delete rows in csv based on specific column value – python without using pandas

Question

I have a large csv with the following header columns id, type, state, location, number of students

and the following values:

124, preschool, Pennsylvania, Pittsburgh, 1242
421, secondary school, Ohio, Cleveland, 1244
213, primary school, California, Los Angeles, 3213
155, secondary school, Pennsylvania, Pittsburgh, 2141
etc...

The file is not ordered and I want a new csv file that contains all the schools with the number of students above 2000.

The answers that I found were regarding to ordered csv files, or splitting them after a specific number of rows.

Asked By: monchisan

||

Source

Answer 1

Here’s a solution using csv module:

import csv

with open('fin.csv', 'r') as fin, open('fout.csv', 'w', newline='') as fout:

    # define reader and writer objects
    reader = csv.reader(fin, skipinitialspace=True)
    writer = csv.writer(fout, delimiter=',')

    # write headers
    writer.writerow(next(reader))

    # iterate and write rows based on condition
    for i in reader:
        if int(i[-1]) > 2000:
            writer.writerow(i)

Result:

id,type,state,location,number of students
213,primary school,California,Los Angeles,3213
155,secondary school,Pennsylvania,Pittsburgh,2141

Answered By: jpp

Answer 2

In case you just want to read file and avoid any other processing, you can use regex – (assuming this is the last column, and value are positive integers) –

import re
f1 = open('Test1.txt','wb')
with open("Test.txt") as f:
    for line in f:
        match = re.search(r'[2-9][0-9]{3,}$', line)
        if (match):
            f1.write(line)

f1.close()

Same thing will be much faster if you do it on bash –

while read line; do
  K='[2-9][0-9]{3,}$'
  if [[ $line =~ $K ]] ; then echo $line; fi
done <Test.txt

Answered By: Aritesh

delete rows in csv based on specific column value – python without using pandas

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