英文:
How do I split cells in Pandas dataframe that have combined data from HTML tables?
问题
Pandas如何将多个单元格合并为一个单元格？是网站或函数的问题吗？
import pandas as pdtables = pd.read_html('http://www.ufcstats.com/fight-details/451525a1abe30a91')
这里说有四个表格。但在这些表格中，实际数据已经合并在一起。例如，39 of 102 26 of 73 应该是两个单元格，但它是1个？
我尝试单独提取表格然后拆分它们：
df = tables[0].values.tolist()print(type(df[0][0]))print(re.split("\s{2,}", df[0][0]))
这没有任何效果。它只是原样返回单元格，没有任何变化。不确定出了什么问题，甚至没有错误。
是否有一种方法可以遍历整个数据框，在存在双空格的地方进行拆分，而不改变其结构？
英文:
Pandas combining multiple cells into one cell? Website or function problem?
import pandas as pdtables=pd.read_html('http://www.ufcstats.com/fight-details/451525a1abe30a91')
This says there are four tables. But in those tables, the actual data is being combined. For example 39 of 102 26 of 73 should be 2 cells. But its 1?
I tried to extract the tables individually and then split them
df=tables[0].values.tolist()print(type(df[0][0]))print(re.split("\s{2,}",df[0][0]))
This achieves nothing. It just bounces back the cell with no change. Unsure of what is wrong, not even an error.
Is there a way to iterate over the entire dataframe and split where there is double spaces present? without changing its structure.
答案1
得分: 2
我不确定pandas是否能解析每个<td>标签内部的嵌套数据/段落。
但无论如何，这是使用[标签：beautifulsoup]解析第一个表格的一种方法：
#pip install beautifulsoup4from bs4 import BeautifulSoupsoup = BeautifulSoup(requests.get(url).text, "html5lib")table = soup.find("table")headers = [col.text.strip() for col in table.find("thead").find_all("th")]data = [
for row in table.find_all("tr") for cell in row.find_all("td")
]
df = pd.DataFrame(data).T.set_axis(headers, axis=1)
输出：
| Fighter | KD | Sig. str. | Sig. str. % | Total str. | Td | Td % | Sub. att | Rev. | Ctrl ||:----------------|-----:|:------------|:--------------|:-------------|:-------|:-------|-----------:|-------:|:-------|| Jessica Andrade | 0 | 131 of 322 | 40% | 148 of 342 | 2 of 3 | 66% | 0 | 0 | 1:35 || Angela Hill | 1 | 89 of 209 | 42% | 99 of 220 | 0 of 0 | --- | 0 | 0 | 0:06 |
使用read_html，我们可以得到：
| Fighter | KD | Sig. str. | Sig. str. % | Total str. | Td | Td % | Sub. att | Rev. | Ctrl ||:----------------------------|:-----|:----------------------|:--------------|:----------------------|:---------------|:---------|:-----------|:-------|:-----------|| Jessica Andrade Angela Hill | 0 1 | 131 of 322 89 of 209 | 40% 42% | 148 of 342 99 of 220 | 2 of 3 0 of 0 | 66% --- | 0 0 | 0 0 | 1:35 0:06 |
英文:
I'm not sure if pandas can parse nested data/paragraphs inside each <td> tag.
But anyways, (as a good start) here is one way to parse the first table with [tag:beautifulsoup] :
#pip install beautifulsoup4from bs4 import BeautifulSoupsoup = BeautifulSoup(requests.get(url).text, "html5lib")table = soup.find("table")headers = [col.text.strip() for col in table.find("thead").find_all("th")]data = [
for row in table.find_all("tr") for cell in row.find_all("td")
]
df = pd.DataFrame(data).T.set_axis(headers, axis=1)
Ouptut :
| Fighter | KD | Sig. str. | Sig. str. % | Total str. | Td | Td % | Sub. att | Rev. | Ctrl |
|---|---|---|---|---|---|---|---|---|---|
| Jessica Andrade | 0 | 131 of 322 | 40% | 148 of 342 | 2 of 3 | 66% | 0 | 0 | 1:35 |
| Angela Hill | 1 | 89 of 209 | 42% | 99 of 220 | 0 of 0 | --- | 0 | 0 | 0:06 |
With read_html, we get :
| Fighter | KD | Sig. str. | Sig. str. % | Total str. | Td | Td % | Sub. att | Rev. | Ctrl |
|---|---|---|---|---|---|---|---|---|---|
| Jessica Andrade Angela Hill | 0 1 | 131 of 322 89 of 209 | 40% 42% | 148 of 342 99 of 220 | 2 of 3 0 of 0 | 66% --- | 0 0 | 0 0 | 1:35 0:06 |
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