Exporting many excel files based on column value in pandas dataframe while maintaining formatting?

Question

I have a dataframe that I would like to parse to individual files based on unique strings in a column "names." I can do this with a simple function like:

f= lambda x: x.to_excel(os.getcwd()+'\{}.xlsx'.format(x.name), index= False)
df.groupby('names').apply(f)

The caveat being that I would like write out these files with conditional formatting. I’ve been able to achieve the desired formatting using ExcelWriter in the following block:

writer= pd.ExcelWriter('Test.xlsx', engine='xlsxwriter' )
df.to_excel(writer, sheet_name='Sheet1', index=False)
workbook= writer.book
worksheet= writer.sheets['Sheet1']
format1= workbook.add_format({'font_color':'#ec5a24'})
format2= workbook.add_format({'bg_color':'#4b4b4b','font_color':'#ffde00'})
format3= workbook.add_format({'font_color':'#86b05b'})
worksheet.conditional_format('A2:AM10000',{'type':'formula','criteria':'=INDIRECT("E"&ROW())= "High"', 'format':format1})
worksheet.conditional_format('A2:AM10000',{'type':'formula','criteria':'=INDIRECT("E"&ROW())= "Med"', 'format':format2})
worksheet.conditional_format('A2:AM10000',{'type':'formula','criteria':'=INDIRECT("E"&ROW())= "Normal"', 'format':format3})
workbook.close()
writer.save()

Is there a method that would allow me to combine these two so that my output is many files (one for each unique name in the column names) which has the desired conditional formatting in the excel files?

New Code per request:

def new_func():
    f= lambda x: x.to_excel(os.getcwd()+'\{}.xlsx'.format(x.name), index= False)
    writer= pd.ExcelWriter(x.name, engine='xlsxwriter' )
    df.to_excel(writer, sheet_name='Sheet1', index=False)
    workbook= writer.book
    worksheet= writer.sheets['Sheet1']
    format1= workbook.add_format({'font_color':'#ec5a24'})
    format2= workbook.add_format({'bg_color':'#4b4b4b','font_color':'#ffde00'})
    format3= workbook.add_format({'font_color':'#86b05b'})
    worksheet.conditional_format('A2:AM10000',{'type':'formula','criteria':'=INDIRECT("E"&ROW())= "High"', 'format':format1})
    worksheet.conditional_format('A2:AM10000',{'type':'formula','criteria':'=INDIRECT("E"&ROW())= "Med"', 'format':format2})
    worksheet.conditional_format('A2:AM10000',{'type':'formula','criteria':'=INDIRECT("E"&ROW())= "Low"', 'format':format3})
    workbook.close()
    writer.save()
df.groupby('names').apply(new_func())

Asked By: StephenD

||

Source

Answer 1

A few edits to your code. It may take a bit of debugging to get it right. hard to tell as I don’t have the data to test with. but i think you are on the right track

def new_func(x): # add x as and object to be passed to the function
    # remove f= lambda x: from line below. you aren't calling a lambda function any longer
    x.to_excel(os.getcwd()+'\{}.xlsx'.format(x.name), index= False)
    writer= pd.ExcelWriter(x.name, engine='xlsxwriter' )
    # the df below should be x, I think???
    x.to_excel(writer, sheet_name='Sheet1', index=False)
    workbook= writer.book
    worksheet= writer.sheets['Sheet1']
    format1= workbook.add_format({'font_color':'#ec5a24'})
    format2= workbook.add_format({'bg_color':'#4b4b4b','font_color':'#ffde00'})
    format3= workbook.add_format({'font_color':'#86b05b'})
    worksheet.conditional_format('A2:AM10000',{'type':'formula','criteria':'=INDIRECT("E"&ROW())= "High"', 'format':format1})
    worksheet.conditional_format('A2:AM10000',{'type':'formula','criteria':'=INDIRECT("E"&ROW())= "Med"', 'format':format2})
    worksheet.conditional_format('A2:AM10000',{'type':'formula','criteria':'=INDIRECT("E"&ROW())= "Low"', 'format':format3})
    workbook.close()
    writer.save()
df.groupby('names').apply(new_func) #removed () after new_func. I don't think you need it with the current syntax

Answered By: Jonathan Leon

Answer 2

Here is the solution that worked for me (I added a header format too), using a lot of help from johathan:

def new_func(x):
        writer= pd.ExcelWriter(os.getcwd()+'\{}.xlsx'.format(x.name), engine='xlsxwriter' )
        x.to_excel(writer, sheet_name='Sheet1', index=False)
        workbook= writer.book
        worksheet= writer.sheets['Sheet1']
        format1= workbook.add_format({'font_color':'#ec5a24'})
        format2= workbook.add_format({'bg_color':'#4b4b4b','font_color':'#ffde00'})
        format3= workbook.add_format({'font_color':'#86b05b'})
        header= workbook.add_format({'font_size':14, 'bold': True, 'font_color':'#3582c0'})
        worksheet.conditional_format('A2:AM10000',{'type':'formula','criteria':'=INDIRECT("E"&ROW())= "High"', 'format':format1})
        worksheet.conditional_format('A2:AM10000',{'type':'formula','criteria':'=INDIRECT("E"&ROW())= "Med"', 'format':format2})
        worksheet.conditional_format('A2:AM10000',{'type':'formula','criteria':'=INDIRECT("E"&ROW())= "Low"', 'format':format3})
        pandas.io.formats.excel.ExcelFormatter.header_style = None
        worksheet.set_row(0, None, header)
        workbook.close()
        writer.save()
    
       
df.groupby('name').apply(new_func)

Answered By: StephenD

Exporting many excel files based on column value in pandas dataframe while maintaining formatting?

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