Features - ( Matplotlib Tutorial )

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Syntax

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0, 10, 100)
plt.plot(x, np.sin(x))
plt.show()

Example

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0, 10, 100)
y = np.sin(x)

fig, ax = plt.subplots()
ax.plot(x, y, label='sine wave')
ax.set_xlabel('x')
ax.set_ylabel('y')
ax.set_title('Sine Wave')
ax.legend()
plt.show()

Output

A figure is displayed with the Sine wave graph.

Explanation

Matplotlib is a popular plotting library in Python that allows users to create a wide range of visualizations.

In the above example, we import matplotlib.pyplot and numpy, and create a simple sine wave graph using the plot function. The plot function takes in the x and y values of the graph as input and displays the graph using the show function.

In the second example, we use subplots to create a figure and axis object and then plot the sine wave graph on the axis. We then set the labels and title for the graph, and add a legend to the plot.

Use

Matplotlib is a powerful visualization library that can be used to create a wide range of plots and charts. It is widely used in data visualization, scientific computing, and machine learning.

Important Points

• Matplotlib is a popular plotting library in Python
• plot is a basic function in Matplotlib that can be used to create simple graphs
• subplots can be used to create a figure and axis object for more flexibility
• Matplotlib can be used to create a wide range of visualizations including line plots, scatter plots, histograms, bar charts, pie charts, etc.

Summary

In conclusion, Matplotlib is a powerful plotting library in Python that can be used to create a wide range of visualizations. plot is a basic function in Matplotlib that can be used to create simple graphs, while subplots can be used to create more flexible and complex visualizations. Matplotlib is widely used in data visualization, scientific computing, and machine learning.