如何将 html 表转换为 Pandas 数据框
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/16009778/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
How to convert a html table into pandas dataframe
提问by waitingkuo
pandasprovides an useful to_html()to convert the DataFrameinto the html table. Is there any useful function to read it back to the DataFrame?
pandas提供了一个有用to_html()的转换DataFrame成html table. 是否有任何有用的功能可以将其读回DataFrame？
回答by elyase
In the general case it is not possible but if you approximately know the structure of your table you could something like this:
在一般情况下，这是不可能的，但如果您大致了解表的结构，您可以这样做：
# Create a test df:
>>> df = DataFrame(np.random.rand(4,5), columns = list('abcde'))
>>> df
a b c d e
0 0.675006 0.230464 0.386991 0.422778 0.657711
1 0.250519 0.184570 0.470301 0.811388 0.762004
2 0.363777 0.715686 0.272506 0.124069 0.045023
3 0.657702 0.783069 0.473232 0.592722 0.855030
Now parse the html and reconstruct:
现在解析 html 并重建：
from pyquery import PyQuery as pq
d = pq(df.to_html())
columns = d('thead tr').eq(0).text().split()
n_rows = len(d('tbody tr'))
values = np.array(d('tbody tr td').text().split(), dtype=float).reshape(n_rows, len(columns))
>>> DataFrame(values, columns=columns)
a b c d e
0 0.675006 0.230464 0.386991 0.422778 0.657711
1 0.250519 0.184570 0.470301 0.811388 0.762004
2 0.363777 0.715686 0.272506 0.124069 0.045023
3 0.657702 0.783069 0.473232 0.592722 0.855030
You could extend it for Multiindex dfs or automatic type detection using eval()if needed.
eval()如果需要，您可以将其扩展为 Multiindex dfs 或自动类型检测。
