<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>Name</th>
      <th>Age</th>
      <th>Gender</th>
      <th>Blood Type</th>
      <th>Medical Condition</th>
      <th>Date of Admission</th>
      <th>Doctor</th>
      <th>Hospital</th>
      <th>Insurance Provider</th>
      <th>Billing Amount</th>
      <th>Room Number</th>
      <th>Admission Type</th>
      <th>Discharge Date</th>
      <th>Medication</th>
      <th>Test Results</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>Bobby JacksOn</td>
      <td>30</td>
      <td>Male</td>
      <td>B-</td>
      <td>Cancer</td>
      <td>2024-01-31</td>
      <td>Matthew Smith</td>
      <td>Sons and Miller</td>
      <td>Blue Cross</td>
      <td>18856.281306</td>
      <td>328</td>
      <td>Urgent</td>
      <td>2024-02-02</td>
      <td>Paracetamol</td>
      <td>Normal</td>
    </tr>
    <tr>
      <th>1</th>
      <td>LesLie TErRy</td>
      <td>62</td>
      <td>Male</td>
      <td>A+</td>
      <td>Obesity</td>
      <td>2019-08-20</td>
      <td>Samantha Davies</td>
      <td>Kim Inc</td>
      <td>Medicare</td>
      <td>33643.327287</td>
      <td>265</td>
      <td>Emergency</td>
      <td>2019-08-26</td>
      <td>Ibuprofen</td>
      <td>Inconclusive</td>
    </tr>
    <tr>
      <th>2</th>
      <td>DaNnY sMitH</td>
      <td>76</td>
      <td>Female</td>
      <td>A-</td>
      <td>Obesity</td>
      <td>2022-09-22</td>
      <td>Tiffany Mitchell</td>
      <td>Cook PLC</td>
      <td>Aetna</td>
      <td>27955.096079</td>
      <td>205</td>
      <td>Emergency</td>
      <td>2022-10-07</td>
      <td>Aspirin</td>
      <td>Normal</td>
    </tr>
    <tr>
      <th>3</th>
      <td>andrEw waTtS</td>
      <td>28</td>
      <td>Female</td>
      <td>O+</td>
      <td>Diabetes</td>
      <td>2020-11-18</td>
      <td>Kevin Wells</td>
      <td>Hernandez Rogers and Vang,</td>
      <td>Medicare</td>
      <td>37909.782410</td>
      <td>450</td>
      <td>Elective</td>
      <td>2020-12-18</td>
      <td>Ibuprofen</td>
      <td>Abnormal</td>
    </tr>
    <tr>
      <th>4</th>
      <td>adrIENNE bEll</td>
      <td>43</td>
      <td>Female</td>
      <td>AB+</td>
      <td>Cancer</td>
      <td>2022-09-19</td>
      <td>Kathleen Hanna</td>
      <td>White-White</td>
      <td>Aetna</td>
      <td>14238.317814</td>
      <td>458</td>
      <td>Urgent</td>
      <td>2022-10-09</td>
      <td>Penicillin</td>
      <td>Abnormal</td>
    </tr>
  </tbody>
</table>
</div>

            Name  Age  Gender Blood Type Medical Condition Date of Admission  \
0  Bobby JacksOn   30    Male         B-            Cancer        2024-01-31   
1   LesLie TErRy   62    Male         A+           Obesity        2019-08-20   
2    DaNnY sMitH   76  Female         A-           Obesity        2022-09-22   
3   andrEw waTtS   28  Female         O+          Diabetes        2020-11-18   
4  adrIENNE bEll   43  Female        AB+            Cancer        2022-09-19   

             Doctor                    Hospital Insurance Provider  \
0     Matthew Smith             Sons and Miller         Blue Cross   
1   Samantha Davies                     Kim Inc           Medicare   
2  Tiffany Mitchell                    Cook PLC              Aetna   
3       Kevin Wells  Hernandez Rogers and Vang,           Medicare   
4    Kathleen Hanna                 White-White              Aetna   

   Billing Amount  Room Number Admission Type Discharge Date   Medication  \
0    18856.281306          328         Urgent     2024-02-02  Paracetamol   
1    33643.327287          265      Emergency     2019-08-26    Ibuprofen   
2    27955.096079          205      Emergency     2022-10-07      Aspirin   
3    37909.782410          450       Elective     2020-12-18    Ibuprofen   
4    14238.317814          458         Urgent     2022-10-09   Penicillin   

   Test Results  
0        Normal  
1  Inconclusive  
2        Normal  
3      Abnormal  
4      Abnormal  

Medical Condition
Arthritis       9308
Diabetes        9304
Hypertension    9245
Obesity         9231
Cancer          9227
Asthma          9185
Name: count, dtype: int64

count    9304.000000
mean       51.554170
std        19.425088
min        14.000000
25%        35.000000
50%        52.000000
75%        68.000000
max        89.000000
Name: Age, dtype: float64

Exploring Medical Conditions in Healthcare Dataset

What are the most common medical conditions?

Can you show the distribution of medical conditions visually?

Can you show the distribution of ages for patients with Diabetes?