10 different data charts using Python

 # 10 different data charts using Python

pip install matplotlib seaborn

# 1. Line Chart:

import matplotlib.pyplot as plt

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

y = [10, 12, 5, 8, 3]

plt.plot(x, y)

plt.title('Line Chart')

plt.xlabel('X-axis')

plt.ylabel('Y-axis')

plt.show()

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# 2. Bar Chart:

import matplotlib.pyplot as plt

categories = ['A', 'B', 'C', 'D']

values = [25, 40, 30, 20]

plt.bar(categories, values)

plt.title('Bar Chart')

plt.xlabel('Categories')

plt.ylabel('Values')

plt.show()

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# 3. Pie Chart:

import matplotlib.pyplot as plt

labels = ['Category A', 'Category B', 'Category C']

sizes = [30, 45, 25]

plt.pie(sizes, labels=labels, autopct='%1.1f%%')

plt.title('Pie Chart')

plt.show()

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# 4. Histogram:

import matplotlib.pyplot as plt

import numpy as np

data = np.random.randn(1000)

plt.hist(data, bins=30, edgecolor='black')

plt.title('Histogram')

plt.xlabel('Values')

plt.ylabel('Frequency')

plt.show()

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# 5. Scatter Plot:

import matplotlib.pyplot as plt

import numpy as np

x = np.random.rand(50)

y = 2 * x + 1 + 0.1 * np.random.randn(50)

plt.scatter(x, y)

plt.title('Scatter Plot')

plt.xlabel('X-axis')

plt.ylabel('Y-axis')

plt.show()

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# 6. Box Plot:

import seaborn as sns

import numpy as np

data = [np.random.normal(0, std, 100) for std in range(1, 4)]

sns.boxplot(data=data)

plt.title('Box Plot')

plt.xlabel('Category')

plt.ylabel('Values')

plt.show()

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# 7. Violin Plot:

import seaborn as sns

import numpy as np

data = [np.random.normal(0, std, 100) for std in range(1, 4)]

sns.violinplot(data=data)

plt.title('Violin Plot')

plt.xlabel('Category')

plt.ylabel('Values')

plt.show()

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# 8. Heatmap:

import seaborn as sns

import numpy as np

data = np.random.rand(10, 10)

sns.heatmap(data, annot=True)

plt.title('Heatmap')

plt.show()

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# 9. Area Chart:

import matplotlib.pyplot as plt

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

y1 = [10, 15, 25, 30, 35]

y2 = [5, 10, 20, 25, 30]

plt.fill_between(x, y1, y2, color='skyblue', alpha=0.4)

plt.title('Area Chart')

plt.xlabel('X-axis')

plt.ylabel('Y-axis')

plt.show()

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# 10. Radar Chart:

import matplotlib.pyplot as plt

import numpy as np

labels = np.array([' A', ' B', ' C', ' D', ' E'])

data = np.array([4, 5, 3, 4, 2])

angles = np.linspace(0, 2 * np.pi, len(labels), endpoint=False)

data = np.concatenate((data, [data[0]]))

angles = np.concatenate((angles, [angles[0]]))

plt.polar(angles, data, marker='o')

plt.fill(angles, data, alpha=0.25)

plt.title('Radar Chart')

plt.show()

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