Question

#Plot a histogram of Height using the histplot function
from plotting import *

Height=[65.78, 71.52, 69.4, 68.22, 67.79, 68.7, 69.8, 70.01, 67.9, 66.78,
66.49, 67.62, 68.3, 67.12, 68.28, 71.09, 66.46, 68.65, 71.23, 67.13, 67.83,
68.88, 63.48, 68.42, 67.63, 67.21, 70.84, 67.49, 66.53, 65.44, 69.52, 65.81,
67.82, 70.6, 71.8, 69.21, 66.8, 67.66, 67.81, 64.05, 68.57, 65.18, 69.66, 67.97,
65.98, 68.67, 66.88, 67.7, 69.82, 69.09]
Weight=[112.99, 136.49, 153.03, 142.34, 144.3, 123.3, 141.49, 136.46,
112.37, 120.67, 127.45, 114.14, 125.61, 122.46, 116.09, 140.0, 129.5, 142.97,
137.9, 124.04, 141.28, 143.54, 97.9, 129.5, 141.85, 129.72, 142.42, 131.55,
108.33, 113.89, 103.3, 120.75, 125.79, 136.22, 140.1, 128.75, 141.8, 121.23,
131.35, 106.71, 124.36, 124.86, 139.67, 137.37, 106.45, 128.76, 145.68, 116.82,
143.62, 134.93]

Answer 1

Use seaborn's histplot (with matplotlib for display). Example:

```python
import seaborn as sns
import matplotlib.pyplot as plt

# your Height list is already defined
sns.set(style="whitegrid")
plt.figure(figsize=(8, 5))
sns.histplot(Height, bins=10, kde=False, color='skyblue', edgecolor='black')
plt.xlabel('Height (inches)')
plt.ylabel('Count')
plt.title('Histogram of Heights')
plt.tight_layout()
plt.show()
```

Optional: set kde=True to overlay a density estimate, or change bins to refine granularity.