Я увидел ссылку, а затем, основываясь на последних HTML-тегах HTML, обновил код, как показано ниже, и он должен работать.Хотя имена столбцов изменились, вы можете изменить их соответствующим образом.
Вот обновленный код (Python 3):
from bs4 import BeautifulSoup
import urllib
import pandas as pd
pages = 18
rec_count = 0
rank = []
gname = []
platform = []
year = []
genre = []
publisher = []
sales_na = []
sales_eu = []
sales_jp = []
sales_ot = []
sales_gl = []
urlhead = 'http://www.vgchartz.com/gamedb/?page='
urltail = '&results=1000&name=&platform=&minSales=0.01&publisher=&genre=&sort=GL'
for page in range(1, pages):
surl = urlhead + str(page) + urltail
r = urllib.request.urlopen(surl).read()
soup = BeautifulSoup(r, features="lxml")
print(page)
chart = soup.find('div', id='generalBody').find('table')
for row in chart.find_all('tr')[3:]:
try:
col = row.find_all('td')
# extract data into column data
column_1 = col[0].string.strip()
column_2 = col[1].find('img')['alt'].strip()
column_3 = col[2].find('a').string.strip()
column_4 = col[3].find('img')['alt'].strip()
column_5 = col[4].string.strip()
column_6 = col[5].string.strip()
column_7 = col[6].string.strip()
column_8 = col[7].string.strip()
column_9 = col[8].string.strip()
column_10 = col[9].string.strip()
column_11 = col[10].string.strip()
# Add Data to columns
# Adding data only if able to read all of the columns
rank.append(column_1)
gname.append(column_2)
platform.append(column_3)
year.append(column_4)
genre.append(column_5)
publisher.append(column_6)
sales_na.append(column_7)
sales_eu.append(column_8)
sales_jp.append(column_9)
sales_ot.append(column_10)
sales_gl.append(column_11)
rec_count += 1
except:
print('Got Exception')
continue
columns = {'Rank': rank, 'Name': gname, 'Platform': platform, 'Year': year, 'Genre': genre, 'Publisher': publisher,
'NA_Sales': sales_na, 'EU_Sales': sales_eu, 'JP_Sales': sales_jp, 'Other_Sales': sales_ot,
'Global_Sales': sales_gl}
print (rec_count)
df = pd.DataFrame(columns)
print(df)
df = df[['Rank', 'Name', 'Platform', 'Year', 'Genre', 'Publisher', 'NA_Sales', 'EU_Sales', 'JP_Sales', 'Other_Sales',
'Global_Sales']]
del df.index.name
df.to_csv("vgsales.csv", sep=",", encoding='utf-8')