writing .txt to .csv excel columns in Python -


i have rather large text file multiple columns must convert 15 column .csv file read in excel. logic parsing fields need written out below, having trouble writing .csv.

columns = [ 'transactn_nbr', 'record_nbr',          'sequence_or_pic_nbr', 'cr_db', 'rt_nbr', 'account_nbr',          'rsn_cod', 'item_amount', 'item_serial', 'chn_ind',          'reason_descr', 'seq2', 'archive_date', 'archive_time', 'on_us_ind' ]      line in in_file:         values = line.split()         if 'print date:' in line:             dtevalue = line.split(a,1)[-1].split(b)[0]             lines.append(dtevalue)          elif 'print time:' in line:             timevalue = line.split(c,1)[-1].split(b)[0]             lines.append(timevalue)             elif (len(values) >= 4 , values[3] == 'c'             , len(values[2]) >= 2 , values[2][:2] == '41'):             print(values)          elif (len(values) >= 4 , values[3] == 'd'             , values[4] in rtnbr):             on_us = '1'         else:             on_us = '0'  print (lines[0]) print (lines[1])

i have tried csv module parsed rows written in 12 columns , not find way write date , time (parsed separately) in columns after each row looking @ pandas package have seen ways extract patterns, wouldn't work established parsed criteria

is there way write csv using above criteria? or have scrap , rewrite code within specific package? appreciated

edit: text file sample:

    * start ******************************************************************************************************************** start *  * start ******************************************************************************************************************** start *  * start ******************************************************************************************************************** start * 1-------------------- 1antecr09                                                 chek                                                 dpck_r_009                                                      transit extract sub-system     current date = 08/03/2017                             journal     report                                              page    1     process date =  id = 022000046-mnt                                                                           file header = h080320171115                                       +____________________________________________________________________________________________________________________________________      r               t      sequence    cr      bt                rsn               item           item chn          user    reaso         nbr       nbr       or pic nbr  db      nbr              nbr cod             amount         serial ind  .......field..  descr       5,556        01        7450282689 c 538196640        9835177743 15          $9,064.81              00                    credit       5,557        01        7450282690 d 031301422         362313705 38            $592.35           43431                    dr cr       5,558        01        7450282691 d 021309379         601298839 38          $1,491.04           44896                    dr cr       5,559        01        7450282692 d 071108834            176885 38          $6,688.00            1454                    dr cr       5,560        01        7450282693 d 031309123     1390001566241 38            $293.42            6878                    dr cr   --------------------      34,615       207        4100223726 c 538196620        9866597322 10            $645.49              00                    credit      34,616       207        4100223727 d 022000046        8891636675 31            $645.49          111583                    dr on-  --------------------      34,617       208        4100223728 c 538196620          11701364 10            $756.19              00                    credit      34,618       208        4100223729 d 071923828                00 54            $305.31        11384597                    bad ac      34,619       208        4100223730 d 071923828          35110011 30            $450.88        10913052 6                  dr sel  --------------------

desired output: looking @ lines containing seq starting 42, contains c

1293    83834   4100225908  c   538196620   9860890913  10  161.5   0       credit  41  3-aug-17    11:15:51 1294    83838   4100225911  c   538196620   25715845    10  138 0       credit  41  3-aug-17    11:15:51

look @ ‘pandas‘ package, more class dataframe. little cleverness ought able read table using ‘pandas.read_table()‘ returns dataframe can output csv ‘to_csv()‘ 2 line solution. you’ll need @ docs find parameters you’ll need read table format, should little easier doing manually.


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