def data_indexer(df):
    """Data indexing by subject and timepoint.
    Will remove all quotes.
    
    Not used now.

    In [34]: bigdict = {}
    
    In [35]: for line in w[1:]:
        ...:     # construct index subj_timepoint_cellpopulation
        ...:     a = line.split('	')
        ...:     k = a[1].replace('"', '').replace('.372', '') + '_' + a[6] + '_' + a[11].replace('"', '')
        ...:     bigdict[k] = a[8]
        ...:     
    
    In [36]: bigdict.items()[:4]
    Out[36]: 
    [('SUB135758_90_CD8+ T cell', '"510.6118469238281"'),
     ('SUB135773_28_Tfh17 CD4+ T cell', '"21.569305419921875"'),
     ('SUB135772_28_CD40- BDCA3+ myeloid dendritic cell', '"0.37419480085372925"'),
     ('SUB135772_0_HLA-DR+ Th1 CD4+ T cell', '"0.06463897228240967"')]
    
    In [37]: # construct wanted list
    
    In [38]: s = 'CellPopulation	' + '	'.join(populations) + '
'
    
    In [39]: row = [x+"_0_" for x in subjects] + [x+"_1_" for x in subjects] + [x+"_7_" for x in subjects] + [x+"_28_" for
        ...:  x in subjects] + [x+"_90_" for x in subjects]
    
    In [40]: len(row)
    Out[40]: 85
    
    In [41]: row[:4]
    Out[41]: ['SUB135758_0_', 'SUB135759_0_', 'SUB135760_0_', 'SUB135761_0_']
    
    In [42]: s = 'CellPopulation	' + '	'.join(row) + '
'
    
    In [43]: for p in populations:
        ...:     s += p + '	' + '	'.join([bigdict.get(x+p, 'NA') for x in row]) + '
'
        ...:     
    
    In [44]: with open('formatted_SDY372_fcs_analyzed_result.txt', 'w') as O:
        ...:     O.write(s)
        ...:     
    
    In [45]: # quotes included in the output above
    


    """
    value_dict = {}
    return value_dict
