search
HomeBackend DevelopmentPython TutorialHow to draw a line chart with matplotlib

How to draw a line chart with matplotlib

Dec 05, 2023 pm 03:13 PM
matplotlibmatplotlib line chart

The matplotlib line chart is drawn by importing the matplotlib library, preparing data, using the plt.plot() function to draw the line chart, setting the properties of the line, adding titles and labels, and displaying graphics. Detailed introduction: 1. Import the matplotlib library, import matplotlib.pyplot as plt; 2. Prepare the data, defining two lists x and y, etc.

How to draw a line chart with matplotlib

The operating system for this tutorial: Windows 10 system, Python version 3.11.4, DELL G3 computer.

Drawing a matplotlib line chart can be completed through the following steps. I will explain each step in detail so that you can fully understand:

1. Import the matplotlib library

import matplotlib.pyplot as plt

Matplotlib is a Python library for drawing data visualization graphics. First, we need to import the matplotlib.pyplot module, which contains many functions and methods for creating graphics.

2. Prepare data

x = [1, 2, 3, 4, 5]
y = [10, 15, 7, 10, 5]

Before drawing the line chart, we need to prepare the data to be drawn. In this example, we define two lists x and y, which represent the values ​​of the abscissa and ordinate on the line chart respectively.

3. Use the plt.plot() function to draw a line chart

plt.plot(x, y)

Use the plt.plot() function to draw a line chart. Here, we pass x and y as parameters to the plt.plot() function, which will draw a line chart based on these data.

4. Set the properties of the polyline

plt.plot(x, y, color='red', linestyle='-', marker='o')

In addition to simply drawing the line chart, we can also set the color, line type, mark and other properties of the polyline. In this example, we set the polyline color to red, the line style to solid line, and the marker to a circle.

5. Add title and label

plt.title('Line chart example')

plt.xlabel('X-axis label')

plt.ylabel('Y-axis label')

To make the line chart clearer and easier to understand, we can add a title and axis label. Use the plt.title() function to add a title, and use the plt.xlabel() and plt.ylabel() functions to add horizontal and vertical axis labels.

6. Display graphics

plt.show()

Finally, use the plt.show() function to display the drawn line chart. This function opens a window to display the graph and allow user interaction.

To sum up, the above is the complete process of drawing matplotlib line chart. With these steps, we can easily create beautiful and informative line charts that show trends and relationships between data. At the same time, matplotlib also provides a wealth of customization options, allowing users to more beautify and customize graphics according to their own needs. Hopefully this detailed explanation will help you better understand how to draw matplotlib line charts.

The above is the detailed content of How to draw a line chart with matplotlib. For more information, please follow other related articles on the PHP Chinese website!

Statement
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn
Python vs. C  : Understanding the Key DifferencesPython vs. C : Understanding the Key DifferencesApr 21, 2025 am 12:18 AM

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Python vs. C  : Which Language to Choose for Your Project?Python vs. C : Which Language to Choose for Your Project?Apr 21, 2025 am 12:17 AM

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

Reaching Your Python Goals: The Power of 2 Hours DailyReaching Your Python Goals: The Power of 2 Hours DailyApr 20, 2025 am 12:21 AM

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Maximizing 2 Hours: Effective Python Learning StrategiesMaximizing 2 Hours: Effective Python Learning StrategiesApr 20, 2025 am 12:20 AM

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Choosing Between Python and C  : The Right Language for YouChoosing Between Python and C : The Right Language for YouApr 20, 2025 am 12:20 AM

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python vs. C  : A Comparative Analysis of Programming LanguagesPython vs. C : A Comparative Analysis of Programming LanguagesApr 20, 2025 am 12:14 AM

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

2 Hours a Day: The Potential of Python Learning2 Hours a Day: The Potential of Python LearningApr 20, 2025 am 12:14 AM

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

Python vs. C  : Learning Curves and Ease of UsePython vs. C : Learning Curves and Ease of UseApr 19, 2025 am 12:20 AM

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Tools

ZendStudio 13.5.1 Mac

ZendStudio 13.5.1 Mac

Powerful PHP integrated development environment

EditPlus Chinese cracked version

EditPlus Chinese cracked version

Small size, syntax highlighting, does not support code prompt function

MinGW - Minimalist GNU for Windows

MinGW - Minimalist GNU for Windows

This project is in the process of being migrated to osdn.net/projects/mingw, you can continue to follow us there. MinGW: A native Windows port of the GNU Compiler Collection (GCC), freely distributable import libraries and header files for building native Windows applications; includes extensions to the MSVC runtime to support C99 functionality. All MinGW software can run on 64-bit Windows platforms.

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor