Parsing CSV tab-delimited txt file with Python

Question

I currently have a CSV file which  when opened in Excel  has a total of 5 columns  Only columns A and C are of any significance to me and the data in the remaining columns is irrelevant   Starting on line 8 and then working in multiples of 7  ie  lines 8  15  22  29  36 etc      I am looking to create a dictionary with Python 2 7 with the information from these fields  The data in column A will be the key  a 6-digit integer  and the data in column C being the respective value for the key  I ve tried to highlight this below but the formatting isn t the best -      A        B      C          D 1                           CDCDCDCD   2                           VDDBDDB 3 4 5 6 7  DDEFEEF                   FEFEFEFE 8  123456         JONES 9 10 11 12 13 14 15 293849         SMITH   As per the above  I am looking to extract the value from A7  DDEFEEF  as a key in my dictionary and  FEFEFEFE  being the respective data and then add another entry to my dictionary  jumping to line 15 with  2938495  being my key and  Smith  being the respective value   Any suggestions  The source file is a  txt file with entries being tab-delimited  Thanks  Clarification   Just to clarify  so far  I have tried the below -  import csv  mydict       f   open  myfile    rt   reader   csv reader f      for row in reader          print row   The above simply prints out all content though a row at a time  I did try  for row 7  in reader  but this returned an error  I then researched it and had a go at the below but it didn t work neither   import csv from itertools import islice  entries   csv reader open  myfile    rb    mydict     key     value    for i in xrange 6       mydict  i 0      I 2       integers representing columns     range   islice entries 6      for entry in range          mydict entries 0    entries 2     integers representing columns

User · Accepted Answer

Start by turning the text into a list of lists. That will take care of the parsing part:

lol = list(csv.reader(open('text.txt', 'rb'), delimiter='\t'))

The rest can be done with indexed lookups:

d = dict()
key = lol[6][0]      # cell A7
value = lol[6][3]    # cell D7
d[key] = value       # add the entry to the dictionary
 ...

User · Answer

Although there is nothing wrong with the other solutions presented  you could simplify and greatly escalate your solutions by using python s excellent library pandas  Pandas is a library for handling data in Python  preferred by many Data Scientists  Pandas has a simplified CSV interface to read and parse files  that can be used to return a list of dictionaries  each containing a single line of the file  The keys will be the column names  and the values will be the ones in each cell  In your case      import pandas      def create dictionary filename           my data   pandas DataFrame from csv filename  sep   t   index col False            Here you can delete the dataframe columns you don t want          del my data  B           del my data  D                           Now you transform the DataFrame to a list of dictionaries         list of dicts    item for item in my data T to dict   values            return list of dicts    Usage  x   create dictionary  quot myfile csv quot

User · Answer

If the file is large  you may not want to load it entirely into memory at once  This approach avoids that   Of course  making a dict out of it could still take up some RAM  but it s guaranteed to be smaller than the original file    my dict      for i  line in enumerate file       if  i - 8    7          continue     k  v   line split   t    3 2      my dict k    v   Edit  Not sure where I got extend from before  I meant update

[python] Parsing CSV / tab-delimited txt file with Python

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