How to optimize excel writing using pandas

How to use pandas to achieve efficient writing to Excel

In the process of data processing and analysis, writing data to Excel files is a common operation. Python's pandas library provides an efficient way to achieve this. This article will introduce how to use pandas to achieve efficient writing to Excel, and provide specific code examples.

First, we need to install the pandas library. pandas can be installed in the command prompt or terminal using the following command:

pip install pandas

Once the installation is complete, we can start writing code.

1. Create DataFrame object

Before starting to write data, we first need to prepare the data to be written to Excel. DataFrame objects in pandas are ideal for storing and processing tabular data. We can create a DataFrame object in the following way:

import pandas as pd

data = {'姓名': ['张三', '李四', '王五'],
        '年龄': [25, 30, 35],
        '性别': ['男', '女', '男']}

df = pd.DataFrame(data)

This DataFrame object contains three columns of data, namely name, age and gender.

2. Write to Excel file

Next, we can use the to_excel() method provided by pandas to write the DataFrame object to the Excel file. This method requires specifying the path and file name of the output file. We can use the following code to write a DataFrame object to an Excel file:

df.to_excel('output.xlsx', index=False)

In this example, we write a DataFrame object to an Excel file named output.xlsx and do not include the row index.

If you want to write multiple DataFrame objects to different worksheets in the same Excel file, you can use the ExcelWriter object. The following is a sample code:

writer = pd.ExcelWriter('output.xlsx')

df1.to_excel(writer, sheet_name='Sheet1', index=False)
df2.to_excel(writer, sheet_name='Sheet2', index=False)

writer.save()

In this example, we create an ExcelWriter object and use it to write two DataFrame objects into two worksheets (Sheet1 and Sheet2). Finally, we call the save() method to save the Excel file.

3. Other properties for writing Excel files

In addition to writing data, we can also set the format of cells, adjust column width and row height and other properties. The following are some commonly used methods and properties:

• Format the cell:

  df['年龄'].style.format('{:.1f}')

  This example retains the data in the age column to one decimal place.

• Adjust column width and row height:

  writer.sheets['Sheet1'].set_column('A:A', 20)
  writer.sheets['Sheet1'].set_row(0, 30)

  This example sets the width of the first column to 20 and the height of the first row to 30.

By using the methods and properties provided by the pandas library, we can easily perform advanced operations on Excel files.

Summary

This article introduces how to use pandas to achieve efficient writing to Excel, and provides specific code examples. By using pandas' DataFrame object and the to_excel() method, we can easily write data to an Excel file. In addition, we can also format cells, adjust column widths, row heights and other properties. If you often encounter the need to write Excel files during data processing and analysis, then pandas will become a powerful assistant for you.

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