Histograms for Data Distributions

Histograms show how values in your data are distributed across different ranges. They're essential for understanding the shape, spread, and central tendency of your data.

Basic Histogram

Choosing the Right Number of Bins

The number of bins affects how the distribution appears:

Custom Bin Edges

Specify exact bin boundaries:

Comparing Distributions

Overlay multiple histograms:

Density Plots (Normalized Histograms)

Compare distributions with different sample sizes:

Histogram with Statistics

Add statistical annotations:

Step Histogram

For cleaner overlapping distributions:

Cumulative Histogram

Show cumulative distribution:

2D Histogram (Heatmap)

Visualize the joint distribution of two variables:

Practice: Analyze a Distribution

Key Takeaways

• Histograms show how data is distributed across value ranges
• Choose bins carefully: too few hides detail, too many creates noise
• Use density=True to compare distributions with different sample sizes
• Add statistical measures (mean, median, std) as reference lines
• Step histograms (histtype='step') work well for overlapping distributions
• Cumulative histograms show running totals
• 2D histograms and hexbin plots show joint distributions

In the next module, we'll explore pie charts and subplot layouts.