Vertical Histogram in Python and Matplotlib

A vertical histogram is the default orientation in Matplotlib where bars extend upward from the x-axis. This tutorial shows how to create vertical histograms using plt.hist() with customizable figure settings.

Basic Vertical Histogram

The plt.hist() function creates vertical histograms by default. Here's a simple example ?

import matplotlib.pyplot as plt

# Sample data
data = [1, 2, 3, 1, 2, 3, 4, 1, 3, 4, 5]

plt.hist(data)
plt.title('Vertical Histogram')
plt.xlabel('Values')
plt.ylabel('Frequency')
plt.show()

Customizing Figure Properties

You can customize the figure size and layout using rcParams ?

import matplotlib.pyplot as plt

# Set figure properties
plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True

data = [1, 2, 3, 1, 2, 3, 4, 1, 3, 4, 5]

# Create vertical histogram (default orientation)
plt.hist(data, orientation="vertical")
plt.title('Custom Sized Vertical Histogram')
plt.xlabel('Values')
plt.ylabel('Frequency')
plt.show()

Enhanced Vertical Histogram

Add colors, transparency, and grid for better visualization ?

import matplotlib.pyplot as plt

data = [1, 1, 2, 2, 2, 3, 3, 3, 3, 4, 4, 5]

plt.figure(figsize=(8, 5))
plt.hist(data, bins=5, color='skyblue', alpha=0.7, edgecolor='black')
plt.title('Enhanced Vertical Histogram')
plt.xlabel('Values')
plt.ylabel('Frequency')
plt.grid(axis='y', alpha=0.3)
plt.show()

Key Parameters

Conclusion

Vertical histograms are the default in Matplotlib and perfect for displaying frequency distributions. Use plt.hist() with customization parameters like bins, color, and alpha for enhanced visualizations.