Mastering Matplotlib: A Guide to Bar Charts, Histograms, Scatter Plots, and Pie Charts

Matplotlib (5 Part Series)

1 How Data Visualization Enhances Understanding: A Matplotlib Primer
2 Creating Line Plots with Object-Oriented API and Subplot Function in Python
3 Creating Eye-Catching Plots with Matplotlib: A Guide to Custom Titles
4 Mastering Matplotlib: A Guide to Bar Charts, Histograms, Scatter Plots, and Pie Charts
5 How to Export Matplotlib Plots to JPEG or PDF

Let’s dive into the different types of plots you can create using Matplotlib, along with examples:

Bar Chart:

A bar chart (or bar plot) displays categorical data with rectangular bars. Each bar represents a category, and the height of the bar corresponds to the value of that category.
Example:


 <span>import</span> <span>matplotlib.pyplot</span> <span>as</span> <span>plt</span>
 <span>x</span> <span>=</span> <span>[</span><span>1</span><span>,</span> <span>3</span><span>,</span> <span>5</span><span>,</span> <span>7</span><span>,</span> <span>9</span><span>]</span>
 <span>y1</span> <span>=</span> <span>[</span><span>5</span><span>,</span> <span>2</span><span>,</span> <span>7</span><span>,</span> <span>8</span><span>,</span> <span>2</span><span>]</span>
 <span>y2</span> <span>=</span> <span>[</span><span>8</span><span>,</span> <span>6</span><span>,</span> <span>2</span><span>,</span> <span>5</span><span>,</span> <span>6</span><span>]</span>
 <span>plt</span><span>.</span><span>bar</span><span>(</span><span>x</span><span>,</span> <span>y1</span><span>,</span> <span>label</span><span>=</span><span>"</span><span>Example one</span><span>"</span><span>)</span>
 <span>plt</span><span>.</span><span>bar</span><span>(</span><span>x</span><span>,</span> <span>y2</span><span>,</span> <span>label</span><span>=</span><span>"</span><span>Example two</span><span>"</span><span>,</span> <span>color</span><span>=</span><span>'</span><span>g</span><span>'</span><span>)</span>
 <span>plt</span><span>.</span><span>xlabel</span><span>(</span><span>"</span><span>X-axis</span><span>"</span><span>)</span>
 <span>plt</span><span>.</span><span>ylabel</span><span>(</span><span>"</span><span>Y-axis</span><span>"</span><span>)</span>
 <span>plt</span><span>.</span><span>title</span><span>(</span><span>"</span><span>Bar Chart Example</span><span>"</span><span>)</span>
 <span>plt</span><span>.</span><span>legend</span><span>()</span>
 <span>plt</span><span>.</span><span>show</span><span>()</span>
 <span>import</span> <span>matplotlib.pyplot</span> <span>as</span> <span>plt</span>

 <span>x</span> <span>=</span> <span>[</span><span>1</span><span>,</span> <span>3</span><span>,</span> <span>5</span><span>,</span> <span>7</span><span>,</span> <span>9</span><span>]</span>
 <span>y1</span> <span>=</span> <span>[</span><span>5</span><span>,</span> <span>2</span><span>,</span> <span>7</span><span>,</span> <span>8</span><span>,</span> <span>2</span><span>]</span>
 <span>y2</span> <span>=</span> <span>[</span><span>8</span><span>,</span> <span>6</span><span>,</span> <span>2</span><span>,</span> <span>5</span><span>,</span> <span>6</span><span>]</span>

 <span>plt</span><span>.</span><span>bar</span><span>(</span><span>x</span><span>,</span> <span>y1</span><span>,</span> <span>label</span><span>=</span><span>"</span><span>Example one</span><span>"</span><span>)</span>
 <span>plt</span><span>.</span><span>bar</span><span>(</span><span>x</span><span>,</span> <span>y2</span><span>,</span> <span>label</span><span>=</span><span>"</span><span>Example two</span><span>"</span><span>,</span> <span>color</span><span>=</span><span>'</span><span>g</span><span>'</span><span>)</span>

 <span>plt</span><span>.</span><span>xlabel</span><span>(</span><span>"</span><span>X-axis</span><span>"</span><span>)</span>
 <span>plt</span><span>.</span><span>ylabel</span><span>(</span><span>"</span><span>Y-axis</span><span>"</span><span>)</span>
 <span>plt</span><span>.</span><span>title</span><span>(</span><span>"</span><span>Bar Chart Example</span><span>"</span><span>)</span>
 <span>plt</span><span>.</span><span>legend</span><span>()</span>
 <span>plt</span><span>.</span><span>show</span><span>()</span>
 import matplotlib.pyplot as plt

 x = [1, 3, 5, 7, 9]
 y1 = [5, 2, 7, 8, 2]
 y2 = [8, 6, 2, 5, 6]

 plt.bar(x, y1, label="Example one")
 plt.bar(x, y2, label="Example two", color='g')

 plt.xlabel("X-axis")
 plt.ylabel("Y-axis")
 plt.title("Bar Chart Example")
 plt.legend()
 plt.show()

This code creates a bar chart with two sets of bars, labeled “Example one” and “Example two” ⁴.

2.Histogram:

A histogram represents the distribution of continuous data by dividing it into bins and showing the frequency of values falling into each bin.

Example:


 <span>import</span> <span>matplotlib.pyplot</span> <span>as</span> <span>plt</span>
 <span>import</span> <span>numpy</span> <span>as</span> <span>np</span>
 <span>data</span> <span>=</span> <span>np</span><span>.</span><span>random</span><span>.</span><span>randn</span><span>(</span><span>1000</span><span>)</span>  <span># Generate random data </span> <span>plt</span><span>.</span><span>hist</span><span>(</span><span>data</span><span>,</span> <span>bins</span><span>=</span><span>20</span><span>,</span> <span>edgecolor</span><span>=</span><span>'</span><span>black</span><span>'</span><span>)</span>
 <span>plt</span><span>.</span><span>xlabel</span><span>(</span><span>"</span><span>Value</span><span>"</span><span>)</span>
 <span>plt</span><span>.</span><span>ylabel</span><span>(</span><span>"</span><span>Frequency</span><span>"</span><span>)</span>
 <span>plt</span><span>.</span><span>title</span><span>(</span><span>"</span><span>Histogram Example</span><span>"</span><span>)</span>
 <span>plt</span><span>.</span><span>show</span><span>()</span>
 <span>import</span> <span>matplotlib.pyplot</span> <span>as</span> <span>plt</span>
 <span>import</span> <span>numpy</span> <span>as</span> <span>np</span>

 <span>data</span> <span>=</span> <span>np</span><span>.</span><span>random</span><span>.</span><span>randn</span><span>(</span><span>1000</span><span>)</span>  <span># Generate random data </span> <span>plt</span><span>.</span><span>hist</span><span>(</span><span>data</span><span>,</span> <span>bins</span><span>=</span><span>20</span><span>,</span> <span>edgecolor</span><span>=</span><span>'</span><span>black</span><span>'</span><span>)</span>

 <span>plt</span><span>.</span><span>xlabel</span><span>(</span><span>"</span><span>Value</span><span>"</span><span>)</span>
 <span>plt</span><span>.</span><span>ylabel</span><span>(</span><span>"</span><span>Frequency</span><span>"</span><span>)</span>
 <span>plt</span><span>.</span><span>title</span><span>(</span><span>"</span><span>Histogram Example</span><span>"</span><span>)</span>
 <span>plt</span><span>.</span><span>show</span><span>()</span>
 import matplotlib.pyplot as plt
 import numpy as np

 data = np.random.randn(1000)  # Generate random data  plt.hist(data, bins=20, edgecolor='black')

 plt.xlabel("Value")
 plt.ylabel("Frequency")
 plt.title("Histogram Example")
 plt.show()

This code creates a histogram from random data.

3.Scatter Plot:

A scatter plot displays individual data points as dots. It is useful for visualizing relationships between two continuous variables.

Example:


 <span>import</span> <span>matplotlib.pyplot</span> <span>as</span> <span>plt</span>
 <span>x</span> <span>=</span> <span>[</span><span>10</span><span>,</span> <span>20</span><span>,</span> <span>30</span><span>,</span> <span>40</span><span>]</span>
 <span>y</span> <span>=</span> <span>[</span><span>20</span><span>,</span> <span>25</span><span>,</span> <span>35</span><span>,</span> <span>55</span><span>]</span>
 <span>plt</span><span>.</span><span>scatter</span><span>(</span><span>x</span><span>,</span> <span>y</span><span>,</span> <span>marker</span><span>=</span><span>'</span><span>o</span><span>'</span><span>,</span> <span>color</span><span>=</span><span>'</span><span>b</span><span>'</span><span>,</span> <span>label</span><span>=</span><span>"</span><span>Data points</span><span>"</span><span>)</span>
 <span>plt</span><span>.</span><span>xlabel</span><span>(</span><span>"</span><span>X-axis</span><span>"</span><span>)</span>
 <span>plt</span><span>.</span><span>ylabel</span><span>(</span><span>"</span><span>Y-axis</span><span>"</span><span>)</span>
 <span>plt</span><span>.</span><span>title</span><span>(</span><span>"</span><span>Scatter Plot Example</span><span>"</span><span>)</span>
 <span>plt</span><span>.</span><span>legend</span><span>()</span>
 <span>plt</span><span>.</span><span>show</span><span>()</span>
 <span>import</span> <span>matplotlib.pyplot</span> <span>as</span> <span>plt</span>

 <span>x</span> <span>=</span> <span>[</span><span>10</span><span>,</span> <span>20</span><span>,</span> <span>30</span><span>,</span> <span>40</span><span>]</span>
 <span>y</span> <span>=</span> <span>[</span><span>20</span><span>,</span> <span>25</span><span>,</span> <span>35</span><span>,</span> <span>55</span><span>]</span>

 <span>plt</span><span>.</span><span>scatter</span><span>(</span><span>x</span><span>,</span> <span>y</span><span>,</span> <span>marker</span><span>=</span><span>'</span><span>o</span><span>'</span><span>,</span> <span>color</span><span>=</span><span>'</span><span>b</span><span>'</span><span>,</span> <span>label</span><span>=</span><span>"</span><span>Data points</span><span>"</span><span>)</span>
 <span>plt</span><span>.</span><span>xlabel</span><span>(</span><span>"</span><span>X-axis</span><span>"</span><span>)</span>
 <span>plt</span><span>.</span><span>ylabel</span><span>(</span><span>"</span><span>Y-axis</span><span>"</span><span>)</span>
 <span>plt</span><span>.</span><span>title</span><span>(</span><span>"</span><span>Scatter Plot Example</span><span>"</span><span>)</span>
 <span>plt</span><span>.</span><span>legend</span><span>()</span>
 <span>plt</span><span>.</span><span>show</span><span>()</span>
 import matplotlib.pyplot as plt

 x = [10, 20, 30, 40]
 y = [20, 25, 35, 55]

 plt.scatter(x, y, marker='o', color='b', label="Data points")
 plt.xlabel("X-axis")
 plt.ylabel("Y-axis")
 plt.title("Scatter Plot Example")
 plt.legend()
 plt.show()

This code creates a scatter plot with data points.

4.Pie Chart:

A pie chart represents parts of a whole. It shows the proportion of each category relative to the total.

Example:


 <span>import</span> <span>matplotlib.pyplot</span> <span>as</span> <span>plt</span>
 <span>labels</span> <span>=</span> <span>[</span><span>'</span><span>Apples</span><span>'</span><span>,</span> <span>'</span><span>Bananas</span><span>'</span><span>,</span> <span>'</span><span>Cherries</span><span>'</span><span>,</span> <span>'</span><span>Dates</span><span>'</span><span>]</span>
 <span>sizes</span> <span>=</span> <span>[</span><span>30</span><span>,</span> <span>25</span><span>,</span> <span>20</span><span>,</span> <span>15</span><span>]</span>
 <span>plt</span><span>.</span><span>pie</span><span>(</span><span>sizes</span><span>,</span> <span>labels</span><span>=</span><span>labels</span><span>,</span> <span>autopct</span><span>=</span><span>'</span><span>%1.1f%%</span><span>'</span><span>,</span> <span>startangle</span><span>=</span><span>90</span><span>)</span>
 <span>plt</span><span>.</span><span>axis</span><span>(</span><span>'</span><span>equal</span><span>'</span><span>)</span>  <span># Equal aspect ratio ensures a circular pie chart </span> <span>plt</span><span>.</span><span>title</span><span>(</span><span>"</span><span>Pie Chart Example</span><span>"</span><span>)</span>
 <span>plt</span><span>.</span><span>show</span><span>()</span>
 <span>import</span> <span>matplotlib.pyplot</span> <span>as</span> <span>plt</span>

 <span>labels</span> <span>=</span> <span>[</span><span>'</span><span>Apples</span><span>'</span><span>,</span> <span>'</span><span>Bananas</span><span>'</span><span>,</span> <span>'</span><span>Cherries</span><span>'</span><span>,</span> <span>'</span><span>Dates</span><span>'</span><span>]</span>
 <span>sizes</span> <span>=</span> <span>[</span><span>30</span><span>,</span> <span>25</span><span>,</span> <span>20</span><span>,</span> <span>15</span><span>]</span>

 <span>plt</span><span>.</span><span>pie</span><span>(</span><span>sizes</span><span>,</span> <span>labels</span><span>=</span><span>labels</span><span>,</span> <span>autopct</span><span>=</span><span>'</span><span>%1.1f%%</span><span>'</span><span>,</span> <span>startangle</span><span>=</span><span>90</span><span>)</span>
 <span>plt</span><span>.</span><span>axis</span><span>(</span><span>'</span><span>equal</span><span>'</span><span>)</span>  <span># Equal aspect ratio ensures a circular pie chart </span> <span>plt</span><span>.</span><span>title</span><span>(</span><span>"</span><span>Pie Chart Example</span><span>"</span><span>)</span>
 <span>plt</span><span>.</span><span>show</span><span>()</span>
 import matplotlib.pyplot as plt

 labels = ['Apples', 'Bananas', 'Cherries', 'Dates']
 sizes = [30, 25, 20, 15]

 plt.pie(sizes, labels=labels, autopct='%1.1f%%', startangle=90)
 plt.axis('equal')  # Equal aspect ratio ensures a circular pie chart  plt.title("Pie Chart Example")
 plt.show()

This code creates a simple pie chart with labeled slices ².

Remember to customize these plots further by adjusting labels, colors, and other parameters according to your specific requirements. Happy plotting!

Matplotlib (5 Part Series)

原文链接：Mastering Matplotlib: A Guide to Bar Charts, Histograms, Scatter Plots, and Pie Charts

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