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在Python中将表格写入CSV文件

pythoncsv
4

我写了这段代码：

import urllib.request
import re
import csv

from bs4 import BeautifulSoup
stocklist = ['aapl','goog','fb','amzn','COP']
for stocklist in stocklist:
 optionsUrl = urllib.request.urlopen('http://finance.yahoo.com/q?s='+stocklist).read()
 soup = BeautifulSoup(optionsUrl)
 optionsTable = [
  [x.text for x in y.parent.contents]
   for y in soup.findAll('td', attrs={'class': 'yfnc_tabledata1','rtq_table': ''})
 ]
 print(optionsTable)
 length = len(optionsTable[0])
 with open('test.csv', 'w', newline='') as fp:
  a = csv.writer(fp, delimiter=',')
  for y in range(length):
   a.writerow([x[y] for x in optionsTable])

我正在尝试将输出写入CSV文件，但我只能写入“COP”股票的股票信息，而不能写入其他4只股票的信息。虽然打印输出了正确数量的行。
另外，如何只获取一次标题和5次数据？
此外，在写入CSV时如何添加名为“Symbol”的新列？
类似于这样：
Symbol [['Prev Close:'], ['Open:',], ['Bid:'], ['Ask:'], ['1y Target Est:', ],
 ['Beta:'], ['Earnings Date:'], ["Day's Range:"], ['52wk Range:'], ['Volume:',
 ], ['Avg Vol (3m):'], ['Market Cap:'], ['P/E (ttm):'], ['EPS (ttm):'], ['Div &
 Yield:'], ['Forward P/E (1 yr):'], ['P/S (ttm):], ['Ex-Dividend Date:'],
 ['Annual EPS Est\n                      (Sep-16)\n                    :'],
 ['Quarterly EPS Est\n                      (Jun-16)\n                    :'],
 ['Mean Recommendation*:'], ['PEG Ratio (5 yr expected):]]

这是输出结果：
[['Prev Close:', '98.94'], ['Open:', '98.50'], ['Bid:', '99.74 x 1500'], ['Ask:', '99.75 x 1400'], ['1y Target Est:', '124.90'], ['Beta:', '1.48679'], ['Earnings Date:', 'Jul 19 - Jul 25 (Est.)'], ["Day's Range:", '98.47 - 99.99'], ['52wk Range:', '89.47 - 132.97'], ['Volume:', '23,937,011'], ['Avg Vol (3m):', '38,273,600'], ['Market Cap:', '546.10B'], ['P/E (ttm):', '11.10'], ['EPS (ttm):', '8.98'], ['Div & Yield:', '2.28 (2.31%) '], ['Forward P/E (1 yr):', '10.95'], ['P/S (ttm):', '2.38'], ['Ex-Dividend Date:', '05-May-16'], ['Annual EPS Est\n                      (Sep-16)\n                    :', '8.28'], ['Quarterly EPS Est\n                      (Jun-16)\n                    :', '1.39'], ['Mean Recommendation*:', '1.8'], ['PEG Ratio (5 yr expected):', '1.29']]
[['Prev Close:', '728.28'], ['Open:', '723.71'], ['Bid:', '728.40 x 1300'], ['Ask:', '728.67 x 100'], ['1y Target Est:', '924.83'], ['Beta:', '1.032'], ['Next Earnings Date:', 'N/A'], ["Day's Range:", '722.34 - 729.54'], ['52wk Range:', '515.18 - 789.87'], ['Volume:', '837,958'], ['Avg Vol (3m):', '1,787,830'], ['Market Cap:', '500.30B'], ['P/E (ttm):', '29.65'], ['EPS (ttm):', '24.58'], ['Div & Yield:', 'N/A (N/A) '], ['Forward P/E (1 yr):', '18.37'], ['P/S (ttm):', '6.41'], ['Ex-Dividend Date:', 'N/A'], ['Annual EPS Est\n                      (Dec-16)\n                    :', '33.60'], ['Quarterly EPS Est\n                      (Jun-16)\n                    :', '8.06'], ['Mean Recommendation*:', '1.8'], ['PEG Ratio (5 yr expected):', '1.31']]
[['Prev Close:', '118.39'], ['Open:', '118.13'], ['Bid:', '118.60 x 300'], ['Ask:', '118.61 x 1900'], ['1y Target Est:', '142.87'], ['Beta:', '0.840485'], ['Earnings Date:', 'Jul 27 - Aug 1 (Est.)'], ["Day's Range:", '117.71 - 118.68'], ['52wk Range:', '72.00 - 121.08'], ['Volume:', '12,644,305'], ['Avg Vol (3m):', '25,848,800'], ['Market Cap:', '339.02B'], ['P/E (ttm):', '72.49'], ['EPS (ttm):', '1.64'], ['Div & Yield:', 'N/A (N/A) '], ['Forward P/E (1 yr):', '25.90'], ['P/S (ttm):', '17.13'], ['Ex-Dividend Date:', 'N/A'], ['Annual EPS Est\n                      (Dec-16)\n                    :', '3.56'], ['Quarterly EPS Est\n                      (Jun-16)\n                    :', '0.81'], ['Mean Recommendation*:', '1.7'], ['PEG Ratio (5 yr expected):', '0.96']]
[['Prev Close:', '726.64'], ['Open:', '723.10'], ['Bid:', '727.45 x 100'], ['Ask:', '727.59 x 100'], ['1y Target Est:', '800.92'], ['Beta:', '1.6465'], ['Earnings Date:', 'Jul 21 - Jul 25 (Est.)'], ["Day's Range:", '722.30 - 728.91'], ['52wk Range:', '422.64 - 731.50'], ['Volume:', '1,970,078'], ['Avg Vol (3m):', '3,982,600'], ['Market Cap:', '343.40B'], ['P/E (ttm):', '300.00'], ['EPS (ttm):', '2.43'], ['Div & Yield:', 'N/A (N/A) '], ['Forward P/E (1 yr):', '73.41'], ['P/S (ttm):', '3.02'], ['Ex-Dividend Date:', 'N/A'], ['Annual EPS Est\n                      (Dec-16)\n                    :', '5.38'], ['Quarterly EPS Est\n                      (Jun-16)\n                    :', '1.10'], ['Mean Recommendation*:', '1.8'], ['PEG Ratio (5 yr expected):', '2.43']]
[['Prev Close:', '47.49'], ['Open:', '46.72'], ['Bid:', '46.69 x 2900'], ['Ask:', '46.70 x 2700'], ['1y Target Est:', '51.23'], ['Beta:', '1.42252'], ['Earnings Date:', 'Jul 28 - Aug 1 (Est.)'], ["Day's Range:", '46.55 - 47.14'], ['52wk Range:', '31.05 - 64.24'], ['Volume:', '4,646,126'], ['Avg Vol (3m):', '9,070,990'], ['Market Cap:', '57.76B'], ['P/E (ttm):', 'N/A'], ['EPS (ttm):', '-4.98'], ['Div & Yield:', '1.98 (4.35%) '], ['Forward P/E (1 yr):', '150.64'], ['P/S (ttm):', '2.15'], ['Ex-Dividend Date:', '18-May-16'], ['Annual EPS Est\n                      (Dec-16)\n                    :', '-2.26'], ['Quarterly EPS Est\n                      (Jun-16)\n                    :', '-0.67'], ['Mean Recommendation*:', '2.5'], ['PEG Ratio (5 yr expected):', '0.38']]
尝试使用csv.DictWriter：https://docs.python.org/2/library/csv.html#csv.DictWriter - Brian Cain
3
我可以建议您使用pandas库。我看到您正在处理股票市场数据，我也做了一个小项目。除了csv写入之外，pandas还将帮助您进行进一步的数据分析。如果您特别是在使用雅虎财经，那么还有一个可用的模块。 - Eular
我正在使用如下示例。 - showri
2023年，这个方法已经不再有效（即使将URL调整为'https://finance.yahoo.com/quote/'+stocklist+'?ltr=1'，因为该网站现在使用大量的JavaScript来实时生成页面）。 - undefined
1个回答
0

首先，您需要收集列标题。您的标题有很多额外的空格，我们也不需要末尾的:。因此，我们进行一些格式化和清理。

header = [re.sub(' +',' ',i[0][:-1].replace('\n', ' ')) for i in optionsTable[0]]

with open('test.csv', 'w') as fp:
   writer = csv.writer(fp, delimiter=',')
   writer.writerow(header)
   for row in optionsTable:
      writer.writerow([i[1] for i in row])
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