python怎么读取excel文件?
1.首先说明我是使用的python3.5,我的office版本是2010,首先打开dos命令窗,安装必须的两个库,命令是:
pip3 install xlrd Pip3 install xlwt
2.准备好excel,例如我的一个工作文件,我放在D盘/百度经验/11.xlsx,只有一个页签A,内容是一些销售数据
3.打开pycharm,新建一个excel.py的文件,首先导入支持库
import xlrdimport xlwt
4.针对刚入门的新手,先介绍三个知识,第一个:获取excel的sheet名称,第二:获取excel行数与列数,第三:获取第几行第几列的具体值,这是最常用的三个知识点
5.贴出代码,具体分析:
1.要操作excel,首先得打开excel,使用open_workbook(‘路径’)
2.要获取行与列,使用nrows(行),ncols(列)
3.获取具体的值,使用cell(row,col).value
workbook=xlrd.open_workbook(r'E:\11.xlsx')print (workbook.sheet_names()) sheet2=workbook.sheet_by_name('A') nrows=sheet2.nrows ncols=sheet2.ncols print(nrows,ncols) cell_A=sheet2.cell(1,1).value print(cell_A)
6.要在excel里写入值,就要使用write属性,重点说明写入是用到xlwt这个支援库,思路是先新建excel,然后新建页签B,然后将一组数据写入到B,最后保存为excel.xls,这里建议保存为2003的格式,大部分电脑都能打开,特别注意保存的excel的路径是在python工作文件的目录下面,贴出代码:
stus = [['年', '月'], ['2018', '10'], ['2017', '9'], ['2016', '8']]Excel = xlwt.Workbook() # 新建excelsheet = Excel.add_sheet('B') #新建页签Brow = 0for stu in stus: col = 0 for s in stu: sheet.write(row, col, s) #开始写入 col = col + 1 row = row + 1Excel.save('Excel.xls') #保存
The above is the detailed content of How to read excel files in python. For more information, please follow other related articles on the PHP Chinese website!

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.

Python's real-world applications include data analytics, web development, artificial intelligence and automation. 1) In data analysis, Python uses Pandas and Matplotlib to process and visualize data. 2) In web development, Django and Flask frameworks simplify the creation of web applications. 3) In the field of artificial intelligence, TensorFlow and PyTorch are used to build and train models. 4) In terms of automation, Python scripts can be used for tasks such as copying files.

Python is widely used in data science, web development and automation scripting fields. 1) In data science, Python simplifies data processing and analysis through libraries such as NumPy and Pandas. 2) In web development, the Django and Flask frameworks enable developers to quickly build applications. 3) In automated scripts, Python's simplicity and standard library make it ideal.

Python's flexibility is reflected in multi-paradigm support and dynamic type systems, while ease of use comes from a simple syntax and rich standard library. 1. Flexibility: Supports object-oriented, functional and procedural programming, and dynamic type systems improve development efficiency. 2. Ease of use: The grammar is close to natural language, the standard library covers a wide range of functions, and simplifies the development process.

Python is highly favored for its simplicity and power, suitable for all needs from beginners to advanced developers. Its versatility is reflected in: 1) Easy to learn and use, simple syntax; 2) Rich libraries and frameworks, such as NumPy, Pandas, etc.; 3) Cross-platform support, which can be run on a variety of operating systems; 4) Suitable for scripting and automation tasks to improve work efficiency.

Yes, learn Python in two hours a day. 1. Develop a reasonable study plan, 2. Select the right learning resources, 3. Consolidate the knowledge learned through practice. These steps can help you master Python in a short time.


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

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

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.

Notepad++7.3.1
Easy-to-use and free code editor

WebStorm Mac version
Useful JavaScript development tools

Dreamweaver Mac version
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)