如何使用 Python return 多行而不是只有一行？
How can I return multple rows instead of just one using Python?
我正在尝试从 finivz 中提取数据，但我始终只能提取一行。
这是我的代码：
url = ('https://finviz.com/quote.ashx?t=' + ticker.upper())
r = Request(url, headers = header)
html = urlopen(r).read()
soup = BeautifulSoup(html, 'lxml')
rows = soup.find_all('tr')
rows = rows[13:20]
for row in rows:
row_td = row.find_all('td') <------------ I believe the issue is with this section?
#print(row_td)
str_cells = str(row_td)
clean = BeautifulSoup(str_cells, "lxml").get_text()
print(clean)
只打印：
[股息 %，2.97%，速动比率，1.30，过去 5 年的销售额，-5.70%，毛利率，60.60%，52W 低，20.59%，ATR，0.64] - 即使我指定 rows[13:30]
我想打印出 table on the page. 中的所有行
here is a screenshot of the table
在 for 循环中，您一遍又一遍地重写变量 row_td。将变量的内容存储在列表中（在我的示例中，我使用列表 all_data 来存储所有行）。
要打印 table 中的所有行，您可以使用下一个示例：
import requests
from bs4 import BeautifulSoup
headers = {
"User-Agent": "Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:91.0) Gecko/20100101 Firefox/91.0"
}
url = "https://finviz.com/quote.ashx?t=KO"
soup = BeautifulSoup(requests.get(url, headers=headers).content, "lxml")
all_data = []
for tr in soup.select(".snapshot-table2 tr"):
tds = [td.get_text(strip=True) for td in tr.select("td")]
all_data.append(tds)
fmt_string = "{:<15}" * 12
for row in all_data:
print(fmt_string.format(*row))
打印：
Index DJIA S&P500 P/E 30.35 EPS (ttm) 1.87 Insider Own 0.30% Shs Outstand 4.31B Perf Week -1.03%
Market Cap 245.44B Forward P/E 23.26 EPS next Y 2.44 Insider Trans -2.65% Shs Float 4.29B Perf Month 0.30%
Income 8.08B PEG 3.00 EPS next Q 0.58 Inst Own 69.00% Short Float 0.75% Perf Quarter 3.70%
Sales 36.41B P/S 6.74 EPS this Y -13.30% Inst Trans 0.55% Short Ratio 2.34 Perf Half Y 11.87%
Book/sh 5.16 P/B 10.98 EPS next Y 7.84% ROA 8.90% Target Price 62.06 Perf Year 19.62%
Cash/sh 3.01 P/C 18.82 EPS next 5Y 10.12% ROE 40.10% 52W Range 46.97 - 57.56 Perf YTD 3.28%
Dividend 1.68 P/FCF 95.02 EPS past 5Y 1.40% ROI 12.20% 52W High -1.60% Beta 0.63
Dividend % 2.97% Quick Ratio 1.30 Sales past 5Y -5.70% Gross Margin 60.60% 52W Low 20.59% ATR 0.64
Employees 80300 Current Ratio 1.50 Sales Q/Q 41.70% Oper. Margin 25.70% RSI (14) 51.63 Volatility 1.17% 0.94%
Optionable Yes Debt/Eq 1.89 EPS Q/Q 47.70% Profit Margin 22.20% Rel Volume 0.76 Prev Close 56.86
Shortable Yes LT Debt/Eq 1.79 Earnings Jul 21 BMO Payout 87.90% Avg Volume 13.67M Price 56.64
Recom 2.20 SMA20 -0.42% SMA50 1.65% SMA200 6.56% Volume 10,340,772 Change -0.39%
您只需使用 pandas DataFrame 即可轻松完成。
这是完整的工作输出。
代码：
import requests
import pandas as pd
headers = {'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/92.0.4515.131 Safari/537.36'}
url = "https://finviz.com/quote.ashx?t=KO"
req = requests.get(url,headers=headers)
wiki_table = pd.read_html(req.text, attrs = {"class":"snapshot-table2"} )
df = wiki_table[0]
print(df)
输出：
0 1 2 3 ... 8 9 10 11
0 Index DJIA S&P500 P/E 30.35 ... Shs Outstand 4.31B Perf Week -1.03%
1 Market Cap 245.44B Forward P/E 23.26 ... Shs Float 4.29B Perf Month 0.30%
2 Income 8.08B PEG 3.00 ... Short Float 0.75% Perf Quarter 3.70%
3 Sales 36.41B P/S 6.74 ... Short Ratio 2.34 Perf Half Y 11.87%
4 Book/sh 5.16 P/B 10.98 ... Target Price 62.06 Perf Year 19.62%
5 Cash/sh 3.01 P/C 18.82 ... 52W Range 46.97 - 57.56 Perf YTD 3.28%
6 Dividend 1.68 P/FCF 95.02 ... 52W High -1.60% Beta 0.63
7 Dividend % 2.97% Quick Ratio 1.30 ... 52W Low 20.59% ATR 0.64
8 Employees 80300 Current Ratio 1.50 ... RSI (14) 51.63 Volatility 1.17% 0.94%
9 Optionable Yes Debt/Eq 1.89 ... Rel Volume 0.76 Prev Close 56.86
10 Shortable Yes LT Debt/Eq 1.79 ... Avg Volume 13.67M Price 56.64
11 Recom 2.20 SMA20 -0.42% ... Volume 10340772 Change -0.39%
[12 rows x 12 columns]
我正在尝试从 finivz 中提取数据，但我始终只能提取一行。 这是我的代码：
url = ('https://finviz.com/quote.ashx?t=' + ticker.upper())
r = Request(url, headers = header)
html = urlopen(r).read()
soup = BeautifulSoup(html, 'lxml')
rows = soup.find_all('tr')
rows = rows[13:20]
for row in rows:
row_td = row.find_all('td') <------------ I believe the issue is with this section?
#print(row_td)
str_cells = str(row_td)
clean = BeautifulSoup(str_cells, "lxml").get_text()
print(clean)
只打印：
[股息 %，2.97%，速动比率，1.30，过去 5 年的销售额，-5.70%，毛利率，60.60%，52W 低，20.59%，ATR，0.64] - 即使我指定 rows[13:30]
我想打印出 table on the page. 中的所有行 here is a screenshot of the table
在 for 循环中，您一遍又一遍地重写变量 row_td。将变量的内容存储在列表中（在我的示例中，我使用列表 all_data 来存储所有行）。
要打印 table 中的所有行，您可以使用下一个示例：
import requests
from bs4 import BeautifulSoup
headers = {
"User-Agent": "Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:91.0) Gecko/20100101 Firefox/91.0"
}
url = "https://finviz.com/quote.ashx?t=KO"
soup = BeautifulSoup(requests.get(url, headers=headers).content, "lxml")
all_data = []
for tr in soup.select(".snapshot-table2 tr"):
tds = [td.get_text(strip=True) for td in tr.select("td")]
all_data.append(tds)
fmt_string = "{:<15}" * 12
for row in all_data:
print(fmt_string.format(*row))
打印：
Index DJIA S&P500 P/E 30.35 EPS (ttm) 1.87 Insider Own 0.30% Shs Outstand 4.31B Perf Week -1.03%
Market Cap 245.44B Forward P/E 23.26 EPS next Y 2.44 Insider Trans -2.65% Shs Float 4.29B Perf Month 0.30%
Income 8.08B PEG 3.00 EPS next Q 0.58 Inst Own 69.00% Short Float 0.75% Perf Quarter 3.70%
Sales 36.41B P/S 6.74 EPS this Y -13.30% Inst Trans 0.55% Short Ratio 2.34 Perf Half Y 11.87%
Book/sh 5.16 P/B 10.98 EPS next Y 7.84% ROA 8.90% Target Price 62.06 Perf Year 19.62%
Cash/sh 3.01 P/C 18.82 EPS next 5Y 10.12% ROE 40.10% 52W Range 46.97 - 57.56 Perf YTD 3.28%
Dividend 1.68 P/FCF 95.02 EPS past 5Y 1.40% ROI 12.20% 52W High -1.60% Beta 0.63
Dividend % 2.97% Quick Ratio 1.30 Sales past 5Y -5.70% Gross Margin 60.60% 52W Low 20.59% ATR 0.64
Employees 80300 Current Ratio 1.50 Sales Q/Q 41.70% Oper. Margin 25.70% RSI (14) 51.63 Volatility 1.17% 0.94%
Optionable Yes Debt/Eq 1.89 EPS Q/Q 47.70% Profit Margin 22.20% Rel Volume 0.76 Prev Close 56.86
Shortable Yes LT Debt/Eq 1.79 Earnings Jul 21 BMO Payout 87.90% Avg Volume 13.67M Price 56.64
Recom 2.20 SMA20 -0.42% SMA50 1.65% SMA200 6.56% Volume 10,340,772 Change -0.39%
您只需使用 pandas DataFrame 即可轻松完成。
这是完整的工作输出。
代码：
import requests
import pandas as pd
headers = {'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/92.0.4515.131 Safari/537.36'}
url = "https://finviz.com/quote.ashx?t=KO"
req = requests.get(url,headers=headers)
wiki_table = pd.read_html(req.text, attrs = {"class":"snapshot-table2"} )
df = wiki_table[0]
print(df)
输出：
0 1 2 3 ... 8 9 10 11
0 Index DJIA S&P500 P/E 30.35 ... Shs Outstand 4.31B Perf Week -1.03%
1 Market Cap 245.44B Forward P/E 23.26 ... Shs Float 4.29B Perf Month 0.30%
2 Income 8.08B PEG 3.00 ... Short Float 0.75% Perf Quarter 3.70%
3 Sales 36.41B P/S 6.74 ... Short Ratio 2.34 Perf Half Y 11.87%
4 Book/sh 5.16 P/B 10.98 ... Target Price 62.06 Perf Year 19.62%
5 Cash/sh 3.01 P/C 18.82 ... 52W Range 46.97 - 57.56 Perf YTD 3.28%
6 Dividend 1.68 P/FCF 95.02 ... 52W High -1.60% Beta 0.63
7 Dividend % 2.97% Quick Ratio 1.30 ... 52W Low 20.59% ATR 0.64
8 Employees 80300 Current Ratio 1.50 ... RSI (14) 51.63 Volatility 1.17% 0.94%
9 Optionable Yes Debt/Eq 1.89 ... Rel Volume 0.76 Prev Close 56.86
10 Shortable Yes LT Debt/Eq 1.79 ... Avg Volume 13.67M Price 56.64
11 Recom 2.20 SMA20 -0.42% ... Volume 10340772 Change -0.39%
[12 rows x 12 columns]