In [23]:

    

%run basics
import collections
import xlrd


    

In [7]:

    

cfname = "../controlfiles/Whroo/all/L6.txt"
cf = qcio.get_controlfilecontents(cfname)


    

In [18]:

    

cpd_path = "../"+cf["Files"]["file_path"]
cpd_name = cpd_path+cf["Files"]["cpd_filename"]
cpd_wb = xlrd.open_workbook(cpd_name)
annual_ws = cpd_wb.sheet_by_name("Annual")
header_list = [x for x in annual_ws.row_values(0)]
year_list = [str(int(x)) for x in annual_ws.col_values(0)[1:]]


    

In [19]:

    

print header_list
print year_list


    

    




['', u'total', u'norm_a1_median', u'norm_a2_median', u'qcpass', u'qcpass_prop', u'a_valid', u'b_valid', u'ustar_mean', u'ustar_sig', u'ustar_n', u'crit_t', u'95%ci_lower', u'95%ci_upper', u'skew', u'kurt']
['2012', '2013', '2014']

In [35]:

    

cpd_annual_dict = collections.OrderedDict()
for i,year in enumerate(year_list):
    cpd_annual_dict[year] = collections.OrderedDict()
    for item in header_list:
        xlcol = header_list.index(item)
        cpd_annual_dict[year][item] = annual_ws.col_values(xlcol)[i+1]


    

In [36]:

    

print cpd_annual_dict.keys()


    

    




['2012', '2013', '2014']

In [37]:

    

print cpd_annual_dict["2012"]["95%ci_lower"]


    

    




0.233119723805

In [38]:

    

for year in cpd_annual_dict.keys():
    print year,cpd_annual_dict[year]["ustar_mean"]


    

    




2012 0.390355641344
2013 0.423973924194
2014 0.411640974614

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