Analysis

Analysis Introduction: Google Sheets is a powerful online electronic watch tool that can be used for collaboration editing, data analysis, data visualization, etc.The Gspread library is a Python library that provides a convenient way to operate Google Sheets data through the Python code.This article will introduce how to use the Gspread library to operate Google Sheets in Python and analyze its technical principles. Technical principle analysis: 1. Certification When using the GSPread library, you first need to be certified to access and operate Google Sheets.Usually, we can certify by creating a service account.First, create a project on the Google Cloud platform and add "Google Sheets API" to the project.Then generate a JSON key file with a service account to save it locally.In the code, use this key file for certification to access Google Sheets data. 2. Introduce the GSPREAD library and certification In the code, we need to introduce the GSPread library first to use the `Import GSPREAD` statement.Then, we use the `gspread.service_account () function to pass the JSON key file path for authentication to create an` Service` object.This `server` object is used to communicate with Google Sheets. 3. Open Google Sheets documentation By calling the `Open () method of the` Service` object, we can open a Google Sheets document.You need to pass the document name or unique identifier.For the document name, you can directly use the document name string; for the unique identifier, you can use the URL link, document ID, etc. of the document. 4. Choose a worksheet Once the Google Sheets document is opened, we can select a specific worksheet by calling the `Worksheet ()" method.The name or index of the worksheet can be passed.The working gauge name is a string, and the workheet index is an integer. 5. Read data After selecting a specific worksheet, we can use the method of `get_all_values ()` to read the data of the entire worksheet.This method will return a nested list, which each subline is a line of data in the worksheet. 6. Write data To write data into Google Sheets worksheets, we can use the `update () method.This method accepts a cell range and data list as a parameter, and writes the data into the specified cell range. Complete code and related configuration: Here are a complete code example using the GSPREAD library for Google Sheets operation.Before performing this code, make sure that the GSPREAD library has been installed and the JSON key file has been obtained. python import gspread from gspread.service_account import ServiceAccountCredentials # 认 认 scopes = ['https://www.googleapis.com/auth/spreadsheets'] credentials = ServiceAccountCredentials.from_json_keyfile_name('credentials.json', scopes) service = gspread.authorize(credentials) # doc = service.open ('document name') # Select a working gauge Worksheet = DOC.WORKSHEET ('Workheet name')) # Read data data = worksheet.get_all_values() # data input worksheet.update('A1', [['Hello', 'World']]) # Output Data for row in data: print(row) In the above code, `Credentials.json` is the JSON key file generated when creating projects and service accounts on the Google Cloud platform.In the 10th line of the code, open a Google Sheets document called "Document Name") `` document name ') `` `` `` document names.In line 13, select a worksheet named "Workheet Name" through the `DOC.WORKSHEET.In line 16, the data of the entire worksheet was read through the `Workshhet.get_all_values ()`).In line 19, write the data into cell A1 by `Worksheet.Update ('A1', [['Hello', 'World']]` `` `` `` `` `` `` It should be noted that according to your own specific situation, replace the document names, worksheet names and data range of the code according to your own situation. in conclusion: Using the GSPREAD library can easily perform Google Sheets in Python.By authenticating and calling the related functions of the GSPREAD library, we can turn on, select worksheet, read data, and write data.Understanding these technical principles and corresponding code and configuration can help us better use the GSPREAD library and flexibly operate Google Sheets data in Python.