| by Arround The Web | No comments

## Matplotlib Plot Multiple Lines

“Matplotlib” is a versatile library that provides a variety of tools to create/make various types of plots. One of the most common tasks is plotting “multiple” lines in a “single” chart. In this article, we’ll explore different ways to plot multiple lines using “Matplotlib” and how to customize the style, color, and labels to create effective and visually appealing plots.

## Creating a Basic Line Plot

Before diving into multiple line plots, let’s first create a simple line plot using “Matplotlib”. In order to get started, let’s import the essential libraries and generate some sample data.

Example
In the following code, the “matplotlib.plot()” function is utilized to make a basic line plot:

import matplotlib.pyplot as plt
import numpy
value1 = numpy.arange(0, 10, 0.1)
value2 = numpy.sin(value1)
plt.plot(value1, value2)
plt.show()

In the above code snippet, the “np.arange()” function is used to generate an array of values from “0” to “10” with a step of “0.1”. Similarly, the “np.sin()” function is used to calculate the sine of each value in the passed array. To create a basic line plot, pass the array and calculated sine of the array values as the “plt.plot()” function arguments, respectively.

Output

The above output implies that the basic line plot has been created.

## Plotting Single Horizontal Lines

To plot a single horizontal line, the “plt.axhline()” function is used in Python.

Example
As an example, let’s look at the following code:

import matplotlib.pyplot as plt
plt.axhline(y=2)
plt.show()

In the above lines of code, the “axhline()” function is used to plot a horizontal line at “y=2” on the current plot.

Output

In the above output, the single horizontal line has been plotted successfully.

## Plotting Single Vertical Lines

To plot a single vertical line, the “plt.axvline()” function is used instead in Python.

Example
Let’s overview the following example code:

import matplotlib.pyplot as plt
plt.axvline(x=2)
plt.show()

According to the above code block, the “plt.axvline()” function is used to plot a vertical line at “x=2” on the current plot.

Output

As analyzed, the single vertical line has been plotted appropriately.

## Plotting Multiple Lines

To plot multiple lines, we simply pass multiple “x” and “y” arrays to the “plt.plot()” function.

Example
The code is summarized below:

import matplotlib.pyplot as plt
import numpy
x = numpy.arange(0, 10, 0.1)
y1 = numpy.sin(x)
y2 = numpy.sin(2 * x)
plt.plot(x, y1)
plt.plot(x, y2)
plt.show()

According to the above code, two arrays “y1” and “y2” are created with each representing a sine wave with a different frequency. The “plt.plot()” function takes the array with each of the sine waves separately as an argument and creates two lines in the same plot.

Output

Based on the above output, the two lines in the same plot have been generated successfully.

## Plotting Multiple Lines by Customizing “linestyle” and “color” Arguments

In “Matplotlib”, by default, the plot is drawn with a solid blue line. The “linestyle” and “color” arguments can, however, be customized.

Example
The below code is used to plot multiple lines with customized line styles and colors:

import matplotlib.pyplot as plt
import numpy
x = numpy.arange(0, 10, 0.1)
y1 = numpy.sin(x)
y2 = numpy.sin(2 * x)
plt.plot(x, y1, linestyle='--', color='red')
plt.plot(x, y2, linestyle=':', color='green')
plt.show()

In the above code, the “linestyle” is set to ‘‘ for the first line and ‘:‘ for the second one, giving us dashed and dotted lines, respectively. Also, the colors are also set to red and green for the first and second lines, accordingly.

Output

Based on the above output, multiple lines have been plotted via different line styles and colors.

## Conclusion

Matplotlib” provides functions such as “plt.plot()” to plot multiple lines on the same plot. These multiple-line plots can also be plotted using different line styles and colors with the help of the customized “linestyle” and “color” arguments. This post discussed various ways to plot multiple lines using numerous examples.

Source: linuxhint.com