我想使用 BeautifulSoup 分隔日期和价格，但它们都在同一个 td 标签下

Question

我想通过使用 BeautifulSoup 进行网络抓取，从 http://www.westmetall.com/en/markdaten.php?action=show_table&field=LME_Ni_cash#y2017 获取镍价数据。

有两个问题

1) 我想将价格与日期分开，将它们放在不同的列中
2）我想删除“。”在日期

到目前为止我的代码是：

import bs4 
import csv
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
from datetime import datetime

my_url='http://www.westmetall.com/en/markdaten.php?action=show_table&field=LME_Ni_cash#y2017'
uClient=uReq(my_url)
page_html=uClient.read()
uClient.close()
page_soup=soup(page_html, "html.parser")
containers=page_soup.findAll("table")
contain=containers[0]
print(contain.td.text)    #I only print this because I want to view the HTML

如果我这样做并应用循环，它将提取 td 下的所有元素，并将日期和价格放在 1 列中。我的目标是将它们分成两列。

HTML预览如下：

<tr class="even">
<td>15. Febuary 2018</td>
<td>14.150,00</td>
<td>14.200,00</td>
<td class="last">339.708</td></tr>
<tr class="odd">
<td>14. Febuary 2018</td>
<td>13.630,00</td>
<td>13.660,00</td>
<td class="last">338.652</td>
</tr>

非常感谢您的帮助！！！

Answer 1

这应该会有所帮助。

import requests
from bs4 import BeautifulSoup

t = """<table><tr><th>date</th><th class="last">LME Nickel Cash-Settlement</th><th class="last">LME Nickel 3-month</th><th class="last">LME Nickel stock</th></tr><tr class="even"><td>15. Febuary 2018</td><td>14.150,00</td><td>14.200,00</td><td class="last">339.708</td></tr><tr class="odd"><td>14. Febuary 2018</td><td>13.630,00</td><td>13.660,00</td><td class="last">338.652</td></tr><tr class="even"><td>13. Febuary 2018</td><td>13.215,00</td><td>13.255,00</td><td class="last">339.006</td></tr><tr class="odd"><td>12. Febuary 2018</td><td>12.965,00</td><td>13.005,00</td><td class="last">341.160</td></tr><tr class="even"><td>09. Febuary 2018</td><td>12.970,00</td><td>13.000,00</td><td class="last">342.204</td></tr><tr class="odd"><td>08. Febuary 2018</td><td>13.025,00</td><td>13.080,00</td><td class="last">343.896</td></tr><tr class="even"><td>07. Febuary 2018</td><td>13.490,00</td><td>13.500,00</td><td class="last">347.148</td></tr><tr class="odd"><td>06. Febuary 2018</td><td>13.370,00</td><td>13.380,00</td><td class="last">349.476</td></tr><tr class="even"><td>05. Febuary 2018</td><td>13.540,00</td><td>13.585,00</td><td class="last">350.652</td></tr><tr class="odd"><td>02. Febuary 2018</td><td>13.795,00</td><td>13.830,00</td><td class="last">353.592</td></tr><tr class="even"><td>01. Febuary 2018</td><td>13.545,00</td><td>13.555,00</td><td class="last">355.266</td></tr><tr class="shaded"><th>date</th><th class="last">LME Nickel Cash-Settlement</th><th class="last">LME Nickel 3-month</th><th class="last">LME Nickel stock</th></tr><tr class="odd"><td>31. January 2018</td><td>13.555,00</td><td>13.550,00</td><td class="last">357.012</td></tr><tr class="even"><td>30. January 2018</td><td>13.650,00</td><td>13.700,00</td><td class="last">359.292</td></tr><tr class="odd"><td>29. January 2018</td><td>13.890,00</td><td>13.890,00</td><td class="last">360.714</td></tr><tr class="even"><td>26. January 2018</td><td>13.750,00</td><td>13.770,00</td><td class="last">361.782</td></tr><tr class="odd"><td>25. January 2018</td><td>13.695,00</td><td>13.725,00</td><td class="last">362.058</td></tr><tr class="even"><td>24. January 2018</td><td>13.000,00</td><td>13.005,00</td><td class="last">362.196</td></tr><tr class="odd"><td>23. January 2018</td><td>12.750,00</td><td>12.820,00</td><td class="last">362.868</td></tr><tr class="even"><td>22. January 2018</td><td>12.720,00</td><td>12.755,00</td><td class="last">363.168</td></tr><tr class="odd"><td>19. January 2018</td><td>12.595,00</td><td>12.610,00</td><td class="last">361.500</td></tr><tr class="even"><td>18. January 2018</td><td>12.455,00</td><td>12.500,00</td><td class="last">362.532</td></tr><tr class="odd"><td>17. January 2018</td><td>12.415,00</td><td>12.470,00</td><td class="last">364.968</td></tr><tr class="even"><td>16. January 2018</td><td>12.415,00</td><td>12.490,00</td><td class="last">364.218</td></tr><tr class="odd"><td>15. January 2018</td><td>12.835,00</td><td>12.875,00</td><td class="last">364.248</td></tr><tr class="even"><td>12. January 2018</td><td>12.670,00</td><td>12.690,00</td><td class="last">365.994</td></tr><tr class="odd"><td>11. January 2018</td><td>12.835,00</td><td>12.890,00</td><td class="last">368.292</td></tr><tr class="even"><td>10. January 2018</td><td>12.900,00</td><td>12.950,00</td><td class="last">365.868</td></tr><tr class="odd"><td>09. January 2018</td><td>12.515,00</td><td>12.565,00</td><td class="last">367.056</td></tr><tr class="even"><td>08. January 2018</td><td>12.450,00</td><td>12.490,00</td><td class="last">368.430</td></tr><tr class="odd"><td>05. January 2018</td><td>12.500,00</td><td>12.505,00</td><td class="last">365.070</td></tr><tr class="even"><td>04. January 2018</td><td>12.615,00</td><td>12.680,00</td><td class="last">365.934</td></tr><tr class="odd"><td>03. January 2018</td><td>12.465,00</td><td>12.525,00</td><td class="last">366.072</td></tr><tr class="even"><td>02. January 2018</td><td>12.690,00</td><td>12.730,00</td><td class="last">366.612</td></tr></table>"""
soup = BeautifulSoup(t, "html.parser")
res = []
for tr in soup.findAll("table"):
    for td in tr.find_all("tr", class_=["even", "odd"]):
        print td.td.text.replace(".", ""), " = ", td.find('td', class_="last").text

输出：

15 Febuary 2018  =  339.708
14 Febuary 2018  =  338.652
13 Febuary 2018  =  339.006
12 Febuary 2018  =  341.160
09 Febuary 2018  =  342.204
08 Febuary 2018  =  343.896
07 Febuary 2018  =  347.148
06 Febuary 2018  =  349.476
05 Febuary 2018  =  350.652
02 Febuary 2018  =  353.592
01 Febuary 2018  =  355.266
31 January 2018  =  357.012
30 January 2018  =  359.292
29 January 2018  =  360.714
26 January 2018  =  361.782
25 January 2018  =  362.058
24 January 2018  =  362.196
23 January 2018  =  362.868
22 January 2018  =  363.168
19 January 2018  =  361.500
18 January 2018  =  362.532
17 January 2018  =  364.968
16 January 2018  =  364.218
15 January 2018  =  364.248
12 January 2018  =  365.994
11 January 2018  =  368.292
10 January 2018  =  365.868
09 January 2018  =  367.056
08 January 2018  =  368.430
05 January 2018  =  365.070
04 January 2018  =  365.934
03 January 2018  =  366.072
02 January 2018  =  366.612

Answer 2

综合您在上一篇文章中的建议，我已经使用以下代码成功地从该网站上抓取了镍价和库存的每日数据。感谢大家的帮助，不胜感激

import bs4
import csv
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup

my_url='http://www.westmetall.com/en/markdaten.php?
action=show_table&field=LME_Ni_cash#y2017'
uClient=uReq(my_url)
page_html=uClient.read()
uClient.close()
page_soup=soup(page_html, "html.parser")
containers=page_soup.findAll('tr', class_=["even", "odd"])
contain=containers[0]

for contain in containers:
    date = contain.td.text
    invs = contain.find("td", class_="last").text
    harga = contain.findAll('td')[1].text

 with open('nickel.csv','a') as csv_file:
    writer=csv.writer(csv_file)
    writer.writerow([date.replace(".",""),
    invs.replace(".",""),harga.replace(".","").replace(",",".")])