I can’t figure out how to get python to count each of the instances of each keyword and put them in a list "count_of_occ". It will output to one row.

from collections import Counter
import pandas as pd
import bs4
import requests
keywords = ["Goulds", "Pump", "http"]
df = pd.DataFrame({'Keyword': keywords})
URL = ["https://www.gouldspumps.com/en-US/Home/"]
for r in URL:
    ctnt=requests.get(r, verify=False)
output_content = str(ctnt.content)
count_of_occ = [0 for i in keywords]
for num in count_of_occ:
    for i in keywords:
        if i in output_content:
            count_of_occ[num] += output_content.count(i)
df['Occurence'] = pd.Series(count_of_occ, index=df.index)
print(df)

Output:
  Keyword  Occurence
0  Goulds        429
1    Pump          0
2    http          0

>Solution :

Here’s an example that demonstrates the issue:

count_of_occ = [0, 0, 0]

for num in count_of_occ:
    count_of_occ[num] += 5

print(count_of_occ)

you might expect the above to output [5, 5, 5], but it’ll actually print [15, 0, 0]. The for-loop has 3 iterations, but since it’s iterating through [0, 0, 0], num is always 0 so count_of_occ[num] is always the first list item.

Here’s a script that accomplishes what you’re looking for:

import pandas as pd
import requests

keywords = ["Goulds", "Pump", "http"]
df = pd.DataFrame({'Keyword': keywords})
URL = ["https://www.gouldspumps.com/en-US/Home/"]
for r in URL:
    ctnt = requests.get(r, verify=False)
output_content = str(ctnt.content)
df['Occurence'] = pd.Series(output_content.count(i) for i in keywords)
print(df)

  Keyword  Occurence
0  Goulds         47
1    Pump         81
2    http         15

I used a generator expression in place of the count_of_occ list, but you can also do the following:

count_of_occ = [0 for i in keywords]
for i in range(len(count_of_occ)):
    if keywords[i] in output_content:
        count_of_occ[i] += output_content.count(keywords[i])
df['Occurence'] = pd.Series(count_of_occ, index=df.index)