI2JR4QpJD+/0aloYXyMxM7NMfNeWmZll4iAxM7NMHCRmBSS9WfD+bEnXpOWvSxpZpuPUSTqtHPsq2G/ZajQrhS+2m22HiJhcjv1IagPUAacBvyrHPhuUq0azUnlEYrYdJI2XdFFafljSVZJ+L+mPkgak9j0k3SDpcUlPShqe2s+W9GtJdwFzgMuBQZIWSfqOpNaSfpT6LZb0tdTvs+lYMyQ9I+lmSUrrLpe0NG0/sUiNB0n6Q1p/u6QP59V+haT5kv4kadBO/iitGfGIxOz9dpO0KO99Z7b9lzf3iIiBkgYDNwB9ge8BD0XEKEkfAuZLeiBtfwTQLyLWSvoscFFEHAsgaTSwPiI+Lakt8DtJc1K/g4EDyT3f7HfAZyQtBU4APhERkY5V6JfAtyLit5L+BbiM3HeCANpExABJX0ztx5T4+ZhtxUFi9n5/i4iDGt5IOhvov41tbwGIiEckdUy/zD8PHNcwKgDakfvyJsD9EbF2G/v6PNBP0knpfSegN/AOMD8i6lM9i8hNi/0B2AhcL+kect+l2EJSJ+BDEfHb1DQV+HXeJjPTz4Vpf2Y7xEFilk3hF7GC3Jc1vxIRz+avkHQY8FYj+xK50cPsgn6fBd7Oa9pMbjSxKU2nDQFGkHvCwNHbUXvDPjfj3wWWga+RmGVzCoCkI8lNS60HZgPfyruOcfA2+m4AOuS9nw18Q9Iuqd/HJO2xrQNLag90iojfkJuuOih/faplXd71jzOB32JWZv5XiFk26yT9HugIjEpt/wpcBSxOYfICcGyRvouBTZKeAn4BXE1uiumJ1G81cHwjx+4A3CmpHbnRzHeKbHMWMFnS7sDzgB+pbmXnR6SY7aD0DKeLImJBtWsxqyZPbZmZWSYekZiZWSYekZiZWSYOEjMzy8RBYmZmmThIzMwsEweJmZll4iAxM7NM/hdCG+SbNg1I0QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20, 11))\n",
    "df.groupby(['Hipertension', 'No-show'])['Hipertension'].count().unstack('No-show').plot(kind='bar', stacked=True)\n",
    "plt.title('Hipertension effect')\n",
    "plt.ylabel('Show-up')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# (Question 3) Are chronic illnesses like hypertension and diabetes affecting patient's absences?\n",
    "## Most of the people suf\n",
    "## Most of the people suffering  from diabetes show up in their appointments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Show-up')"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1440x792 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20, 11))\n",
    "df.groupby(['Diabetes', 'No-show'])['Diabetes'].count().unstack('No-show').plot(kind='bar', stacked=True)\n",
    "plt.title('Diabetes effect')\n",
    "plt.ylabel('Show-up')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# (Question 4) Is alcoholism a prominent factor in patient's absences? Are the absences frequent?\n",
    "## Most of the people suffering from alcoholism show up on their appointments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Show-up')"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1440x792 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20, 11))\n",
    "df.groupby(['Alcoholism', 'No-show'])['Alcoholism'].count().unstack('No-show').plot(kind='bar', stacked=True)\n",
    "plt.title('Alcoholism effect')\n",
    "plt.ylabel('Show-up')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# (Question 5) Does people who have handicap not show up in their appointments?\n",
    "## All of the people that have handicap show up in their appointments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Show-up')"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1440x792 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20, 11))\n",
    "df.groupby(['Handcap', 'No-show'])['Handcap'].count().unstack('No-show').plot(kind='bar', stacked=True)\n",
    "plt.title('Handicap effect')\n",
    "plt.ylabel('Show-up')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# (Question 6) Do SMS reminders decrease the number of absences?\n",
    "## People who recived an SMS committed to their appointments more than those who didn't recive."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Show-up')"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1440x792 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20, 11))\n",
    "df.groupby(['SMS_received', 'No-show'])['SMS_received'].count().unstack('No-show').plot(kind='bar', stacked=True)\n",
    "plt.title('Reciving an SMS effect')\n",
    "plt.ylabel('Show-up')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='conclusions'></a>\n",
    "## Conclusions\n",
    "# Results\n",
    "<li> People who recived an SMS committed to their appointments more than those who didn't recive.</li>\n",
    "<li> All of the people that have handicap show up in their appointments.</li>\n",
    "<li> Most of the people suffering from alcoholism show up on their appointments.</li>\n",
    "<li> Most of the people suffering  from diabetes show up in their appointments.</li>\n",
    "<li> Most of the people suffering from hipertension show up in their appointments.</li>\n",
    "<li> Most of the people who have a scholarship show up in their appointments.</li>\n",
    "<li> Females don't show up on their appointments any more than males.</li>\n",
    "\n",
    "# Limitiations\n",
    "<li> Can't show strong correlations between factors since most of the data is categorical. </li>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}