Histograms show how data is distributed across a range. Use plt.hist() — it groups values into bins and draws a bar for each bin.

Here's a histogram of simulated height data using 10 bins:

import matplotlib.pyplot as plt import numpy as np np.random.seed(42) data = np.random.normal(170, 10, 200) plt.hist(data, bins=10) plt.title('Height Distribution') plt.xlabel('Height (cm)') plt.ylabel('Frequency') plt.show()

Python

Run Code

Output

The bins parameter controls how many bars the histogram has. More bins = more detail; fewer bins = smoother overview.

More bins reveal finer details. You can also add color and edgecolor to improve readability:

import matplotlib.pyplot as plt import numpy as np np.random.seed(42) data = np.random.normal(170, 10, 200) plt.hist(data, bins=20, color='salmon', edgecolor='white') plt.title('Height Distribution') plt.xlabel('Height (cm)') plt.ylabel('Frequency') plt.show()

Python

Run Code

Output