Matplotlib bar() / barh() Function
Matplotlib Reference Documentation
bar()Used to draw vertical bar charts,barh()Used to draw horizontal bar charts.
Bar charts are used to display the quantitative comparison of categorical data, where each category is represented by a bar whose length indicates its value.
Function Definition
bar() - Vertical Bar Chart
matplotlib.pyplot.bar(x, height, width=0.8, bottom=0, *, align='center',
**kwargs)
barh() - Horizontal Bar Chart
matplotlib.pyplot.barh(y, width, height=0.8, left=0, *, align='center',
**kwargs)
Axes Interface
Axes.bar(x, height, width=0.8, bottom=0, *, align='center', **kwargs) Axes.barh(y, width, height=0.8, left=0, *, align='center', **kwargs)
Parameter Description
| Parameter | Type | Description |
|---|---|---|
| x / y | array-like | The position coordinates of the bars (x for vertical, y for horizontal) |
| height / width | array-like | The height (vertical) or width (horizontal) of the bars, i.e., the data values |
| width（bar）/ height（barh） | float or array-like | The width/height of the bars, default 0.8 |
| bottom / left | float or array-like | The starting position of the bottom of the bars, default 0. Can be used to draw stacked bar charts. |
| align | str | Alignment of the bars relative to the x/y coordinates: 'center' (default) or 'edge' |
| color | color or list | Bar color, can be a single color or a list of colors |
| edgecolor | color | Bar border color |
| linewidth / lw | float | Bar border width |
| tick_label | array-like | Tick labels for the bars, corresponding one-to-one with the x positions |
| label | str | Legend label (used for grouped bar charts) |
| alpha | float | Transparency |
| hatch | str | Fill patterns: '/', '\\', '|', '-', '+', 'x', 'o', '*' |
bar_label() Additional Notes
bar_label()Used to display value labels directly on the bars.
Axes.bar_label(container, labels=None, *, fmt=None, label_type='edge',
padding=0, **kwargs)
Both bar() and barh() return a
BarContainerobject, which can be passed to bar_label() to add value labels. This is the recommended approach in Matplotlib 3.4+.
Usage Examples
Example 1: Basic Vertical Bar Chart
Example
import matplotlib.pyplot as plt
# Category labels and data
categories = ['Python', 'Java', 'JavaScript', 'C++', 'Go']
values = [85, 72, 68, 55, 42]
fig, ax = plt.subplots(layout='constrained')
# Draw bar chart
bars = ax.bar(categories, values,
color=['#3498db', '#e74c3c', '#f39c12', '#2E7DCC', '#9b59b6'],
edgecolor='white', linewidth=1)
# Display values on the bars
ax.bar_label(bars, fmt='%d', padding=3)
ax.set_title('Programming Language Popularity')
ax.set_ylabel('Score')
ax.set_ylim(0, 100)
ax.grid(axis='y', alpha=0.3)
plt.show()
# Category labels and data
categories = ['Python', 'Java', 'JavaScript', 'C++', 'Go']
values = [85, 72, 68, 55, 42]
fig, ax = plt.subplots(layout='constrained')
# Draw bar chart
bars = ax.bar(categories, values,
color=['#3498db', '#e74c3c', '#f39c12', '#2E7DCC', '#9b59b6'],
edgecolor='white', linewidth=1)
# Display values on the bars
ax.bar_label(bars, fmt='%d', padding=3)
ax.set_title('Programming Language Popularity')
ax.set_ylabel('Score')
ax.set_ylim(0, 100)
ax.grid(axis='y', alpha=0.3)
plt.show()
Example 2: Grouped Bar Chart
Example
import matplotlib.pyplot as plt
import numpy as np
# Grouped data
labels = ['Q1', 'Q2', 'Q3', 'Q4']
product_a = [120, 135, 148, 162]
product_b = [90, 105, 115, 130]
x = np.arange(len(labels)) # x positions: [0, 1, 2, 3]
width = 0.35 # Width of each bar
fig, ax = plt.subplots(layout='constrained')
# First group of bars (offset -width/2)
bars1 = ax.bar(x - width/2, product_a, width,
label='Product A', color='steelblue', edgecolor='white')
# Second group of bars (offset +width/2)
bars2 = ax.bar(x + width/2, product_b, width,
label='Product B', color='coral', edgecolor='white')
# Add value labels
ax.bar_label(bars1, padding=3, fmt='%d')
ax.bar_label(bars2, padding=3, fmt='%d')
ax.set_title('Quarterly Sales Comparison')
ax.set_ylabel('Sales (units)')
ax.set_xticks(x)
ax.set_xticklabels(labels)
ax.legend()
ax.grid(axis='y', alpha=0.3)
plt.show()
import numpy as np
# Grouped data
labels = ['Q1', 'Q2', 'Q3', 'Q4']
product_a = [120, 135, 148, 162]
product_b = [90, 105, 115, 130]
x = np.arange(len(labels)) # x positions: [0, 1, 2, 3]
width = 0.35 # Width of each bar
fig, ax = plt.subplots(layout='constrained')
# First group of bars (offset -width/2)
bars1 = ax.bar(x - width/2, product_a, width,
label='Product A', color='steelblue', edgecolor='white')
# Second group of bars (offset +width/2)
bars2 = ax.bar(x + width/2, product_b, width,
label='Product B', color='coral', edgecolor='white')
# Add value labels
ax.bar_label(bars1, padding=3, fmt='%d')
ax.bar_label(bars2, padding=3, fmt='%d')
ax.set_title('Quarterly Sales Comparison')
ax.set_ylabel('Sales (units)')
ax.set_xticks(x)
ax.set_xticklabels(labels)
ax.legend()
ax.grid(axis='y', alpha=0.3)
plt.show()
Example 3: Stacked Bar Chart
Example
import matplotlib.pyplot as plt
categories = ['Jan', 'Feb', 'Mar', 'Apr', 'May']
income = [5000, 5200, 4800, 5500, 6000]
expense = [3000, 3500, 3200, 4000, 4200]
fig, ax = plt.subplots(layout='constrained')
# First layer of bars (bottom)
bars_income = ax.bar(categories, income,
label='Income', color='#2E7DCC', edgecolor='white')
# Second layer of bars (stacked on top of the first layer)
bars_expense = ax.bar(categories, expense, bottom=income,
label='Expense', color='#e74c3c', edgecolor='white')
# Add labels
ax.bar_label(bars_income, label_type='center', fmt='$%d')
ax.bar_label(bars_expense, label_type='center', fmt='$%d')
ax.set_title('Stacked Bar Chart: Monthly Finance')
ax.set_ylabel('Amount ($)')
ax.legend()
ax.grid(axis='y', alpha=0.3)
plt.show()
categories = ['Jan', 'Feb', 'Mar', 'Apr', 'May']
income = [5000, 5200, 4800, 5500, 6000]
expense = [3000, 3500, 3200, 4000, 4200]
fig, ax = plt.subplots(layout='constrained')
# First layer of bars (bottom)
bars_income = ax.bar(categories, income,
label='Income', color='#2E7DCC', edgecolor='white')
# Second layer of bars (stacked on top of the first layer)
bars_expense = ax.bar(categories, expense, bottom=income,
label='Expense', color='#e74c3c', edgecolor='white')
# Add labels
ax.bar_label(bars_income, label_type='center', fmt='$%d')
ax.bar_label(bars_expense, label_type='center', fmt='$%d')
ax.set_title('Stacked Bar Chart: Monthly Finance')
ax.set_ylabel('Amount ($)')
ax.legend()
ax.grid(axis='y', alpha=0.3)
plt.show()
Example 4: Horizontal Bar Chart (barh)
Example
import matplotlib.pyplot as plt
tasks = ['Task A', 'Task B', 'Task C', 'Task D', 'Task E']
hours = [12.5, 8.0, 15.3, 6.2, 10.8]
fig, ax = plt.subplots(figsize=(8, 4), layout='constrained')
# Horizontal bar chart
bars = ax.barh(tasks, hours,
color='#3498db', edgecolor='white', height=0.6)
# Add labels at the end of the bars
ax.bar_label(bars, fmt='%.1f h', padding=5)
ax.set_title('Task Completion Time (Horizontal Bar)')
ax.set_xlabel('Hours')
ax.invert_yaxis() # Invert the y-axis so the first category is at the top
ax.grid(axis='x', alpha=0.3)
plt.show()
tasks = ['Task A', 'Task B', 'Task C', 'Task D', 'Task E']
hours = [12.5, 8.0, 15.3, 6.2, 10.8]
fig, ax = plt.subplots(figsize=(8, 4), layout='constrained')
# Horizontal bar chart
bars = ax.barh(tasks, hours,
color='#3498db', edgecolor='white', height=0.6)
# Add labels at the end of the bars
ax.bar_label(bars, fmt='%.1f h', padding=5)
ax.set_title('Task Completion Time (Horizontal Bar)')
ax.set_xlabel('Hours')
ax.invert_yaxis() # Invert the y-axis so the first category is at the top
ax.grid(axis='x', alpha=0.3)
plt.show()
FAQ
What is the axis correspondence for bar() and barh()?
bar(x, height): x is the position, height determines the bar height (vertical direction).
barh(y, width): y is the position, width determines the bar width (horizontal direction).
Note the different parameter names: bar uses height, barh uses width to represent the data values.
How to make the bars in a grouped bar chart next to each other?
willwidthSet it to the reciprocal of the total width of each group of bars, and usealign='edge'。
Other Extensions