CODEWITHSUNDEEP
pythoncsv
jcross
jcross

Reputation: 57

Search csv file for specific items in columns

I am trying to create a loop that searches through a csv file for rows with a common 3rd and 4th column and performs an operation on them.
The file I have looks like this: 

name1,x,y,z,notes
name2,a,b,c,notes
name3,a,y,z,notes

I am using a code that reads the first line and identifies row[2] and row[3] and performs searches all rows in the file for that combination of columns. Unfortunately, I can't seem to figure out how to actually search them. 

for row in csvfile:
    row_identify = row[2:3]
    for row in csvfile:
        if row_identify in row:
            print row
        else:
            print "not here"

I want it to print the first and third row (since y and z would be row_identify). I assumed I could just explicitly state that I wanted to search for those rows, but that doesn't seem to work. I also tried using 

row_identify =  str(row[2]),str(row[3])

but that doesn't seem to work either.

Upvotes: 5

Views: 617

Answers (2)

inspectorG4dget
inspectorG4dget

Reputation: 114035

If you are looking to identify rows with the same 3rd and 4th columns as the first row:

import csv
import operator

key = operator.itemgetter(2,3)
with open('path/to/input') as infile:
    rows = csv.reader(infile)
    holyGrail = key(next(rows))
    for row in rows:
        if key(row) != holyGrail:
            continue
        do_stuff(row)

If you'd like a more generalized version, clustering all rows that share a similar 3rd and 4th column, then:

import csv
import operator
from collections import defaultdict as dd

key = operator.itemgetter(2,3)
info = operator.itemgetter(0,1)
similarities = dd(list)
with open('path/to/input') as infile:
    for i,row in enumerate(csv.reader(infile)):
        similarities[key(row)].append((i,info(row)))

for k, rows in similarities.items():
    print("These following rows all have the id <{}> (the data follows):".format(k), ', '.join([str(i) for i,_ in rows]))
    print('\n'.join(['\t' + '\t'.join([row]) for _,row in rows])

Upvotes: 0

Ozgur Vatansever
Ozgur Vatansever

Reputation: 52223

You can create a dictionary of pairs where keys are tuples containing identifying columns and values are the list of similar rows:

>>> import collections
>>> similarities = collections.defaultdict(list)

>>> for row in csvfile:
...     similarities[(row[2], row[3])].append(row)

>>> print similarities 
{('y', 'z'): [['name1', 'x', 'y', 'z', 'notes'], 
              ['name3', 'a', 'y', 'z', 'notes']], 
 ('b', 'c'): [['name2', 'a', 'b', 'c', 'notes']]
}

Upvotes: 4

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