读取csv文件并使用文本换行将df写入excel

Question

I am trying to get the following output. All rows and columns are text wrapped except the header though:

import pandas as pd
    import pandas.io.formats.style
    import os
    from pandas import ExcelWriter
    import numpy as np

    from xlsxwriter.utility import xl_rowcol_to_cell
    writer = pd.ExcelWriter('test1.xlsx',engine='xlsxwriter',options={'strings_to_numbers': True},date_format='mmmm dd yyyy')  
    df = pd.read_csv("D:\\Users\\u700216\\Desktop\\Reports\\CD_Counts.csv")
    df.to_excel(writer,sheet_name='Sheet1',startrow=1 , startcol=1, header=True, index=False, encoding='utf8')  
    workbook  = writer.book
    worksheet = writer.sheets['Sheet1']

    format = workbook.add_format()
    format1 = workbook.add_format({'bold': True, 'align' : 'left'})
    format.set_align('Center')
    format1.set_align('Center')
    format.set_text_wrap()
    format1.set_text_wrap()
    worksheet.set_row(0, 20, format1)
    worksheet.set_column('A:Z', 30, format)
    writer.save()

format is applied for all rows and columns except header. i dont know why format is not applied to first column (Header) or i would like to manually add column header numbers such as 0,1,2 etc so that i will turn of the header therefore all the rows and columns will be formatted

In the above screenshot wrap text is not applied to A1 to E1, C1 column has header with lot of space. if i manually click wrap text it gets aligned else all the header is not formatted using text wrap.

Answer 1

A couple of problems:

1. Your code is correctly attempting to format the header, but when you create your file using .to_excel() you are telling it to start at row/col 1, 1 . The cells though are numbered from 0, 0 . So if you change to:

    df.to_excel(writer,sheet_name='Sheet1', startrow=0, startcol=0, header=True, index=False, encoding='utf8') 

   You will see col A and row 1 are both formatted:

   

   ie Col A is 0 and Row 1 is 0

2. When using Pandas to write the header, it applies its own format which will overwrite the formatting you have provided. To get around this, turn off headers and get it to only write the data from row 1 onwards and write the header manually.

The following might be a bit clearer:

import pandas as pd
import pandas.io.formats.style
import os
from pandas import ExcelWriter
import numpy as np

from xlsxwriter.utility import xl_rowcol_to_cell

writer = pd.ExcelWriter('test1.xlsx', engine='xlsxwriter', options={'strings_to_numbers': True}, date_format='mmmm dd yyyy')  
#df = pd.read_csv("D:\\Users\\u700216\\Desktop\\Reports\\CD_Counts.csv")
df = pd.read_csv("CD_Counts.csv")
df.to_excel(writer, sheet_name='Sheet1', startrow=1 , startcol=0, header=False, index=False, encoding='utf8')  
workbook  = writer.book
worksheet = writer.sheets['Sheet1']

format_header = workbook.add_format()
format_header.set_align('center')
format_header.set_bold()
format_header.set_text_wrap()
format_header.set_border()

format_data = workbook.add_format()
format_data.set_align('center')
format_data.set_text_wrap()

worksheet.set_column('A:Z', 20, format_data)
worksheet.set_row(0, 40, format_header)

# Write the header manually
for colx, value in enumerate(df.columns.values):
    worksheet.write(0, colx, value)

writer.save()

Which would give you:

Note: It is also possible to tell Pandas the style to use, or to force it to None so it will inherit your own style. The only drawback with that approach is that the method required to do that depends on the version of Pandas that is being used. This approach works for all versions.