Once the dataset is cleaned, we can begin analyzing the data.
The describe() function in Python can be used to generate a summary of the data.
| print(health_data.describe()) |
Result:
|
|
Duration |
Average_Pulse |
Max_Pulse |
Calorie_Burnage |
Hours_Work |
Hours_Sleep |
|
Count |
10.0 |
10.0 |
10.0 |
10.0 |
10.0 |
10.0 |
|
Mean |
51.0 |
102.5 |
137.0 |
285.0 |
6.6 |
7.5 |
|
Std |
10.49 |
15.4 |
11.35 |
30.28 |
3.63 |
0.53 |
|
Min |
30.0 |
80.0 |
120.0 |
240.0 |
0.0 |
7.0 |
|
25% |
45.0 |
91.25 |
130.0 |
262.5 |
7.0 |
7.0 |
|
50% |
52.5 |
102.5 |
140.0 |
285.0 |
8.0 |
7.5 |
|
75% |
60.0 |
113.75 |
145.0 |
307.5 |
8.0 |
8.0 |
|
Max |
60.0 |
125.0 |
150.0 |
330.0 |
10.0 |
8.0 |
