how to color selected columns in python dataframe?

Question

I am using the below code to export my df to excel, I have a requirement to color the particular columns in the output excel.

# DF TO EXCEL
from pandas import Ex         


        

Answer 1

You can use:

import string
np.random.seed(100)
df = pd.DataFrame(np.random.randint(10, size=(5,5)), columns=list('GHIJK'))
print (df)
   G  H  I  J  K
0  8  8  3  7  7
1  0  4  2  5  2
2  2  2  1  0  8
3  4  0  9  6  2
4  4  1  5  3  4

If need set all selected columns to same color:

writer = pd.ExcelWriter('file1.xlsx', engine='xlsxwriter')
df.to_excel(writer, sheet_name='Sheet1')

#set format
workbook = writer.book
format = workbook.add_format({'bg_color': 'red'})
worksheet = writer.sheets['Sheet1']

#dict for map excel header, first A is index, so omit it
d = dict(zip(range(25), list(string.ascii_uppercase)[1:]))
print (d)
{0: 'B', 1: 'C', 2: 'D', 3: 'E', 4: 'F', 5: 'G', 6: 'H', 7: 'I', 8: 'J',
 9: 'K', 10: 'L', 11: 'M', 12: 'N', 13: 'O', 14: 'P', 15: 'Q', 16: 'R', 
 17: 'S', 18: 'T', 19: 'U', 20: 'V', 21: 'W', 22: 'X', 23: 'Y', 24: 'Z'}

 #select columns of df
cols = ['G','J','K']

#in loop set background color where are data
#http://xlsxwriter.readthedocs.io/working_with_conditional_formats.html
for col in cols:
    excel_header = str(d[df.columns.get_loc(col)])
    len_df = str(len(df.index) + 1)

    rng = excel_header + '2:' + excel_header + len_df
    worksheet.conditional_format(rng, {'type': 'no_blanks',
                                       'format': format})
writer.save()

If need set all selected columns to different color:

writer = pd.ExcelWriter('file1.xlsx', engine='xlsxwriter')
df.to_excel(writer, sheet_name='Sheet1')

#set format
workbook = writer.book
worksheet = writer.sheets['Sheet1']

#dict for map excel header, first A is index, so omit it
d = dict(zip(range(25), list(string.ascii_uppercase)[1:]))
print (d)
{0: 'B', 1: 'C', 2: 'D', 3: 'E', 4: 'F', 5: 'G', 6: 'H', 7: 'I', 8: 'J',
 9: 'K', 10: 'L', 11: 'M', 12: 'N', 13: 'O', 14: 'P', 15: 'Q', 16: 'R', 
 17: 'S', 18: 'T', 19: 'U', 20: 'V', 21: 'W', 22: 'X', 23: 'Y', 24: 'Z'}

 #select columns of df
cols = ['G','J','K']
colors = ['red','yellow','blue']

#in loop set background color where are data
#http://xlsxwriter.readthedocs.io/working_with_conditional_formats.html
for i, col in enumerate(cols):
    format = workbook.add_format({'bg_color': colors[i]})
    excel_header = str(d[df.columns.get_loc(col)])
    len_df = str(len(df.index) + 1)

    rng = excel_header + '2:' + excel_header + len_df
    worksheet.conditional_format(rng, {'type': 'no_blanks',
                                       'format': format})
writer.save()

Answer 2

A little update for those that would find this question; today Pandas is including style functions and styler objects, and this is extremely practical to achieve what you want without going through very convoluted methods. https://pandas.pydata.org/pandas-docs/stable/style.html