The Tool Desk
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Write one DataFrame to a new Excel file
Import pandas, create or load a DataFrame, then call to_excel() with a filename:
import pandas as pd
df = pd.DataFrame({"name": ["Ada", "Grace"], "score": [98, 95]})
df.to_excel("output.xlsx", index=False)This creates an .xlsx workbook. By default, pandas writes the DataFrame index as an extra column; use index=False when those row labels should not appear. The default worksheet name is Sheet1; set sheet_name to choose another name. See the DataFrame.to_excel API reference and the pandas getting-started tutorial.
Choose what pandas writes
to_excel() provides options for selecting columns, setting headers and placing data. Common controls include:
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| Option | Purpose |
|---|---|
index |
Include or omit DataFrame row labels; the default is True. |
sheet_name |
Choose the worksheet name; the default is Sheet1. |
columns |
Write only selected columns. |
header |
Control or rename column headings. |
index_label |
Set a label for the index column or columns. |
na_rep |
Choose the text used for missing values. |
float_format |
Set a representation for floating-point values. |
startrow and startcol |
Position the output within the worksheet. |
freeze_panes and autofilter |
Set common worksheet conveniences. |
merge_cells |
Control merging for MultiIndex values. |
inf_rep |
Set the text used for infinity, which Excel does not represent as a native value. |
Lists and dictionaries are serialized to strings. Consult the API reference for the full parameter details.
Write multiple DataFrames to separate sheets
Use one ExcelWriter context to create the workbook and write each DataFrame to its own worksheet:
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with pd.ExcelWriter("output.xlsx") as writer:
df_a.to_excel(writer, sheet_name="Summary", index=False)
df_b.to_excel(writer, sheet_name="Details", index=False)The context manager saves the workbook and closes file handles when the block ends. If you do not use a context manager, close the writer explicitly. ExcelWriter can also write to an in-memory buffer such as BytesIO. See the ExcelWriter reference and pandas I/O guide.
Append a sheet to an existing workbook
To add output to an existing workbook rather than replace it, open an ExcelWriter in append mode and select the openpyxl engine. Decide explicitly what should happen if the target worksheet already exists:
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with pd.ExcelWriter(
"output.xlsx",
mode="a",
engine="openpyxl",
if_sheet_exists="replace",
) as writer:
df.to_excel(writer, sheet_name="Summary", index=False)Use if_sheet_exists="replace" to replace the existing sheet, or if_sheet_exists="overlay" to write over or alongside content on that sheet. With overlay, choose startrow and startcol as needed and check that the new output will not overlap existing cells. The append mode and sheet policies are documented in the ExcelWriter reference.
Pick an engine and file format
The writer engine is the library pandas uses to create the workbook. The current documentation says .xlsx output uses XlsxWriter if it is installed, otherwise openpyxl; configuration and installed libraries can affect defaults. Both are documented choices for .xlsx. The I/O guide also describes openpyxl for .xlsm and odf for .ods. Install the optional dependency required for your chosen engine. For predictable output or engine-specific features, specify engine= deliberately. See the ExcelWriter reference and Excel files section of the I/O guide.
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Style the exported workbook
As of pandas 3.0, DataFrame.to_excel() does not apply default styling. For styled output, use Styler.to_excel() or use formatting features provided by the selected engine. The pandas I/O guide links to XlsxWriter’s pandas integration for engine-specific formatting.
Avoid overwriting files or losing later writes
Creating an ExcelWriter for an existing filename in the default write mode overwrites that file. If you need to preserve existing workbook content, use append mode and an explicit existing-sheet policy rather than assuming a normal write will add to it.
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Write all needed sheets before the writer is finalized. The pandas API notes: “Once a workbook has been saved it is not possible to write further data without rewriting the whole workbook.” Calling to_excel() again does not extend a workbook that has already been saved; use an ExcelWriter workflow for multiple writes.
Check Excel’s worksheet limits
pandas checks row count, column count and cell character count against Excel limits, but other Excel limitations remain for you to check. If the workbook will be consumed by a specific Excel version or downstream tool, verify its additional constraints as well. See the DataFrame.to_excel API notes.
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