python - pandas to multiple dict objects -

i have scoring scale in table/dataframe. want read read frame , convert multiple dict objects. have table:

col_ref col_cutoff col_value c1      10          100 c1      20          200 c1      miss        500 c1      null        100 c2                250 c2      b           200 c2      null        0 c2      miss        100 

i want convert 2 dict objects:

c1_dict = {     'miss' : 500,     'null'    :100,     'vals'    : [         (10, 100),         (20, 2000)     ] }  c2_dict = {     'miss' : 100,     'null'    :0,     'vals'    : [         (a, 250),         (b, 200)     ] } 

here started with.. can't figure further

import pandas pd  def panda_2_dict(pd):     pdf_ref = pd.read_csv()     col_refs = pd.pdf_ref.[col_ref.distinct]     each in col_refs              col_ref_i = {col_cutoff:col_val}     return col_ref_i 

i expecting list of dict objects(here 2).

you can try:

  col_ref col_cutoff  col_value 0      c1         10        100 1      c1         20        200 2      c1       miss        500 3      c1       null        100 4      c2                 250 5      c2          b        200 6      c2       null          0 7      c2       miss        100  gb = df.groupby('col_ref')  k, v in gb:     print k     = (v[:2].set_index('col_cutoff')['col_value'].to_dict()).items()     b = v[2:].set_index('col_cutoff')['col_value'].to_dict()     b['vals'] =     print b      c1     {'vals': [('10', 100), ('20', 200)], 'null': 100, 'miss': 500}     c2     {'vals': [('a', 250), ('b', 200)], 'null': 0, 'miss': 100}