AttributeError：“NoneType”对象没有属性“文本”-BeautifulShop

Question

我有一些代码用于从 fbref 获取 scraping 信息（数据链接：https://fbref.com/en/comps/9/stats/Premier-League-Stats），它运行良好，但现在我在某些功能上遇到了一些问题（我检查了这些字段现在不起作用的是“player”、“nationality”、“position”、“squad”、“age”、“birth_year”）。我还检查了这些字段在网络中的名称是否与以前相同。有什么想法/帮助解决问题吗？

非常感谢！

import requests
from bs4 import BeautifulSoup
import pandas as pd
import numpy as np
import re
import sys, getopt
import csv

def get_tables(url):
    res = requests.get(url)
    ## The next two lines get around the issue with comments breaking the parsing.
    comm = re.compile("<!--|-->")
    soup = BeautifulSoup(comm.sub("",res.text),'lxml')
    all_tables = soup.findAll("tbody")
    team_table = all_tables[0]
    player_table = all_tables[1]
    return player_table, team_table

def get_frame(features, player_table):
    pre_df_player = dict()
    features_wanted_player = features
    rows_player = player_table.find_all('tr')
    for row in rows_player:
        if(row.find('th',{"scope":"row"}) != None):
    
            for f in features_wanted_player:
                cell = row.find("td",{"data-stat": f})
                a = cell.text.strip().encode()
                text=a.decode("utf-8")
                if(text == ''):
                    text = '0'
                if((f!='player')&(f!='nationality')&(f!='position')&(f!='squad')&(f!='age')&(f!='birth_year')):
                    text = float(text.replace(',',''))
                if f in pre_df_player:
                    pre_df_player[f].append(text)
                else:
                    pre_df_player[f] = [text]
    df_player = pd.DataFrame.from_dict(pre_df_player)
    return df_player

stats = ["player","nationality","position","squad","age","birth_year","games","games_starts","minutes","goals","assists","pens_made","pens_att","cards_yellow","cards_red","goals_per90","assists_per90","goals_assists_per90","goals_pens_per90","goals_assists_pens_per90","xg","npxg","xa","xg_per90","xa_per90","xg_xa_per90","npxg_per90","npxg_xa_per90"]

def frame_for_category(category,top,end,features):
    url = (top + category + end)
    player_table, team_table = get_tables(url)
    df_player = get_frame(features, player_table)
    return df_player

top='https://fbref.com/en/comps/9/'
end='/Premier-League-Stats'
df1 = frame_for_category('stats',top,end,stats)

df1

Answer 1

如果您只关注球员统计数据，请将player_table = all_tables[1] 更改为player_table = all_tables[2]，因为现在您将团队表输入到get_frame 函数中。

我试过了，之后效果很好。

Answer 2

我建议用熊猫的read_html 加载表格。在 Share & Export --> Embed this Table 下有一个指向此表的直接链接。

import pandas as pd
df = pd.read_html("https://widgets.sports-reference.com/wg.fcgi?css=1&site=fb&url=%2Fen%2Fcomps%2F9%2Fstats%2FPremier-League-Stats&div=div_stats_standard", header=1)

这会输出一个数据帧列表，该表可以通过df[0] 访问。输出df[0].head()：

	Rk	Player	Nation	Pos	Squad	Age	Born	MP	Starts	Min	90s	Gls	Ast	G-PK	PK	PKatt	CrdY	CrdR	Gls.1	Ast.1	G+A	G-PK.1	G+A-PK	xG	npxG	xA	npxG+xA	xG.1	xA.1	xG+xA	npxG.1	npxG+xA.1	Matches
0	1	Patrick van Aanholt	nl NED	DF	Crystal Palace	30-190	1990	16	15	1324	14.7	0	1	0	0	0	1	0	0	0.07	0.07	0	0.07	1.2	1.2	0.8	2	0.08	0.05	0.13	0.08	0.13	Matches
1	2	Tammy Abraham	eng ENG	FW	Chelsea	23-156	1997	20	12	1021	11.3	6	1	6	0	0	0	0	0.53	0.09	0.62	0.53	0.62	5.6	5.6	0.9	6.5	0.49	0.08	0.57	0.49	0.57	Matches
2	3	Che Adams	eng ENG	FW	Southampton	24-237	1996	26	22	1985	22.1	5	4	5	0	0	1	0	0.23	0.18	0.41	0.23	0.41	5.5	5.5	4.3	9.9	0.25	0.2	0.45	0.25	0.45	Matches
3	4	Tosin Adarabioyo	eng ENG	DF	Fulham	23-164	1997	23	23	2070	23	0	0	0	0	0	1	0	0	0	0	0	0	1	1	0.1	1.1	0.04	0.01	0.05	0.04	0.05	Matches
4	5	Adrián	es ESP	GK	Liverpool	34-063	1987	3	3	270	3	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	Matches