<｜begin▁of▁sentence｜>### Instruction:
As a data scientist, you've been presented with a dataset of 1000 weight measurements from clients as they start a personalized nutrition program. Using the matplotlib and numpy libraries, you are required to create a histogram with 30 bins to visualize the distribution of these weight measurements. This will help to gain insights into the initial distribution of weights and identify any patterns that may exist prior to the nutrition program.
### Response:
import matplotlib.pyplot as plt
import numpy as np

# Generate random data
data = np.random.randn(1000)

# Create histogram
hist, bins = np.histogram(data, bins=30)

# Plot histogram
plt.bar(bins[:-1], hist, width=(bins[1]-bins[0]), edgecolor='black')
plt.title('Histogram Example')
plt.xlabel('Value')
plt.ylabel('Frequency')
plt.show()
<|EOT|>
