如何使用 Python 導出到 Excel 文件

How to Export to Excel File Using Python

1. In Visual Studio Code, create a Python file.
2. Install the Pip Python IronXL library.
3. Establish the data that needs to be exported to Excel.
4. Map the data using the Excel library to the specific cell.
5. To export all data frames to the new Excel file, save it.

IronXL

IronXL is a feature-rich Python library designed especially for usage with Excel files. Programmers have a plethora of solutions at their disposal for reading, writing, editing, and altering spreadsheet data. Built on top of the .NET framework, IronXL combines the flexibility of Python with the performance of .NET to offer an efficient means of interacting with Excel files.

One of IronXL's primary strengths is its simplicity of reading data from existing Excel files. Developers may quickly extract data from specific files, such as formatted cells, rows, lists of column names, and object cells that follow values or columns, enabling them to incorporate Excel spreadsheet data into Python programs with ease. Whether you need to retrieve sales, customer, or financial data, IronXL provides the tools you need to work with your Excel file data effectively.

Setup Environment

pip install ironxl

pip install ironxl

Export Data To Excel using IronXL

With IronXL for Python, exporting data to a new or existing Excel file without the need to import Pandas is simple. Let's examine a straightforward illustration of data exporting to an Excel spreadsheet:

from ironxl import WorkBook

# Sample dataset created as a list of lists
data = [
    ["Name", "Age", "Salary"],
    ["John", 30, 50000],
    ["Alice", 25, 60000],
    ["Bob", 35, 70000]
]

# Create a new Excel WorkBook document
workbook = WorkBook.Create()

# Create a blank WorkSheet
worksheet = workbook.CreateWorkSheet("new_sheet")

# Write data to Excel worksheet
worksheet.InsertColumn(4)
worksheet.InsertRow(len(data) + 1)

# Loop through rows and columns in the dataset
for row_idx, row_data in enumerate(data):
    for col_idx, cell_data in enumerate(row_data):
        try:
            # Set the cell value
            worksheet.SetCellValue(row_idx, col_idx, str(cell_data))
        except Exception as e:
            print("An exception occurred: " + str(e))

# Save the workbook to the specified file path
workbook.SaveAs("output.xlsx")

from ironxl import WorkBook

# Sample dataset created as a list of lists
data = [
    ["Name", "Age", "Salary"],
    ["John", 30, 50000],
    ["Alice", 25, 60000],
    ["Bob", 35, 70000]
]

# Create a new Excel WorkBook document
workbook = WorkBook.Create()

# Create a blank WorkSheet
worksheet = workbook.CreateWorkSheet("new_sheet")

# Write data to Excel worksheet
worksheet.InsertColumn(4)
worksheet.InsertRow(len(data) + 1)

# Loop through rows and columns in the dataset
for row_idx, row_data in enumerate(data):
    for col_idx, cell_data in enumerate(row_data):
        try:
            # Set the cell value
            worksheet.SetCellValue(row_idx, col_idx, str(cell_data))
        except Exception as e:
            print("An exception occurred: " + str(e))

# Save the workbook to the specified file path
workbook.SaveAs("output.xlsx")

The code snippet above creates a sample dataset as a list of lists representing data rows and columns. Then, we use nested loops to write each data frame to a new Excel worksheet created using IronXL's CreateWorkSheet method. We can create multiple sheets similarly. The output target file can be saved as "output.xlsx", which creates a new Excel file at the specified location.

# Customizing Excel export
worksheet["A1"].Style.Font.Bold = True  # Make the font in cell A1 bold
worksheet["A1"].Style.BackgroundColor = "Red"  # Set the background color of cell A1 to red
worksheet.Columns[0].Width = "20"  # Set the width of the first column
worksheet.Columns[0].FormatString = "$#,###0.00"  # Format the column as currency

# Save the workbook
workbook.SaveAs("formattedoutput.xlsx")

# Customizing Excel export
worksheet["A1"].Style.Font.Bold = True  # Make the font in cell A1 bold
worksheet["A1"].Style.BackgroundColor = "Red"  # Set the background color of cell A1 to red
worksheet.Columns[0].Width = "20"  # Set the width of the first column
worksheet.Columns[0].FormatString = "$#,###0.00"  # Format the column as currency

# Save the workbook
workbook.SaveAs("formattedoutput.xlsx")

Conclusion

We have looked at how IronXL for Python makes data exporting to Excel spreadsheets easier in this article. IronXL offers a reliable and simple solution for data exporting, from installing the library to modifying the exported data. IronXL for Python gives developers the ability to optimize their data export processes and open up new possibilities for data management and visualization, whether they're creating reports, exchanging insights, or performing analysis. Explore the world of data export with IronXL for Python and enhance your apps that are powered by data.

A permanent license, upgrade options, and a year of software support are included with IronXL's $799 Lite edition. During the trial period, customers can evaluate the product in real-world scenarios. To find out more about IronXL's pricing, licensing, and a free trial. Alternatively, go to this website to learn more about Iron Software.

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