157. Data Visualization with matplotlib

Here are 10 Python snippets demonstrating data visualization with the matplotlib library, showcasing various plotting techniques. Each snippet is separated by a delimiter.

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Snippet 1: Basic Line Plot

import matplotlib.pyplot as plt

x = [1, 2, 3, 4, 5]
y = [10, 20, 25, 30, 40]

plt.plot(x, y)
plt.title("Basic Line Plot")
plt.xlabel("X-axis")
plt.ylabel("Y-axis")
plt.show()

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Snippet 2: Scatter Plot

import matplotlib.pyplot as plt

x = [5, 7, 8, 7, 2, 17, 2, 9, 4, 11]
y = [99, 86, 87, 88, 100, 86, 103, 87, 94, 78]

plt.scatter(x, y, color='red', marker='o')
plt.title("Scatter Plot")
plt.xlabel("X-axis")
plt.ylabel("Y-axis")
plt.show()

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Snippet 3: Bar Chart

import matplotlib.pyplot as plt

categories = ['A', 'B', 'C', 'D']
values = [5, 7, 8, 4]

plt.bar(categories, values, color='blue')
plt.title("Bar Chart")
plt.xlabel("Categories")
plt.ylabel("Values")
plt.show()

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Snippet 4: Histogram

import matplotlib.pyplot as plt

data = [1, 2, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5]

plt.hist(data, bins=5, color='green', edgecolor='black')
plt.title("Histogram")
plt.xlabel("Bins")
plt.ylabel("Frequency")
plt.show()

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Snippet 5: Pie Chart

import matplotlib.pyplot as plt

sizes = [20, 30, 25, 25]
labels = ['Category A', 'Category B', 'Category C', 'Category D']

plt.pie(sizes, labels=labels, autopct='%1.1f%%', startangle=90)
plt.title("Pie Chart")
plt.show()

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Snippet 6: Multiple Lines in One Plot

import matplotlib.pyplot as plt

x = [1, 2, 3, 4, 5]
y1 = [10, 20, 30, 40, 50]
y2 = [5, 15, 25, 35, 45]

plt.plot(x, y1, label='Line 1')
plt.plot(x, y2, label='Line 2', linestyle='--')

plt.title("Multiple Lines")
plt.xlabel("X-axis")
plt.ylabel("Y-axis")
plt.legend()
plt.show()

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Snippet 7: Box Plot

import matplotlib.pyplot as plt

data = [7, 8, 9, 10, 12, 15, 19, 20, 23, 25]

plt.boxplot(data)
plt.title("Box Plot")
plt.ylabel("Values")
plt.show()

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Snippet 8: Area Plot

import matplotlib.pyplot as plt

x = [1, 2, 3, 4, 5]
y = [3, 8, 1, 10, 5]

plt.fill_between(x, y, color="skyblue", alpha=0.5)
plt.plot(x, y, color="Slateblue", alpha=0.6, linewidth=2)
plt.title("Area Plot")
plt.xlabel("X-axis")
plt.ylabel("Y-axis")
plt.show()

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Snippet 9: Horizontal Bar Chart

import matplotlib.pyplot as plt

categories = ['A', 'B', 'C', 'D']
values = [5, 7, 8, 4]

plt.barh(categories, values, color='purple')
plt.title("Horizontal Bar Chart")
plt.xlabel("Values")
plt.ylabel("Categories")
plt.show()

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Snippet 10: Heatmap (Using Matplotlib's imshow)

import matplotlib.pyplot as plt
import numpy as np

data = np.random.rand(5, 5)

plt.imshow(data, cmap='hot', interpolation='nearest')
plt.colorbar()
plt.title("Heatmap")
plt.show()

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