Histograms

What is a Histogram?

A histogram shows how data is spread out:

How many people are age 20-30? 30-40? 40-50?
How many products cost $10-20? $20-30?

It groups data into bins and counts each bin.

Basic Histogram

code.py

import matplotlib.pyplot as plt

ages = [22, 25, 27, 28, 30, 31, 33, 35, 38, 40, 42, 45, 48, 55]

fig, ax = plt.subplots()
ax.hist(ages)
ax.set_xlabel('Age')
ax.set_ylabel('Count')
ax.set_title('Age Distribution')
plt.show()

Set Number of Bins

code.py

ax.hist(ages, bins=5)   # 5 bins
ax.hist(ages, bins=10)  # 10 bins
ax.hist(ages, bins=20)  # 20 bins

More bins = more detail, but can be noisy.

Set Specific Bin Edges

code.py

# Custom ranges: 20-30, 30-40, 40-50, 50-60
ax.hist(ages, bins=[20, 30, 40, 50, 60])

Change Color

code.py

ax.hist(ages, color='green')

Add Edge Color

code.py

ax.hist(ages, color='skyblue', edgecolor='black')

Multiple Histograms

code.py

import matplotlib.pyplot as plt

men_ages = [25, 28, 30, 32, 35, 38, 40, 42]
women_ages = [22, 25, 27, 30, 32, 33, 36, 39]

fig, ax = plt.subplots()
ax.hist(men_ages, alpha=0.5, label='Men', color='blue')
ax.hist(women_ages, alpha=0.5, label='Women', color='red')

ax.legend()
plt.show()

alpha makes bars transparent so they overlap nicely.

Show Percentage Instead of Count

code.py

ax.hist(ages, density=True)

Horizontal Histogram

code.py

ax.hist(ages, orientation='horizontal')

Add Mean Line

code.py

import numpy as np

fig, ax = plt.subplots()
ax.hist(ages, color='skyblue', edgecolor='black')

# Add vertical line at mean
mean_age = np.mean(ages)
ax.axvline(mean_age, color='red', linestyle='--', label=f'Mean: {mean_age:.1f}')
ax.legend()

plt.show()

Complete Example

code.py

import matplotlib.pyplot as plt
import numpy as np

# Generate sample data
np.random.seed(42)
salaries = np.random.normal(50000, 15000, 500)  # 500 people

fig, ax = plt.subplots(figsize=(10, 6))

# Create histogram
ax.hist(salaries, bins=20, color='steelblue', edgecolor='white')

# Add mean and median lines
mean_sal = np.mean(salaries)
median_sal = np.median(salaries)

ax.axvline(mean_sal, color='red', linestyle='--', label=f'Mean: ${mean_sal:,.0f}')
ax.axvline(median_sal, color='green', linestyle='--', label=f'Median: ${median_sal:,.0f}')

ax.set_xlabel('Salary ($)')
ax.set_ylabel('Number of Employees')
ax.set_title('Salary Distribution')
ax.legend()

plt.show()

Histogram vs Bar Chart

Histogram	Bar Chart
Continuous data	Categories
Shows distribution	Shows comparison
Bars touch	Bars separate

Key Points

hist() creates histograms
bins controls number of groups
Shows how data is distributed
Use alpha for overlapping histograms
Use density=True for percentages
Add axvline for mean/median markers

What's Next?

Learn box plots for showing data spread and outliers.