Matplotlib Pie Charts

Last modified on: October 20, 2024

<h2>Matplotlib Pie Charts: Visualizing Proportions in Python</h2>
<p>Learn how to create and customize pie charts using Matplotlib. Explore options for color customization, exploded slices, percentage labels, and donut charts to effectively represent categorical data proportions.</p>
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<h3>Matplotlib Pie Charts</h3>
<p>Pie charts are a circular statistical graphic that is divided into slices to illustrate numerical proportions. Each slice represents a category's contribution to the total. This guide will cover how to create and customize pie charts using Matplotlib.</p>
<h4>1. <strong>Creating a Basic Pie Chart</strong></h4>
<p>You can create a basic pie chart using the <code>pie()</code> function from the <code>pyplot</code> module.</p>
<p><strong>Example: Basic Pie Chart</strong></p>
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<pre class="language-python"><code>import matplotlib.pyplot as plt

# Sample data
labels = ['Apples', 'Bananas', 'Cherries', 'Dates']
sizes = [15, 30, 45, 10]

# Create a pie chart
plt.pie(sizes, labels=labels)

# Add title
plt.title("Basic Pie Chart")

# Show the plot
plt.show()</code></pre>
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<h4>2. <strong>Customizing Colors</strong></h4>
<p>You can customize the colors of the slices in your pie chart using the <code>colors</code> parameter.</p>
<p><strong>Example: Customized Colors</strong></p>
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<pre class="language-python"><code>colors = ['red', 'yellow', 'pink', 'brown']

plt.pie(sizes, labels=labels, colors=colors)
plt.title("Pie Chart with Custom Colors")
plt.show()</code></pre>
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<h4>3. <strong>Adding Exploded Slices</strong></h4>
<p>You can highlight a specific slice by "exploding" it from the pie chart.</p>
<p><strong>Example: Exploded Slice</strong></p>
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<pre class="language-python"><code>explode = (0.1, 0, 0, 0)  # Explode the first slice (Apples)

plt.pie(sizes, labels=labels, explode=explode)
plt.title("Pie Chart with Exploded Slice")
plt.show()</code></pre>
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<h4>4. <strong>Adding Percentages to Slices</strong></h4>
<p>You can show the percentage of each slice using the <code>autopct</code> parameter.</p>
<p><strong>Example: Pie Chart with Percentages</strong></p>
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<pre class="language-python"><code>plt.pie(sizes, labels=labels, autopct='%1.1f%%')
plt.title("Pie Chart with Percentages")
plt.show()</code></pre>
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<h4>5. <strong>Customizing Start Angle and Shadow</strong></h4>
<p>You can change the starting angle of the pie chart and add a shadow for a 3D effect.</p>
<p><strong>Example: Customized Start Angle and Shadow</strong></p>
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<pre class="language-python"><code>plt.pie(sizes, labels=labels, autopct='%1.1f%%', startangle=90, shadow=True)
plt.title("Pie Chart with Shadow and Start Angle")
plt.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle
plt.show()</code></pre>
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<h4>6. <strong>Creating a Donut Chart</strong></h4>
<p>You can create a donut chart by drawing a pie chart and then adding a circle in the center.</p>
<p><strong>Example: Donut Chart</strong></p>
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<pre class="language-python"><code># Create a pie chart
plt.pie(sizes, labels=labels, startangle=90, colors=colors, wedgeprops=dict(width=0.3))

# Add a circle at the center to create a donut effect
centre_circle = plt.Circle((0, 0), 0.70, fc='white')
fig = plt.gcf()
fig.gca().add_artist(centre_circle)

plt.title("Donut Chart")
plt.axis('equal')  # Equal aspect ratio ensures that donut is drawn as a circle
plt.show()</code></pre>
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<h4>7. <strong>Saving Pie Charts</strong></h4>
<p>You can save your pie charts in various formats using the <code>savefig()</code> function.</p>
<p><strong>Example: Saving a Pie Chart</strong></p>
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<pre class="language-python"><code>plt.pie(sizes, labels=labels, autopct='%1.1f%%')
plt.title("Saved Pie Chart")
plt.savefig("pie_chart.png")  # Save as PNG file
plt.show()</code></pre>
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<h3>Conclusion</h3>
<p>Pie charts are a simple and effective way to visualize the proportion of different categories within a whole. By customizing colors, adding percentages, and creating donut charts, you can enhance the clarity and appeal of your visualizations.</p>
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