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How can I set different background color and font for some rows or columns when exporting a pandas DataFrame to Excel?
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You can export Pandas DataFrame to an Excel file using to_excel. Here is a template that you may apply in Python to export your DataFrame: df.to_excel(r'Path where the exported excel file will be storedFile Name.xlsx', index = False) And if you want to export your DataFrame to a specific Excel Sheet, then you may use this template:
Read an Excel file into a pandas DataFrame. Read a comma-separated values (csv) file into DataFrame. For compatibility with to_csv () , to_excel serializes lists and dicts to strings before writing. Once a workbook has been saved it is not possible to write further data without rewriting the whole workbook.
The Pandas library in Python has been predominantly used for data manipulation and analysis, but did you know that Pandas also allows for conditional formatting of DataFrames? Conditional formatting is a feature that allows you to apply specific formatting to cells that fulfill certain conditions.
# Set the column width and format. worksheet.set_column('B:B', 18, format1) # Set the format but not the column width. worksheet.set_column('C:C', None, format2) # Close the Pandas Excel writer and output the Excel file. writer.save()
https://pbpython.com/improve-pandas-excel-output.html has examples using xlsxwriter to customize the output file:
writer = pd.ExcelWriter('fancy.xlsx', engine='xlsxwriter')
df.to_excel(writer, index=False, sheet_name='report')
workbook = writer.book
worksheet = writer.sheets['report']
percent_fmt = workbook.add_format({'num_format': '0.0%',
'bold': True
#, 'bg_color': '#FFC7CE'
})
worksheet.set_column('L:L', 12, percent_fmt)
writer.save()
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