使用python在excel中进行背景单元格颜色控制

Question

I would like to be able to control the background cell colour in excel. I have largish amounts of data, and I need to determine if the data meets the expectations or not. This I can do already with Python. However, I would like to display this data in excel, and to make it easier to read, I would like to colour cells according to if the data is good or not.

I have already used style.applymap to assign colour to a cell based on specific cell values. For instance, if the cell says 'fail' then I can colour it red.

So if I go through the data and make a new 'pass'/'fail' list and enter these values into the excel document, I can get what I want in terms of colour. This code is shown below, and I can get something that looks like this

However, if I want to enter the actual values into the cells, then I have no idea how to get the background colours I want.

What I have so far:

import pandas as pd
#in the example, I have a list of office items, chairs and computers
names=['chair1','chair2','chair3','chair4','chair5','computer1','computer2','computer3','computer4','computer5']
#Each name has an assigned type. The type determines what the expectations are for the lifetime
inv_type=['furniture','furniture','furniture','furniture','furniture','electronics','electronics','electronics','electronics','electronics']
#The age of each item before breakdown is recorded here
inv_age=[2.2, 5, 7.3, 0.6, 4.3, 3.2, 1.7, 2.3, 2.2 ,0.9]

# a dictionary defines the minimum expected lifetime
expected_life={'furniture':4,'electronics':2}
# initialise the pass_fail list
inventory_pass_fail=[]

# cyle through the items and append 'pass' or 'fail' to the list depending on if the item 
#has reached the minimum expected age. 
for i in range(len(names)):
    if inv_age[i]>expected_life[inv_type[i]]:
        inventory_pass_fail.append('pass')
    else:
        inventory_pass_fail.append('fail')

#get names, type, and pass/fail list into one list for the excel sheet
final_list_report=list(zip(*[names,inv_type,inventory_pass_fail]))


df = pd.DataFrame(final_list_report,columns=['Name','Type','Pass/Fail'])

#define function that determines background colour
def color_code_by_text(val):
    if val=='N/A' or val=='pass':
        color='background-color: %s' % 'green'
    elif  val=='fail':
        color='background-color: %s' % 'red'
    else:
        color=''
    return color

#use style.applymap and the color_code_by_text function to colour background cells
styled = (df.style.applymap(color_code_by_text))
# and save the end result
styled.to_excel('inventory_report.xlsx', engine='openpyxl')

I have tried overwriting the same file with the actual values. This works, but it gets rid of the colour as well. What I'd like is something like this, where the colour indicates the pass/fail status, but the cell holds the actual number:

Would appreciate any advice, thanks!

Answer 1

Ok, I got something to work. Basically, I run the code that I posted above in the question to get the cell background colours, then I use openpyxl to load that file and edit the cell values line by line. This keeps the background colour.

I added the code shown below under the code in the question, and this works.

from openpyxl import load_workbook

#load the excel file that I just wrote
wb=load_workbook(filename='inventory_report.xlsx')

ws = wb.get_active_sheet()
#edit the sheet line by line inserting each value
for i in range(len(vals_list)):
    ws.cell(row=i+2,column=4).value = vals_list[i][2]

#and overwrite the previous file with the changes made
wb.save('inventory_report.xlsx')