使用 Pandas read_html 的问题
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时间：2020-09-14 02:42:37 来源:igfitidea点击:
Trouble using Pandas read_html
提问by theprowler
My goal is to extract data, specifically the data corresponding to the most recent date (in this case 5/20), from an HTML table 
我的目标是从 HTML 表中提取数据，特别是与最近日期（在本例中为 5/20）相对应的数据
Here is the corresponding HTML code:
下面是对应的 HTML 代码：
<html>
<head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8" />
<title>FW: NEFS 2 Available Quota 5/21</title>
<link rel="important stylesheet" href="">
<style>div.headerdisplayname {font-weight:bold;}</style></head>
<body>
<table border=0 cellspacing=0 cellpadding=0 width="100%" class="header-part1"><tr><td><b>Subject: </b>FW: NEFS 2 Available Quota 5/21</td></tr><tr><td><b>From: </b>Claire Fitz-Gerald <[email protected]></td></tr><tr><td><b>Date: </b>5/21/2014 10:08 AM</td></tr></table><br>
<html xmlns:v="urn:schemas-microsoft-com:vml" xmlns:o="urn:schemas-microsoft-com:office:office" xmlns:w="urn:schemas-microsoft-com:office:word" xmlns:m="http://schemas.microsoft.com/office/2004/12/omml" xmlns="http://www.w3.org/TR/REC-html40"><head><META HTTP-EQUIV="Content-Type" CONTENT="text/html; "><meta name=Generator content="Microsoft Word 12 (filtered medium)"><!--[if !mso]><style>v\:* {behavior:url(#default#VML);}
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</o:shapelayout></xml><![endif]--></head><body lang=EN-US link=blue vlink=purple><div class=WordSection1><p class=MsoNormal><span style='color:#1F497D'>Please see the below quota listings.<o:p></o:p></span></p><p class=MsoNormal><span style='color:#1F497D'><o:p> </o:p></span></p><p class=MsoNormal><span style='color:#1F497D'>Thanks,<o:p></o:p></span></p><p class=MsoNormal><span style='color:#1F497D'><o:p> </o:p></span></p><div><p class=MsoNormal><span style='font-size:12.0pt;font-family:"Franklin Gothic Book","sans-serif";color:#1F497D'>Claire Fitz-Gerald<o:p></o:p></span></p><p class=MsoNormal><i><span style='font-size:10.0pt;font-family:"Franklin Gothic Book","sans-serif";color:#1F497D'><o:p> </o:p></span></i></p><p class=MsoNormal><b><span style='font-family:"Franklin Gothic Demi","sans-serif";color:#002776'>Cape Cod Commercial Fishermen's Alliance<o:p></o:p></span></b></p><p class=MsoNormal><b><span style='font-family:"Franklin Gothic Book","sans-serif";color:#DE3500'>~ Small Boats. Big Ideas. ~</span></b><b><span style='color:#DE3500'><o:p></o:p></span></b></p></div><p class=MsoNormal><span style='color:#1F497D'><o:p> </o:p></span></p><div><div style='border:none;border-top:solid #B5C4DF 1.0pt;padding:3.0pt 0in 0in 0in'><p class=MsoNormal><b><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'>From:</span></b><span style='font-size:10.0pt;font-family:"Tahoma","sans-serif"'> David Leveille [mailto:[email protected]] <br><b>Sent:</b> Wednesday, May 21, 2014 8:50 AM<br><b>To:</b> David Leveille<br><b>Subject:</b> NEFS 2 Available Quota 5/21<o:p></o:p></span></p></div></div><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal><span style='font-size:12.0pt;font-family:"Arial","sans-serif";color:#1F487E'>AVAILABLE QUOTA FY 2014</span><span style='font-size:12.0pt;font-family:"Times New Roman","serif"'><o:p></o:p></span></p><table class=MsoNormalTable border=0 cellspacing=0 cellpadding=0 width="71%" style='width:71.28%'><tr><td width=220 style='width:164.95pt;border:none;border-bottom:solid windowtext 1.0pt;background:#8BCDFF;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><b><span style='font-size:9.0pt;font-family:"Arial","sans-serif";color:black'>ID <o:p></o:p></span></b></p></td><td width=161 style='width:120.75pt;border:none;border-bottom:solid windowtext 1.0pt;background:#8BCDFF;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='mso-line-height-alt:15.0pt'><b><span style='font-size:18.0pt;font-family:"Arial","sans-serif";color:black'>Available Quota <o:p></o:p></span></b></p></td><td width=189 style='width:141.75pt;border:none;border-bottom:solid windowtext 1.0pt;background:#8BCDFF;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='mso-line-height-alt:15.0pt'><b><span style='font-size:18.0pt;font-family:"Arial","sans-serif";color:black'>Live Weight Pounds <o:p></o:p></span></b></p></td><td width=126 style='width:94.55pt;border:none;border-bottom:solid windowtext 1.0pt;background:#8BCDFF;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='mso-line-height-alt:15.0pt'><b><span style='font-size:18.0pt;font-family:"Arial","sans-serif";color:black'>Price <o:p></o:p></span></b></p></td><td width=168 style='width:125.95pt;border:none;border-bottom:solid windowtext 1.0pt;background:#8BCDFF;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='mso-line-height-alt:15.0pt'><b><span style='font-size:18.0pt;font-family:"Arial","sans-serif";color:black'>Date Posted <o:p></o:p></span></b></p></td></tr><tr><td width=220 style='width:164.95pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>1724<o:p></o:p></span></p></td><td width=161 style='width:120.75pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>GOM COD<br>GOM HADD<br>GOM BB<br>GREYSOLE<br>DABS<br>GOM YT<o:p></o:p></span></p></td><td width=189 style='width:141.75pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>2328<br>445<br>3007<br>850<br>3101<br>1995<o:p></o:p></span></p></td><td width=126 style='width:94.55pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>Package<o:p></o:p></span></p><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'><o:p> </o:p></span></p><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>,000<o:p></o:p></span></p></td><td width=168 style='width:125.95pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>5/20<o:p></o:p></span></p></td></tr><tr><td width=220 style='width:164.95pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>1578<o:p></o:p></span></p></td><td width=161 style='width:120.75pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>GBE COD<br>GBW COD<br>GB BB<br>GB YT<br>SNE BB<br>SNE YT<br>GOM BB<br>Whake<br>POLL<br>RED<o:p></o:p></span></p></td><td width=189 style='width:141.75pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>538<br>5894<br>1755<br>243<br>490<br>153<br>3965<br>2727<br>9227<br>15060<o:p></o:p></span></p></td><td width=126 style='width:94.55pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>.00<br>from bs4 import BeautifulSoup
import pandas as pd
import lxml
import html5lib
path = 'Z:\blub'
df = pd.pandas.read_html(path)
print (df)
.40<br>from bs4 import BeautifulSoup
import pandas as pd
import lxml
import html5lib
path = 'file.html'
with open(path, 'rt') as myfile:
data = myfile.read().replace("<br>", '\n')
df = pd.read_html(data)
.20<br>.00<br>df[1]
.45<br>from bs4 import BeautifulSoup
path = 'file.html'
ecj_data = open(path,'r').read()
soup = BeautifulSoup(ecj_data)
tabulka = soup.find("table", {"class" : "MsoNormalTable"})
column_headers = ['ID','Available Quota', 'Live Weight Pounds', 'Price', 'Date Posted']
records = []
for idy, row in enumerate(tabulka.findAll('tr')):
if idy == 0:
continue
cols = row.findAll('td')
record = {}
for idx, col in enumerate(cols):
record[column_headers[idx]] = col.text.strip()
records.append(record)
df = pd.DataFrame.from_dict(records)
df[column_headers]
.50<br>path = r'Z:\blub'
if os.path.isfile(path):
df = pd.pandas.read_html(path)
print (df)
.15<br>##代码##.20<br>##代码##.01<br>##代码##.01<o:p></o:p></span></p></td><td width=168 style='width:125.95pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>5/20<o:p></o:p></span></p></td></tr><tr><td width=220 style='width:164.95pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>310<o:p></o:p></span></p></td><td width=161 style='width:120.75pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>GBE COD<br>GBW COD<br>DABS<br>WHAKE<br>POLL<br>RED<br>SNE BB<br>GOM BB<o:p></o:p></span></p></td><td width=189 style='width:141.75pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>825<br>9033<br>1241<br>3120<br>65234<br>76610<br>1688<br>1195<br>2121<br>7285<o:p></o:p></span></p></td><td width=126 style='width:94.55pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>Package<o:p></o:p></span></p><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'><o:p> </o:p></span></p><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>,000<o:p></o:p></span></p></td><td width=168 style='width:125.95pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>5/20<o:p></o:p></span></p></td></tr><tr style='height:23.25pt'><td width=220 style='width:164.95pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt;height:23.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>347<o:p></o:p></span></p></td><td width=161 style='width:120.75pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt;height:23.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>SNE BB<o:p></o:p></span></p></td><td width=189 style='width:141.75pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt;height:23.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>8,000<o:p></o:p></span></p></td><td width=126 style='width:94.55pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt;height:23.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>##代码##.50<o:p></o:p></span></p></td><td width=168 style='width:125.95pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt;height:23.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>5/7<o:p></o:p></span></p></td></tr><tr><td width=220 style='width:164.95pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>1878A<o:p></o:p></span></p></td><td width=161 style='width:120.75pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>GOM COD<br>GOM HADD<br>SNE BB<br>GOM BB<br>GB BB<br>GREYSOLE<br>GOM YT<br>SNE YT<br>POLL<o:p></o:p></span></p></td><td width=189 style='width:141.75pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>6188<br>635<br>3916<br>7873<br>6762<br>3358<br>9776<br>271<br>186550<o:p></o:p></span></p></td><td width=126 style='width:94.55pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>.95<br>.35<br>##代码##.50<br>##代码##.50<br>##代码##.20<br>.40<br>.20<br>##代码##.50<br>##代码##.01<o:p></o:p></span></p></td><td width=168 style='width:125.95pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>5/12<o:p></o:p></span></p></td></tr><tr><td width=220 style='width:164.95pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>1878B<o:p></o:p></span></p></td><td width=161 style='width:120.75pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>GBE COD<br>GBW COD<br>GB YT<o:p></o:p></span></p></td><td width=189 style='width:141.75pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>1113<br>12186<br>850<o:p></o:p></span></p></td><td width=126 style='width:94.55pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>Package<br>,000<o:p></o:p></span></p></td><td width=168 style='width:125.95pt;border:solid windowtext 1.0pt;background:white;padding:2.25pt 2.25pt 2.25pt 2.25pt'><p class=MsoNormal style='line-height:15.0pt'><span style='font-size:13.5pt;font-family:"Arial","sans-serif";color:black'>5/12<o:p></o:p></span></p></td></tr></table><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal>David Leveille<o:p></o:p></p><p class=MsoNormal>II Northeast Fishery Sector Inc.<o:p></o:p></p><p class=MsoNormal>10 Witham Street<o:p></o:p></p><p class=MsoNormal>Gloucester, MA. 01930<o:p></o:p></p><p class=MsoNormal>Cell 978 375 3509<o:p></o:p></p><p class=MsoNormal>Fax 978 281 1555<o:p></o:p></p><p class=MsoNormal>Web <a href="http://nefs2.com/">http://nefs2.com/</a><o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><div class=MsoNormal align=center style='text-align:center'><span style='font-size:12.0pt;font-family:"Times New Roman","serif"'></body></html>
</body>
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I tried using BeautifulSoup to access the data inside each cell. I would see 'if date 5/20 occurs below, capture all data corresponding to it'. That actually worked quite well but when I would go to put the data into a Pandas DataFrame it would fail. After many failed attempts I was told using Pandas read_html would be a wiser choice for this task.
我尝试使用 BeautifulSoup 访问每个单元格内的数据。我会看到“如果日期 5/20 出现在下方，则捕获与其对应的所有数据”。这实际上工作得很好，但是当我将数据放入 Pandas DataFrame 时，它会失败。在多次尝试失败后，我被告知使用 Pandas read_html 将是这项任务的更明智选择。
So far my code is:
到目前为止，我的代码是：
##代码##But when I run it the line df = pd.pandas.read_html(path)produces the error ValueError: No tables found.
但是当我运行它时，该行df = pd.pandas.read_html(path)会产生错误ValueError: No tables found。
Does that mean that the read_html command does not recognize the data table? Is using read_htmlthe wisest approach for parsing this data table neatly? I say neatly because the final step after parsing is to export it all to an Oracle Database.
这是否意味着 read_html 命令无法识别数据表？是否使用read_html最明智的方法来巧妙地解析此数据表？我这么说是因为解析后的最后一步是将其全部导出到 Oracle 数据库。
I would appreciate any and all advice solving this problem. Thanks.
我将不胜感激任何解决此问题的建议。谢谢。
采纳答案by Vikash Singh
First you can read the data from the file and then parse it using
首先，您可以从文件中读取数据，然后使用
##代码##This will give you a list of dataframes. At df[1] you will get the dataframe you want
这将为您提供数据框列表。在 df[1] 你会得到你想要的数据框
##代码##
As this is not a reliable way to parse data from an html I would advice you to go by parsing and creating your data frame using Beautiful Soup.
由于这不是从 html 解析数据的可靠方法，我建议您使用 Beautiful Soup 解析和创建数据框。
##代码##output will look like this:
输出将如下所示：
回答by Marjan Moderc
I think your error lies in the quotes of 'path' argument in read_html() method. Make sure you remove them, otherwise you are calling it with the string 'path' instead of the variable path, which contains your actual path.
我认为您的错误在于 read_html() 方法中“路径”参数的引号。确保删除它们，否则您将使用字符串“path”而不是包含实际路径的变量路径调用它。
##代码##