Wie man Python verwendet, um Excel-Tabellen zu lesen

How to use Python to read Excel spreadsheet

1. Open Visual Studio Code and create a Python file.
2. Use pip to install the IronXL library for Python.
3. Open the Excel document that needs to be read.
4. Iterate through Excel data using loops.
5. Display recurrent data on the console.

Setup Environment

pip install ironxl

pip install ironxl

Reading Excel spreadsheet

IronXL makes it easy to conduct data analysis in an Excel spreadsheet. To begin, let us import data from a pre-existing Excel sheet file format into our Python environment:

from ironxl import *     # Import IronXL library for Excel operations

# Load the Excel file
workbook = WorkBook.Load("Demo.xlsx")

# Access the default worksheet (usually the first one)
worksheet = workbook.DefaultWorkSheet

# Access a specific cell value
cell_value = worksheet["A1"].StringValue

# Access row values as a string
row_values = worksheet.Rows[1].StringValue

# Access column values as a string
column_values = worksheet.Columns[0].StringValue

# Iterate over all rows and print their values
for row in worksheet.Rows:
    print(row.StringValue)

from ironxl import *     # Import IronXL library for Excel operations

# Load the Excel file
workbook = WorkBook.Load("Demo.xlsx")

# Access the default worksheet (usually the first one)
worksheet = workbook.DefaultWorkSheet

# Access a specific cell value
cell_value = worksheet["A1"].StringValue

# Access row values as a string
row_values = worksheet.Rows[1].StringValue

# Access column values as a string
column_values = worksheet.Columns[0].StringValue

# Iterate over all rows and print their values
for row in worksheet.Rows:
    print(row.StringValue)

We use the location of our Excel file to instantiate the WorkBook class after importing it from IronXL. In doing so, we generate a workbook object that we can use to access and retrieve the spreadsheet's contents. Once we've loaded it into a workbook object, we can access the Excel spreadsheet's data, including cell values, rows, and columns stored in the object. IronXL Excel workbooks additionally offer simple ways to make and get data from multiple Excel sheets.

We can obtain the value of a single cell (e.g., A1), as well as tabular data such as the values of a specific row, column labels, and a list of column names. Working with data often involves looping through the rows and columns of an Excel spreadsheet. IronXL simplifies this process with its handy iteration techniques. We can easily process and manipulate the data contained within the Excel sheet by iterating over each row, column index, and cell.

By reading the above Excel file, we will get the following output from IronXL.

To learn about IronXL code refer here.

Conclusion

Finally, IronXL for Python allows developers to overcome the difficulties involved in processing Excel files by acting as a bridge between Python and Excel files. IronXL is a feature-rich tool that offers a stable and user-friendly way to include Excel file functionality into Python programs. It can read and write data, format cells, visualize data, work with formulas, and is compatible across multiple platforms. IronXL for Python provides the flexibility and tools required to succeed in Excel file manipulation within the Python ecosystem, regardless of your background as a software developer, data scientist, or business analyst.

Whether you work as a software developer, business analyst, sales data miner, or data scientist, IronXL can help you become an expert spreadsheet reader and open up a world of possibilities for productive data manipulation. Use IronXL to read an Excel file and explore the realm of data management, increasing your Python knowledge.

IronXL's $799 Lite edition comes with a year of software support, upgrade options, and a permanent license. Customers have the opportunity to assess the product in practical settings throughout the trial time. Please visit the license page. Alternatively, to find out more about Iron Software, visit this page.