Python has four types of data collections, namely list, tuple, dict, set
List, List
List is an ordered and variable data collection in Python. Its elements can be added or removed. The representation method of List is to use a [] to enclose the elements, and separate the elements with a, sign. For example [2,'hah',True].
Create a List
list = [1,2,3,'apple',true] List中的元素的数据类型可以不同,除了整数、浮点数、布尔值、字符串等,也可以是list或则其他。
The length of the List
You can use the len() function to get the length of the list.
Get elements of List
You can use list[index] to get an element in the list from front to back.
You can also use list[-n] to get the nth element from the back to the front in the list.
Append elements append()
For example, list.append('haha') can add an element after the list.
Insert element insert()
For example, list.insert(2, "haha") adds an element to position 3 of the list.
Delete elements pop()
list.pop() deletes the last element of the list by default. list.pop(i) deletes the i+1th element.
Replace elements in the list
list[2]='banana'
Tuple, Tuple
Tuple is an ordered but immutable list in Python. Once a Tuple is created, it cannot be modified. The representation method is to use a pair of () to contain the elements and separate them with,.
For example: (1,2,3). But for a tuple that only uses one element, you need to add one after the element, such as (1,) to distinguish it from the operator ().
The acquisition of Tuple elements
is consistent with list, that is, tuple[index].
Dict Dictionary
The dictionary in Python is a data format stored in key-value format. The key in Dict is the only immutable object.
Dict creation method
my_dict = {'name':'Charlie','age':20,'gender':'male'}
Get value based on key
my_dict['name']
But sometimes we are not sure whether the key we want is in the dict. If not, but we obtain the value according to the above method, KeyError will be reported.
We have two ways to solve it
Use in to determine whether the key exists. key in dict
my_dict.get('name'). If the key does not exist, None is returned. You can also know the return value when the key does not exist, that is, my_dict.get('name','value_if_not_existed')
Delete key-value
my_dict.pop('name')
Dict与List相比,Dict查询、插入的速度快,与Dict大小无关。占用内存大。List查询、插入的速度与List大小呈反比,但是占用内存小。
Set
Set是一个有序且不重复的数据集合。Set中的元素都必须是不可变对象。
创建set
s = set([1,2,3,5,4,3])
创建时重复的元素将被自动删除。
添加元素
s.add('9')
删除元素
s.remove('9')
若元素'9'不存在,则会报KeyError错误。

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.

Python and C have significant differences in memory management and control. 1. Python uses automatic memory management, based on reference counting and garbage collection, simplifying the work of programmers. 2.C requires manual management of memory, providing more control but increasing complexity and error risk. Which language to choose should be based on project requirements and team technology stack.

Python's applications in scientific computing include data analysis, machine learning, numerical simulation and visualization. 1.Numpy provides efficient multi-dimensional arrays and mathematical functions. 2. SciPy extends Numpy functionality and provides optimization and linear algebra tools. 3. Pandas is used for data processing and analysis. 4.Matplotlib is used to generate various graphs and visual results.

Whether to choose Python or C depends on project requirements: 1) Python is suitable for rapid development, data science, and scripting because of its concise syntax and rich libraries; 2) C is suitable for scenarios that require high performance and underlying control, such as system programming and game development, because of its compilation and manual memory management.

Python is widely used in data science and machine learning, mainly relying on its simplicity and a powerful library ecosystem. 1) Pandas is used for data processing and analysis, 2) Numpy provides efficient numerical calculations, and 3) Scikit-learn is used for machine learning model construction and optimization, these libraries make Python an ideal tool for data science and machine learning.

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.


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