Reads a CSV column, writes words and their counts to new CSV

wordcounts.py

import re, csv
import pandas as pd
from collections import Counter
from random import randint

csvfile = 'mycsvfile.csv'
# regex = r'\w+'
regex = r"\b[^\d\W]+\b"  # this will get omit words containing numbers like 4WD or a part number 123ABCD

commonWords = ['a', 'with', 'the', 'and', 'set', 'foot', 'for', 'inch', 'on', 'models',
               'model']

data = pd.read_csv(csvfile)
words = []

for row in data.Title:
    matches = re.findall(regex, row)
    for m in matches:
        if m.lower() != 'rough' and m.lower() != 'country' and m.lower() not in commonWords:
            words.append(m.lower())

for word in words:
    print(word)

print(f'Total count of words: {len(words)}\n')

counts = Counter(words)

try:
    with open('exported_words.csv', 'w', newline='') as csvfile:
        writer = csv.writer(csvfile)
        writer.writerow(["Word", "Occurence"])

        for key, value in counts.items():
            writer.writerow([key, value])
except PermissionError:
    with open('exported_words' + str(randint(100, 500)) + '.csv', 'w', newline='') as csvfile:
        writer = csv.writer(csvfile)
        writer.writerow(["Word", "Occurence"])

        for key, value in counts.items():
            writer.writerow([key, value])