Countif and Sort, 1 million times faster

From time to time, I got to deal with CSVs that are millions lines each, whether the data is from large datasets or from web scraping.

One time, I extracted the followings of the followers of an account, having in mind to know with which accounts they were competing on their audience.

That was an 10k followers account - and, give or take, each follower was in average following 800 accounts as well: that's 8,000,000 lines in total. And I had this data in a CSV, not in a database (oup's).

Question is: what are the accounts the most followed by the follower of an account?

That's a basic COUNTIF question.

Excel only takes into account a little more than 1,000,000 rows. Even more - try to perform a =COUNTIF() on 1 million rows. You'll get the result two days after.

So here I'm just sharing a little Python script, that actually does the work in less than 2 minutes. I'm leaving comments to explain the script below.

Hope it'll help someone!

import csv
import collections
id_followed = collections.Counter() ## we initialize the COUNTIF column as a Counter
outFile = open('occurences.csv','w') ## first output file
outFileSorted = open('sorted.csv','w') ## second output file, sorted
listLines = []
## the output-followings.csv file structure was:
## id_follower, id_following, username_following
## 123456, 7890987, following1
## 123456, 0987890, following2
with open('output-followings.csv','r') as input_file:
   for row in csv.reader(input_file, delimiter=','):
       print(row[2]) ## prints in console the username
       id_followed[row[2]] += 1 ## increment in the Counter corresponding to the username
with open('sorted.csv','w') as sortedfile:
    writer = csv.writer(sortedfile)
    for key, value in id_followed.most_common(1000): # most_common() gives us the possibility to directly sort the Counter
        line = str(key) + ',' + str(value)
        writer.writerow(line.split()) # we write in the sorted.csv file
with open('occurences.csv','w') as csvfile:
   writer = csv.writer(csvfile)
   for key, value in id_followed.items():
       line = str(key) + ',' + str(value)
       writer.writerow(line.split()) # we write all the rows in the outFile
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