Xlsxwriter vs Pandas: Which is Better?
Both xlsxwriter
and pandas
can be used to write data to Excel files, but they serve different purposes. Here’s a comparison:
1. XlsxWriter
✅ Best for: Creating Excel files with advanced formatting, charts, and custom styles.
✅ Pros:
- Allows full control over formatting (cell colors, borders, fonts, etc.).
- Supports charts, conditional formatting, and images.
- Handles large Excel files efficiently (doesn’t load everything into memory).
✅ Cons: - Cannot read Excel files, only write.
- Requires more manual coding compared to pandas.
Example: Writing Data with Formatting
import xlsxwriter
workbook = xlsxwriter.Workbook('example.xlsx')
worksheet = workbook.add_worksheet()
worksheet.write('A1', 'Hello', workbook.add_format({'bold': True, 'font_color': 'red'}))
workbook.close()
2. Pandas (to_excel
)
✅ Best for: Writing DataFrames to Excel quickly with basic formatting.
✅ Pros:
- Simple and fast for exporting DataFrames.
- Can read and write Excel files (
read_excel
andto_excel
). - Supports integration with
XlsxWriter
for advanced formatting.
✅ Cons: - Less flexibility in formatting compared to
xlsxwriter
. - May be slower for very large datasets.
Example: Writing DataFrame to Excel
import pandas as pd
df = pd.DataFrame({'Name': ['Alice', 'Bob'], 'Age': [25, 30]})
df.to_excel('example.xlsx', index=False)
When to Use What?
- Use
xlsxwriter
if you need advanced formatting, charts, or large files. - Use
pandas
if you are working with DataFrames and need a quick export.
👉 Best of both? Use pandas
with xlsxwriter
as an engine:
pythonCopy codedf.to_excel('example.xlsx', engine='xlsxwriter', index=False)
This allows pandas
to write the data while xlsxwriter
enhances formatting. 🚀