title: Parsing CSV / tab-delimited txt file with Python
body: <p>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.</p>
  
  <p>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:-</p>
  
  <pre><code>    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
  </code></pre>
  
  <p>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.</p>
  
  <p>Any suggestions? The source file is a .txt file with entries being tab-delimited.
  Thanks</p>
  
  <p>Clarification:</p>
  
  <p>Just to clarify, so far, I have tried the below:-</p>
  
  <pre><code>import csv
  
  mydict = {:}
  f = open("myfile", 'rt')
  reader = csv.reader(f)
      for row in reader:
          print row
  </code></pre>
  
  <p>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:</p>
  
  <pre><code>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
  </code></pre>