Efficiently Writing Data to Excel Spreadsheets with Python

Introduction

Working with spreadsheets is a common task for many data-driven applications. In Python, several libraries facilitate writing data into Excel files, each with its own strengths and use cases. This tutorial will guide you through using these popular libraries to write data to an Excel spreadsheet effectively.

Key Libraries

1. xlwt: Ideal for basic Excel operations without the need for complex formatting.
2. openpyxl: Useful for handling modern .xlsx files and advanced features like cell formatting.
3. pandas: Offers a high-level interface for working with tabular data, including exporting to Excel.
4. xlsxwriter: Provides extensive functionality for creating sophisticated spreadsheets.

Writing Data Using xlwt

The xlwt library is simple yet powerful for writing data into older .xls format files. Here’s how you can use it:

Installation

pip install xlwt

Basic Usage

Here’s an example of using xlwt to write data into a spreadsheet, including setting number formats.

import xlwt

# Create workbook and sheet
book = xlwt.Workbook()
sheet1 = book.add_sheet('Sheet 1')

# Define style for scientific number format
style = xlwt.XFStyle()
style.num_format_str = '0.00E+00'

# Write headers
sheet1.write(0, 0, "Display")
sheet1.write(1, 0, "Dominance")
sheet1.write(2, 0, "Test")

# Write some variables
variables = [1, 2, 3]
for i, var in enumerate(variables):
    sheet1.write(i + 3, 0, var)

# Headers for lists
sheet1.write(6, 0, "Stimulus Time")
sheet1.write(6, 1, "Reaction Time")

# Sample data from lists
list1 = [2.34, 4.346, 4.234]
for i, value in enumerate(list1):
    sheet1.write(i + 7, 0, value, style)

book.save('output.xls')

Explanation

• Workbook and Sheet: Create a workbook object and add a new worksheet.
• Styles: Define a cell style for scientific number format using XFStyle.
• Write Data: Use the write method to insert data. The last parameter allows you to apply styles.

Using pandas for Excel Export

pandas is excellent for working with tabular data and provides straightforward methods to export data frames into Excel files.

Installation

pip install pandas openpyxl

Basic Usage

Here’s how to use pandas to convert data structures into an Excel file:

import pandas as pd

# Sample data in lists and variables
list1 = [2.34, 4.346, 4.234]
list2 = [3.14, 2.718, 1.618]
x, y, z = 'Display', 'Dominance', 'Test'

# Create a DataFrame
data = {
    "Stimulus Time": list1,
    "Reaction Time": list2[:len(list1)]
}
df = pd.DataFrame(data)

# Add constants as a new row if needed
additional_data = {'x': x, 'y': y, 'z': z}

# Write to Excel file
with pd.ExcelWriter('output.xlsx', engine='openpyxl') as writer:
    df.to_excel(writer, sheet_name='Sheet1', index=False)

    # Optionally add more data or formatting here.

Explanation

• DataFrame: Convert lists and variables into a pandas DataFrame, which provides rich functionality for manipulating tabular data.
• ExcelWriter: Use ExcelWriter with the openpyxl engine to write data frames directly into an Excel file.

Creating Advanced Spreadsheets with xlsxwriter

For more complex spreadsheet creation tasks that involve formatting, images, or charts, xlsxwriter is a powerful choice.

Installation

pip install xlsxwriter

Basic Usage

Here’s how you can use xlsxwriter to create an Excel file:

import xlsxwriter

# Create a workbook and add a worksheet.
workbook = xlsxwriter.Workbook('advanced_demo.xlsx')
worksheet = workbook.add_worksheet()

# Add formats
bold = workbook.add_format({'bold': True})

# Write data with formatting
worksheet.write('A1', 'Header 1', bold)
worksheet.write('A2', 'Header 2', bold)

# Writing numbers and setting column width
worksheet.set_column('A:A', 20)
worksheet.write(2, 0, 123)
worksheet.write(3, 0, 456.789)

# Save workbook
workbook.close()

Explanation

• Workbook Creation: Start by creating a new workbook.
• Worksheet and Formats: Add worksheets and define cell formats for styling.
• Writing Data: Use write to insert data, optionally applying styles.

Conclusion

Choosing the right library depends on your specific needs. For basic tasks and compatibility with older Excel versions, xlwt is suitable. If you’re working with modern .xlsx files and require more complex features, consider openpyxl, pandas, or xlsxwriter. Each of these libraries offers unique capabilities that can enhance the way you manipulate spreadsheet data in Python.