import pandas as pdimport numpy as npimport os,sysdf = pd.read_excel("C:\\Users\\ryanzhang\\Desktop\\template.xlsx")a = df.columnsb = pd.DataFrame(a,a)c = b.Td = c.append(df)def highlight_max(s):    if s.name == 0:    #print(['background-color: yellow' if v else '' for v in is_max])        return ['background-color: yellow']*len(s)    else:        return ['']*len(s)    one = df.style.set_properties(**{
   'border-style': 'solid','border-width':'1px','text-align':'left'})two = one.apply(highlight_max,axis=1)two.to_excel("C:\\Users\\ryanzhang\\Desktop\\test.xlsx",header=False, index=False,)

 

import pandas as pda = [["ryan","job","can"],["good","you","me"],["ryan","hello","how"],["any","each","where"]]name = ["one","two","three"]index = ["four","five","six","seven"]b = pd.DataFrame(a,index=index,columns=name)print(b,"\n")def need_group(index):    if b.loc[index]["one"] =="ryan":        return 1    elif b.loc[index]["one"] =="good":        return 1    elif b.loc[index]["one"] =="any":        return 3c = b.groupby(need_group)for i,j in c:    print(i,"\n",j)