how to add sub headings to the html table using pandas dataframes and how can we access dataframe data to html table?

Question

Below if my dataframe

html = data.to_html()

I am getting output table as :

by i want output table as :

Code:

data = [[0,65247.0,53306.0,112.0,6524.0,53306.0,112.0], [1,55695.0,43214.0,0.0,5569.0,43214.0,0.0], [2,78345.0,65189.0,0.0,7834.0,65189.0,0.0], [3,16151.0,14057.0,0.0,1615.0,14057.0,0.0],[4,13960.0,12062.0,0.0,1396.0,12062.0,0.0]] 

df = pd.DataFrame(data, columns = ['HOUR','SUB','DEL %','WAIT %', 'SUB','DEL %','WAIT %']) 

Answer 1

Have duplicate columns isn't a good idea, adding the suffix can help

df.columns = pd.MultiIndex.from_tuples((('', 'HOUR'), ('BSNL_WEST', 'SUB'), ('BSNL_WEST', 'DEL %'), ('BSNL_WEST', 'WAIT %'), ('BSNL_NORTH', 'SUB_2'), ('BSNL_NORTH', 'DEL %_2'), ('BSNL_NORTH', 'WAIT %_2')))

Results in

         BSNL_WEST                 BSNL_NORTH
  HOUR       SUB    DEL % WAIT %      SUB_2  DEL %_2 WAIT %_2
0    0   65247.0  53306.0  112.0     6524.0  53306.0    112.0
1    1   55695.0  43214.0    0.0     5569.0  43214.0      0.0
2    2   78345.0  65189.0    0.0     7834.0  65189.0      0.0
3    3   16151.0  14057.0    0.0     1615.0  14057.0      0.0
4    4   13960.0  12062.0    0.0     1396.0  12062.0      0.0

Answer 2

You can try this, i tried it on your data set:

testdf = df
testdf = testdf.drop(columns='HOUR')
columns=[('BSNL_WEST', 'SUB'), ('BSNL_WEST', 'DEL %'), ('BSNL_WEST', 'WAIT %'),('BSNL_NORTH', 'SUB'), ('BSNL_NORTH', 'DEL %'), ('BSNL_NORTH', 'WAIT %') ] 
testdf.columns = pd.MultiIndex.from_tuples(columns)
testdf = testdf.rename_axis(columns=['HOUR','HOUR']) 

I changed to your dataframe:

HOUR BSNL_WEST                 BSNL_NORTH                
HOUR       SUB    DEL % WAIT %        SUB    DEL % WAIT %
0      65247.0  53306.0  112.0     6524.0  53306.0  112.0
1      55695.0  43214.0    0.0     5569.0  43214.0    0.0
2      78345.0  65189.0    0.0     7834.0  65189.0    0.0
3      16151.0  14057.0    0.0     1615.0  14057.0    0.0
4      13960.0  12062.0    0.0     1396.0  12062.0    0.0

You can set the hour as index, but it won't format the same as how an excel spreadheet does:

testdf.rename_axis(index=['HOUR']) 

     BSNL_WEST                 BSNL_NORTH                
           SUB    DEL % WAIT %        SUB    DEL % WAIT %
HOUR                                                     
0      65247.0  53306.0  112.0     6524.0  53306.0  112.0
1      55695.0  43214.0    0.0     5569.0  43214.0    0.0
2      78345.0  65189.0    0.0     7834.0  65189.0    0.0
3      16151.0  14057.0    0.0     1615.0  14057.0    0.0
4      13960.0  12062.0    0.0     1396.0  12062.0    0.0