使用 pd.read_html 解析 html 表，其中单元格本身包含完整表

我需要从 html 解析一个表，该表在较大的表中嵌套有其他表。如下所示pd.read_html，每个嵌套表都会被解析，然后作为行“插入”/“连接”。

我希望将这些嵌套表分别解析为自己的表pd.DataFrames并将插入的对象作为相应列的值。

如果这是not可能的话，将嵌套表的原始 html 作为字符串放在相应的位置就可以了。

测试代码：

import pandas as pd
df_up = pd.read_html("up_pf00344.test.html", attrs = {'id': 'results'})

Screenshot of output:

Screenshot of table as rendered in html:

文件链接：https://gist.github.com/smsaladi/6adb30efbe70f9fed0306b226e8ad0d8#file-up_pf00344-test-html-L62 https://gist.github.com/smsaladi/6adb30efbe70f9fed0306b226e8ad0d8#file-up_pf00344-test-html-L62

你不能使用read_html https://pandas.pydata.org/pandas-docs/version/0.23.4/generated/pandas.read_html.html读取嵌套表，但您可以使用自己的 html 阅读器并使用read_html对于表格单元格：

import pandas as pd
import bs4

with open('up_pf00344.test.html') as f:
    html = f.read()
soup = bs4.BeautifulSoup(html, 'lxml')
results = soup.find(attrs = {'id': 'results'})

# get first visible header row as dataframe headers
for row in results.thead.find_all('tr'):
    if 'display:none' not in row.get('style',''):
        df = pd.DataFrame(columns=[col.get_text() for col in row.find_all('th')])
    break

# append all table rows to dataframe
for row in results.tbody.find_all('tr', recursive=False):
    if 'display:none' in row.get('style',''):
        continue
    df_row = []
    for col in row.find_all('td', recursive=False):
        table = col.find_all('table')
        df_row.append(pd.read_html(str(col))[0] if table else col.get_text())
    df.loc[len(df)] = df_row

的结果df.iloc[0].map(type):

                                                            <class 'str'>
Entry                                                       <class 'str'>
Organism                                                    <class 'str'>
Protein names                                               <class 'str'>
Gene names                                                  <class 'str'>
Length                                                      <class 'str'>
Cross-reference (Pfam)                                      <class 'str'>
Cross-reference (InterPro)                                  <class 'str'>
Taxonomic lineage IDs                                       <class 'str'>
Subcellular location [CC]                                   <class 'str'>
Signal peptide                                              <class 'str'>
Transit peptide                                             <class 'str'>
Topological domain                  <class 'pandas.core.frame.DataFrame'>
Transmembrane                       <class 'pandas.core.frame.DataFrame'>
Intramembrane                       <class 'pandas.core.frame.DataFrame'>
Sequence caution                                            <class 'str'>
Caution                                                     <class 'str'>
Taxonomic lineage (SUPERKINGDOM)                            <class 'str'>
Taxonomic lineage (KINGDOM)                                 <class 'str'>
Taxonomic lineage (PHYLUM)                                  <class 'str'>
Cross-reference (RefSeq)                                    <class 'str'>
Cross-reference (EMBL)                                      <class 'str'>
e                                                           <class 'str'>

奖励：因为您的表行有一个id，您可以使用它作为数据框的索引df.loc[row.get('id')] = df_row代替df.loc[len(df)] = df_row.