在 Pandas 中将自定义标题添加到数据框并将其转换为 HTML

问：

我正在从目录列表中读取某些 csv 文件，即 actual_results 和 expected_results。现在，我用actual_results浏览每个 csv，并在 expected_results 中比较 csv。然后我想将整个数据显示为 HTML 格式，如下所示

我已经编写了一些代码来实际清理数据，然后比较实际和预期 csv 的数据帧。

以下是整个代码：

import pandas as pd
import sys
from glob import glob
import os
import itertools

# compareCSV takes in two args as path of the two csv files to compare
def compare(expectedList,actualList):
    ctr=0
    dfList = list()
    for (csv1,csv2) in itertools.zip_longest(expectedList,actualList):
        df1_ctr=pd.read_csv(csv1,sep=',')
        df1_ctr[df1_ctr.columns[1:]] = [x.split('\t') for x in df1_ctr['mean(ms)']]
        df1=df1_ctr.apply(pd.to_numeric,errors='coerce')
        df2_ctr=pd.read_csv(csv2,sep=',')
        df2_ctr[df2_ctr.columns[1:]] = [x.split('\t') for x in df2_ctr['mean(ms)']]
        df2=df2_ctr.apply(pd.to_numeric,errors='coerce')
        print("Dataframe for Expected List for file : {} is \n {}".format(csv1,df1))
        print("Dataframe for Actual List for file: {} is \n {}".format(csv2,df2))
        d3=df1.loc[:,:] # Dataframe 1
        d4=df2.loc[:,:] # Dataframe 2
        d5=abs(((d3.subtract(d4))/d3)*100)
        print("Deviation between file {} and {} is :\n {}".format(csv1,csv2,d5))
        ctr=ctr+1  
        #Final Data frame
        df=pd.concat([df1,df2,d5])
        #print("{}".format(df))
        dfList.append(df)   
    #print("Final Data frame: \n{}".format(dfList))
    # for data in dfList:
    #     print("data at index: \n{}".format(data))


if __name__ == "__main__":
    #file1=sys.argv[1]  # FileName1
    #file2=sys.argv[2]  #FileName2
    #compareCSV(file1,file2) # Compare CSV files passed in as paramters
    os.chdir("expected_results")
    expectedCSVs=glob("*.csv")
    #print(expectedCSVs)
    os.chdir("../actual_results")
    actualCSVs=glob("*.csv")
    #print(actualCSVs)
    compare(expectedCSVs,actualCSVs)

我目前有一些多余的打印声明。 上述代码的输出如下：

Dataframe for Expected List for file : CT_QRW_25.csv is 
    100%Q   mean(ms)   P50(ms)     P99(ms)   p99.9(ms)  #Samples
0    NaN   0.038973  0.044939    0.091076    0.363859   1760108
1    NaN   0.050652  0.044963    0.094738    0.402525   1354233
2    NaN   0.046500  0.045020    0.108138    0.320636    123448
3    NaN   1.872630  0.599966   33.313200  172.040000  21954617
4    NaN  37.752900  0.600484  603.063000  805.340000   2708258
Dataframe for Actual List for file: CT_QRW_25.csv is 
    100%Q   mean(ms)   P50(ms)     P99(ms)   p99.9(ms)  #Samples
0    NaN   0.038973  0.044939    0.091076    0.363859   1760108
1    NaN   0.050652  0.044963    0.094738    0.402525   1354233
2    NaN   0.046500  0.045020    0.108138    0.320636    123448
3    NaN   1.872630  0.599966   33.313200  172.040000  21954617
4    NaN  37.752900  0.600484  603.063000  805.340000   2708258
Deviation between file CT_QRW_25.csv and CT_QRW_25.csv is :
    100%Q  mean(ms)  P50(ms)  P99(ms)  p99.9(ms)  #Samples
0    NaN       0.0      0.0      0.0        0.0       0.0
1    NaN       0.0      0.0      0.0        0.0       0.0
2    NaN       0.0      0.0      0.0        0.0       0.0
3    NaN       0.0      0.0      0.0        0.0       0.0
4    NaN       0.0      0.0      0.0        0.0       0.0
Dataframe for Expected List for file : CT_W_14.csv is 
    100%Q  mean(ms)  P50(ms)  P99(ms)  p99.9(ms)   #Samples
0    NaN       NaN      NaN      NaN        NaN        NaN
1    NaN       NaN      NaN      NaN        NaN        NaN
2    NaN       NaN      NaN      NaN        NaN        NaN
3    NaN       NaN      NaN      NaN        NaN        NaN
4    NaN   97.8025  17.8492  725.619    891.455  5304765.0
Dataframe for Actual List for file: CT_W_14.csv is 
    100%Q  mean(ms)  P50(ms)  P99(ms)  p99.9(ms)   #Samples
0    NaN       NaN      NaN      NaN        NaN        NaN
1    NaN       NaN      NaN      NaN        NaN        NaN
2    NaN       NaN      NaN      NaN        NaN        NaN
3    NaN       NaN      NaN      NaN        NaN        NaN
4    NaN   97.8025  17.8492  725.619    891.455  5304765.0
Deviation between file CT_W_14.csv and CT_W_14.csv is :
    100%Q  mean(ms)  P50(ms)  P99(ms)  p99.9(ms)  #Samples
0    NaN       NaN      NaN      NaN        NaN       NaN
1    NaN       NaN      NaN      NaN        NaN       NaN
2    NaN       NaN      NaN      NaN        NaN       NaN
3    NaN       NaN      NaN      NaN        NaN       NaN
4    NaN       0.0      0.0      0.0        0.0       0.0

目标： 由于我目前拥有的语句是打印语句，因此如果我想将其转换为 HTML，我将无法使其动态化。我的目标是将其输出到 HTML 文件中。或者，即使有一种自定义方法可以在数据框中添加行作为标题，也可以。此外，如果偏差大于 10%，那么我想以红色显示单元格。如果有人遇到过这种情况，那就太好了，请帮帮我。任何帮助将不胜感激。