Python searching through columns
<p>I have a CSV file that I need to loop through in a specific pattern for specific columns and have the output patterns be stored in new files with the same name + "_pattern" + [1,2,3,etc.] + .csv.</p>

<p>This is the search pattern: Loop through column 1 and find the same # and grab them, then loop through column 2 of the grabbed list and then grab all that have the same date in column 2, then go to column 4 and grab all #s that are NOT the same, and then create a file with the pattern from column 1 and 2 and 4 organized by column time.</p>

<p>Example: </p>

<pre class="lang-none prettyprint-override"><code>1       2           time    4
13.45   9/29/2016   6:00    98765
12.56   9/29/2016   6:05    76548
13.45   9/29/2016   6:07    98764
13.45   9/29/2016   6:21    98766
13.45   9/29/2016   6:20    96765
12.56   9/29/2016   6:06    76553
</code></pre>

<p><a href="https://i.stack.imgur.com/OqxcG.jpg" rel="nofollow">Better view of table</a></p>

<p>The result would be, file_pattern_1.csv would have:</p>

<pre class="lang-none prettyprint-override"><code>1. 13.45    9/29/2016   6:00    98765
2. 13.45    9/29/2016   6:07    98764
3. 13.45    9/29/2016   6:21    98766
</code></pre>

<p>But would not include:</p>

<pre class="lang-none prettyprint-override"><code>4. 13.45    9/29/2016   6:20    96765 
</code></pre>

<p>Because column 4 repeats from a previous entry, file_pattern_2.csv would have:</p>

<pre class="lang-none prettyprint-override"><code>1. 12.56    9/29/2016   6:05    76548
2. 12.56    9/29/2016   6:06    76553
</code></pre>

<p>This is what I have so far but I have become lost on the looping logic:</p>

<pre><code>import os

infile = raw_input("Which file are we working with? ")
assert os.path.exists(infile), "Path is incorrect."
os.chdir(infile)

def createFile(csvFile, fileName):
    with open (fileName, 'wb') as ftext:
        ftext.write(csvFile)

def appendFile(csvFile, fileName):
    with open (fileName, 'a') as ftext:
        ftext.write(csvFile)

def setfilename(tread):
    fileName = tread[0:tread.index('.')] + '_patterns' + str(countItem) + '.csv'
    return fileName

for i in pcolumn:
    if pcolumn == pcolumn:
        return pfile
    for x in date:
        if date == date:
            return date
            for a in acolumn:
                if acolumn != acolumn:
                    createFile(fileName)
else:
    print "Finished."
</code></pre>

<p>The following should do what you need. It reads a csv file in and generates a matching <code>datetime</code> for each of the entries to allow them to be correctly sorted. It creates output csv files based on the pattern number with the entries sorted by date. Column 4 entries already seen are omitted:</p>

<pre><code>from itertools import groupby
from datetime import datetime
import csv
import os

filename = 'my_data.csv'
data = []

with open(filename, 'rb') as f_input:
    csv_input = csv.reader(f_input, delimiter='\t')
    header = next(csv_input)

    for row in csv_input:
        dt = datetime.strptime('{} {}'.format(row[2], row[1]), '%H:%M %m/%d/%Y')
        data.append([dt] + row)

for index, (k, g) in enumerate(groupby(sorted(data, key=lambda x: x[1]), key=lambda x: x[1]), start=1):
    line = 1
    seen = set()

    with open('{}_pattern_{}.csv'.format(os.path.splitext(filename)[0], index), 'wb') as f_output:
        csv_output = csv.writer(f_output)

        for item in sorted(g, key=lambda x: x[0]):
            if item[4] not in seen:
                seen.add(item[4])
                csv_output.writerow([line] + item[1:])
                line += 1
</code></pre>

python loops csv