how to get the value of a specific column of each row in a html table?

user_16375630 0
Viewed 103

I need to get the sensitivity (7th column) of each setting (row)

site: https://prosettings.net/cs-go-pro-settings-gear-list/

table id: "table_1"

2 rows class: "even", "odd"

sensitivity class: " numdata float column-sensitivity"

i made this, but it just prints None (i'm newbie to programming lol)

import requests
from bs4 import BeautifulSoup

site = "https://prosettings.net/cs-go-pro-settings-gear-list/"
r = requests.get(site)
soup = BeautifulSoup(r. text, "html.parser")
settings_table = soup.find("table", id="table_1")

for settings in settings_table.find_all("tbody"):
    rows = settings.find_all("tr")

    for row in rows:
        sens = row.find("td", class_=" numdata float  column sensitivity")
            print(sens)
web-scraping python-3.x html python
1 Answers

The data comes from a POST request.

Here's how to get the seventh row, which is, sensitivity:

import requests

api_url = "https://prosettings.net/wp-admin/admin-ajax.php?action=get_wdtable&table_id=55"

headers = {
    "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:100.0) Gecko/20100101 Firefox/100.0",
    "X-Requested-With": "XMLHttpRequest",
    "Content-Type": "application/x-www-form-urlencoded; charset=UTF-8",
    "Referer": "https://prosettings.net/cs-go-pro-settings-gear-list/",
}

payload = "draw=1&columns%5B0%5D%5Bdata%5D=0&columns%5B0%5D%5Bname%5D=rank&columns%5B0%5D%5Bsearchable%5D=true&columns%5B0%5D%5Borderable%5D=true&columns%5B0%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B0%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B1%5D%5Bdata%5D=1&columns%5B1%5D%5Bname%5D=team&columns%5B1%5D%5Bsearchable%5D=true&columns%5B1%5D%5Borderable%5D=true&columns%5B1%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B1%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B2%5D%5Bdata%5D=2&columns%5B2%5D%5Bname%5D=player&columns%5B2%5D%5Bsearchable%5D=true&columns%5B2%5D%5Borderable%5D=true&columns%5B2%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B2%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B3%5D%5Bdata%5D=3&columns%5B3%5D%5Bname%5D=role&columns%5B3%5D%5Bsearchable%5D=true&columns%5B3%5D%5Borderable%5D=true&columns%5B3%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B3%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B4%5D%5Bdata%5D=4&columns%5B4%5D%5Bname%5D=mouse&columns%5B4%5D%5Bsearchable%5D=true&columns%5B4%5D%5Borderable%5D=true&columns%5B4%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B4%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B5%5D%5Bdata%5D=5&columns%5B5%5D%5Bname%5D=hz&columns%5B5%5D%5Bsearchable%5D=true&columns%5B5%5D%5Borderable%5D=true&columns%5B5%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B5%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B6%5D%5Bdata%5D=6&columns%5B6%5D%5Bname%5D=dpi&columns%5B6%5D%5Bsearchable%5D=true&columns%5B6%5D%5Borderable%5D=true&columns%5B6%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B6%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B7%5D%5Bdata%5D=7&columns%5B7%5D%5Bname%5D=sensitivity&columns%5B7%5D%5Bsearchable%5D=true&columns%5B7%5D%5Borderable%5D=true&columns%5B7%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B7%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B8%5D%5Bdata%5D=8&columns%5B8%5D%5Bname%5D=edpi&columns%5B8%5D%5Bsearchable%5D=true&columns%5B8%5D%5Borderable%5D=true&columns%5B8%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B8%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B9%5D%5Bdata%5D=9&columns%5B9%5D%5Bname%5D=zoomsens&columns%5B9%5D%5Bsearchable%5D=true&columns%5B9%5D%5Borderable%5D=true&columns%5B9%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B9%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B10%5D%5Bdata%5D=10&columns%5B10%5D%5Bname%5D=mouseaccel&columns%5B10%5D%5Bsearchable%5D=true&columns%5B10%5D%5Borderable%5D=true&columns%5B10%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B10%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B11%5D%5Bdata%5D=11&columns%5B11%5D%5Bname%5D=windowssens&columns%5B11%5D%5Bsearchable%5D=true&columns%5B11%5D%5Borderable%5D=true&columns%5B11%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B11%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B12%5D%5Bdata%5D=12&columns%5B12%5D%5Bname%5D=rawinput&columns%5B12%5D%5Bsearchable%5D=true&columns%5B12%5D%5Borderable%5D=true&columns%5B12%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B12%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B13%5D%5Bdata%5D=13&columns%5B13%5D%5Bname%5D=monitor&columns%5B13%5D%5Bsearchable%5D=true&columns%5B13%5D%5Borderable%5D=true&columns%5B13%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B13%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B14%5D%5Bdata%5D=14&columns%5B14%5D%5Bname%5D=hz_1&columns%5B14%5D%5Bsearchable%5D=true&columns%5B14%5D%5Borderable%5D=true&columns%5B14%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B14%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B15%5D%5Bdata%5D=15&columns%5B15%5D%5Bname%5D=gpu&columns%5B15%5D%5Bsearchable%5D=true&columns%5B15%5D%5Borderable%5D=true&columns%5B15%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B15%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B16%5D%5Bdata%5D=16&columns%5B16%5D%5Bname%5D=resolution&columns%5B16%5D%5Bsearchable%5D=true&columns%5B16%5D%5Borderable%5D=true&columns%5B16%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B16%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B17%5D%5Bdata%5D=17&columns%5B17%5D%5Bname%5D=aspectratio&columns%5B17%5D%5Bsearchable%5D=true&columns%5B17%5D%5Borderable%5D=true&columns%5B17%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B17%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B18%5D%5Bdata%5D=18&columns%5B18%5D%5Bname%5D=scalingmode&columns%5B18%5D%5Bsearchable%5D=true&columns%5B18%5D%5Borderable%5D=true&columns%5B18%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B18%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B19%5D%5Bdata%5D=19&columns%5B19%5D%5Bname%5D=mousepad&columns%5B19%5D%5Bsearchable%5D=true&columns%5B19%5D%5Borderable%5D=true&columns%5B19%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B19%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B20%5D%5Bdata%5D=20&columns%5B20%5D%5Bname%5D=keyboard&columns%5B20%5D%5Bsearchable%5D=true&columns%5B20%5D%5Borderable%5D=true&columns%5B20%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B20%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B21%5D%5Bdata%5D=21&columns%5B21%5D%5Bname%5D=headset&columns%5B21%5D%5Bsearchable%5D=true&columns%5B21%5D%5Borderable%5D=true&columns%5B21%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B21%5D%5Bsearch%5D%5Bregex%5D=false&columns%5B22%5D%5Bdata%5D=22&columns%5B22%5D%5Bname%5D=cfgcrosshair&columns%5B22%5D%5Bsearchable%5D=true&columns%5B22%5D%5Borderable%5D=true&columns%5B22%5D%5Bsearch%5D%5Bvalue%5D=&columns%5B22%5D%5Bsearch%5D%5Bregex%5D=false&order%5B0%5D%5Bcolumn%5D=0&order%5B0%5D%5Bdir%5D=asc&start=0&length=-1&search%5Bvalue%5D=&search%5Bregex%5D=false&wdtNonce=415443b358"

data = requests.post(api_url, headers=headers, data=payload).json()["data"]
row_seven = [item[7] for item in data]
print("\n".join(row_seven))

Output:

1.45
2.20
3.09
0.90
1.42
1.70
1.60
1.65
1.40
1.90
1.77
1.50

and a lot more ...
user_61067910
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