Detailed introduction to Python array definition method
The examples in this article describe the Python array definition method. Share it with everyone for your reference, the details are as follows:
There is no data structure for arrays in Python, but lists are very similar to arrays, such as:
a=[0,1,2]
At this time: a[0]=0, a[1]=1, a[[2]=2, but it raises a question, that is, what if the array a wants to be defined as 0 to 999? This may be Implemented through a = range(0, 1000). Or omit it as a = range(1000). If you want to define a with a length of 1000, and the initial values are all 0, then a = [0 for x in range(0, 1000)]
The following is a two-dimensional array Definition:
Direct definition:
a=[[1,1],[1,1]]
This defines a 2*2 two-dimensional array with an initial value of 0.
Indirect definition:
a=[[0 for x in range(10)] for y in range(10)]
This defines a 10*10 two-dimensional array with an initial value of 0.
There is also a simpler method of literal two-dimensional array:
b = [[0]*10]*10
Define a 10*10 two-dimensional array with an initial value of 0.
Compare with a=[[0 for x in range(10)] for y in range(10)]: the result of print a==b is True.
But after using the definition method of b instead of a, the program that could run normally before also went wrong. After careful analysis, the difference was found:
a[0][0]=1 , only a[0][0] is 1, and the others are all 0.
When b[0][0]=1, a[0][0], a[1][0], and a[9,0] are all 1.
From this we get that the 10 small one-dimensional data in the large array all have the same reference, that is, they point to the same address.
So b = [[0]*10]*10 does not conform to our conventional two-dimensional array.
After testing at the same time: the definition of c=[0]*10 has the same effect as c=[0 for x in range(10)], without the problem of the same reference above, it is estimated that the definition of array c At this time, the value type is multiplied, while in the previous b, the type is multiplied, because the one-dimensional array is a reference (borrowing the value type and reference type in C#, I don’t know if it is appropriate).
For more detailed introduction to Python array definition methods and related articles, please pay attention to the PHP Chinese website!
Hot AI Tools
Undresser.AI Undress
AI-powered app for creating realistic nude photos
AI Clothes Remover
Online AI tool for removing clothes from photos.
Undress AI Tool
Undress images for free
Clothoff.io
AI clothes remover
Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!
Hot Article
Hot Tools
Notepad++7.3.1
Easy-to-use and free code editor
SublimeText3 Chinese version
Chinese version, very easy to use
Zend Studio 13.0.1
Powerful PHP integrated development environment
Dreamweaver CS6
Visual web development tools
SublimeText3 Mac version
God-level code editing software (SublimeText3)
Hot Topics
1664
14
1422
52
1316
25
1267
29
1239
24
Python vs. C : Applications and Use Cases Compared
Apr 12, 2025 am 12:01 AM
Python is suitable for data science, web development and automation tasks, while C is suitable for system programming, game development and embedded systems. Python is known for its simplicity and powerful ecosystem, while C is known for its high performance and underlying control capabilities.
Python: Games, GUIs, and More
Apr 13, 2025 am 12:14 AM
Python excels in gaming and GUI development. 1) Game development uses Pygame, providing drawing, audio and other functions, which are suitable for creating 2D games. 2) GUI development can choose Tkinter or PyQt. Tkinter is simple and easy to use, PyQt has rich functions and is suitable for professional development.
The 2-Hour Python Plan: A Realistic Approach
Apr 11, 2025 am 12:04 AM
You can learn basic programming concepts and skills of Python within 2 hours. 1. Learn variables and data types, 2. Master control flow (conditional statements and loops), 3. Understand the definition and use of functions, 4. Quickly get started with Python programming through simple examples and code snippets.
Python vs. C : Learning Curves and Ease of Use
Apr 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.
How Much Python Can You Learn in 2 Hours?
Apr 09, 2025 pm 04:33 PM
You can learn the basics of Python within two hours. 1. Learn variables and data types, 2. Master control structures such as if statements and loops, 3. Understand the definition and use of functions. These will help you start writing simple Python programs.
Python and Time: Making the Most of Your Study Time
Apr 14, 2025 am 12:02 AM
To maximize the efficiency of learning Python in a limited time, you can use Python's datetime, time, and schedule modules. 1. The datetime module is used to record and plan learning time. 2. The time module helps to set study and rest time. 3. The schedule module automatically arranges weekly learning tasks.
Python: Automation, Scripting, and Task Management
Apr 16, 2025 am 12:14 AM
Python excels in automation, scripting, and task management. 1) Automation: File backup is realized through standard libraries such as os and shutil. 2) Script writing: Use the psutil library to monitor system resources. 3) Task management: Use the schedule library to schedule tasks. Python's ease of use and rich library support makes it the preferred tool in these areas.
Python: Exploring Its Primary Applications
Apr 10, 2025 am 09:41 AM
Python is widely used in the fields of web development, data science, machine learning, automation and scripting. 1) In web development, Django and Flask frameworks simplify the development process. 2) In the fields of data science and machine learning, NumPy, Pandas, Scikit-learn and TensorFlow libraries provide strong support. 3) In terms of automation and scripting, Python is suitable for tasks such as automated testing and system management.
