pandas.DataFrame.to_excel¶
-
DataFrame.
to_excel
(excel_writer, sheet_name='Sheet1', na_rep='', float_format=None, columns=None, header=True, index=True, index_label=None, startrow=0, startcol=0, engine=None, merge_cells=True, encoding=None, inf_rep='inf', verbose=True, freeze_panes=None)[source]¶ Write DataFrame to an excel sheet
Parameters: excel_writer : string or ExcelWriter object
File path or existing ExcelWriter
sheet_name : string, default ‘Sheet1’
Name of sheet which will contain DataFrame
na_rep : string, default ‘’
Missing data representation
float_format : string, default None
Format string for floating point numbers
columns : sequence, optional
Columns to write
header : boolean or list of string, default True
Write out column names. If a list of string is given it is assumed to be aliases for the column names
index : boolean, default True
Write row names (index)
index_label : string or sequence, default None
Column label for index column(s) if desired. If None is given, and header and index are True, then the index names are used. A sequence should be given if the DataFrame uses MultiIndex.
startrow :
upper left cell row to dump data frame
startcol :
upper left cell column to dump data frame
engine : string, default None
write engine to use - you can also set this via the options
io.excel.xlsx.writer
,io.excel.xls.writer
, andio.excel.xlsm.writer
.merge_cells : boolean, default True
Write MultiIndex and Hierarchical Rows as merged cells.
encoding: string, default None
encoding of the resulting excel file. Only necessary for xlwt, other writers support unicode natively.
inf_rep : string, default ‘inf’
Representation for infinity (there is no native representation for infinity in Excel)
freeze_panes : tuple of integer (length 2), default None
Specifies the one-based bottommost row and rightmost column that is to be frozen
New in version 0.20.0.
Notes
If passing an existing ExcelWriter object, then the sheet will be added to the existing workbook. This can be used to save different DataFrames to one workbook:
>>> writer = pd.ExcelWriter('output.xlsx') >>> df1.to_excel(writer,'Sheet1') >>> df2.to_excel(writer,'Sheet2') >>> writer.save()
For compatibility with to_csv, to_excel serializes lists and dicts to strings before writing.