Python – 使用pandas格式化excel单元格

2023年9月17日 425次阅读

我有一个pandas数据帧,如下所示.

《Python – 使用pandas格式化excel单元格》

我想格式化“通过/失败”列,就好像失败 – >红色背景,否则绿色背景,如：

《Python – 使用pandas格式化excel单元格》

我曾尝试使用Pandas进行格式化,但无法为excel添加颜色.以下是代码：

writer = pandas.ExcelWriter(destination,engine = 'xlsxwriter')
color = Answer.style.applymap(lambda x: 'color: red' if x == "Fail" else 'color: green',subset= pandas.IndexSlice[:,['Pass/Fail']])
color.to_excel(writer,'sheet1')

我尝试了无法安装的StyleFrame.似乎StyleFrame不符合我的python版本3.6.

如何根据需要格式化excel？

最佳答案 你可以使用
conditional_format：

df = pd.DataFrame({'Pass/Fail':['Pass','Fail','Fail'],
                   'expect':[1,2,3]})
print (df)
  Pass/Fail  expect
0      Pass       1
1      Fail       2
2      Fail       3

writer = pd.ExcelWriter('pandas_conditional.xlsx', engine='xlsxwriter')
df.to_excel(writer, sheet_name='Sheet1')
workbook  = writer.book
worksheet = writer.sheets['Sheet1']
red_format = workbook.add_format({'bg_color':'red'})
green_format = workbook.add_format({'bg_color':'green'})

worksheet.conditional_format('B2:B4', {'type': 'text',
                                      'criteria': 'containing',
                                       'value':     'Fail',
                                       'format': red_format})

worksheet.conditional_format('B2:B4', {'type': 'text',
                                      'criteria': 'containing',
                                       'value':   'Pass',
                                       'format':  green_format})
writer.save()

更多动态解决方案,get_loc用于列位置和字典映射：

import string

df = pd.DataFrame({'Pass/Fail':['Pass','Fail','Fail'],
                   'expect':[1,2,3]})
print (df)
  Pass/Fail  expect
0      Pass       1
1      Fail       2
2      Fail       3

writer = pd.ExcelWriter('pandas_conditional.xlsx', engine='xlsxwriter')
df.to_excel(writer, sheet_name='Sheet1')
workbook  = writer.book
worksheet = writer.sheets['Sheet1']
red_format = workbook.add_format({'bg_color':'red'})
green_format = workbook.add_format({'bg_color':'green'})

#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'}

#set column for formatting
col = 'Pass/Fail'
excel_header = str(d[df.columns.get_loc(col)])
#get length of df
len_df = str(len(df.index) + 1)
rng = excel_header + '2:' + excel_header + len_df
print (rng)
B2:B4

worksheet.conditional_format(rng, {'type': 'text',
                                      'criteria': 'containing',
                                       'value':     'Fail',
                                       'format': red_format})

worksheet.conditional_format(rng, {'type': 'text',
                                      'criteria': 'containing',
                                       'value':   'Pass',
                                       'format':  green_format})
writer.save()

EDIT1：

感谢jmcnamara的评论和XlsxWriter

col = 'Pass/Fail'
loc = df.columns.get_loc(col) + 1
len_df = len(df.index) + 1

worksheet.conditional_format(1,loc,len_df,loc, {'type': 'text',
                                      'criteria': 'containing',
                                       'value':     'Fail',
                                       'format': red_format})

worksheet.conditional_format(1,loc,len_df,loc, {'type': 'text',
                                      'criteria': 'containing',
                                       'value':   'Pass',
                                       'format':  green_format})
writer.save()

编辑：

最后一个版本的pandas(0.20.1)和styles的另一个解决方案：

df = pd.DataFrame({'Pass/Fail':['Pass','Fail','Fail'],
                   'expect':['d','f','g']})
print (df)
  Pass/Fail expect
0      Pass      d
1      Fail      f
2      Fail      g

def f(x):
    col = 'Pass/Fail'
    r = 'background-color: red'
    g = 'background-color: green'
    c = np.where(x[col] == 'Pass', g, r)
    y = pd.DataFrame('', index=x.index, columns=x.columns)
    y[col] = c
    return y

styled = df.style.apply(f, axis=None)
styled.to_excel('styled.xlsx', engine='openpyxl')
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