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Attend our Free Webinar on How to Nail Your Next Technical Interview

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How To Nail Your Next Tech Interview

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Ryan Valles
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Our tried & tested strategy for cracking interviews
How FAANG hiring process works
The 4 areas you must prepare for
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Plot Multiple Lines in Matplotlib

Attend our Free Webinar on How to Nail Your Next Technical Interview

WEBINAR +LIVE Q&A

How To Nail Your Next Tech Interview

Hosted By
Ryan Valles
Founder, Interview Kickstart
Our tried & tested strategy for cracking interviews
How FAANG hiring process works
The 4 areas you must prepare for
How you can accelerate your learnings

Plot Multiple Lines in Matplotlib

Matplotlib is a powerful Python library used for data visualization. It is a fantastic tool for creating a wide range of interactive, highly customizable plots and graphs. It can also be used to plot multiple lines on the same graph. This capability allows comparison of data across different categories, as well as the ability to view trends over time. It is important to note that matplotlib requires the data to be in a specific format before it can be plotted. To ensure that the data is in the right format, it is recommended to use NumPy arrays. This tutorial will demonstrate how to use matplotlib to plot multiple lines on the same graph.

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The following code creates a simple line graph with multiple lines in Matplotlib: ```python import matplotlib.pyplot as plt # Create two data sets x1 = [1, 2, 3, 4] y1 = [2, 4, 6, 8] x2 = [1, 2, 3, 4] y2 = [3, 6, 9, 12] # Plot the data plt.plot(x1, y1, label="Line 1") plt.plot(x2, y2, label="Line 2") # Add labels, title, and legend plt.xlabel('X Axis') plt.ylabel('Y Axis') plt.title('Multiple Line Graph') plt.legend() # Show the graph plt.show() ``` This code uses the `matplotlib.pyplot` library to create a line graph with two sets of data. First, two data sets (`x1` and `y1`, `x2` and `y2`) are created. Next, the `plot()` function is used to plot the data in the graph. Labels, title, and legend are added to the graph with the `xlabel()`, `ylabel()`, `title()`, and `legend()` functions. Finally, the `show()` function is used to show the graph.