如何在Python中从同一个字符串中提取多个名称

Question

我正在努力抓取数据并解析字符串中的名称。例如，我正在使用类似于以下内容的字符串：

Dr. Sharif Amlani, UC Davis Health, Dr. Joe Biden, UC San Francisco, and Dr. Elton John, Public Health Director for Davis County

和

Dr. Winston Bishop from UC San Francisco and Usain Bolt from UC San Francisco 

是否有代码可以获取此类文本并将其转换为数据集？

这样，数据看起来像这样：

   Name           Affiliation

Sharif Amlani   UC Davis Health

Joe Biden       UC San Francisco

Elton John      Public Health Director for Davis County

Winston Bishop  UC San Francisco

Usain Bolt      UC San Francisco

谢谢

Answer 1

如果您的字符串始终采用 format name from place and name from place，您可以这样做：import pandas as pd# your consistently formatted strings = "Dr. Winston Bishop from UC San Francisco and Usain Bolt from UC San Francisco" l = list() # a list to keep track of data - I am sure there's a better way to do thisfor row in s.split('and'): # each row looks like "name from affiliation"    # l = [(name, affiliation), ...]    l.append(n.split((n.strip() for n in row.split('from')) # then create the DataFramedf = pd.DataFrame(data = l, columns = ['Name', 'Affiliation'])# you might want to strip the names and affiliations using pandas DataFrame using a lambda expression

Answer 2

您可以进行正则表达式匹配并创建 df. 此处显示一个字符串的示例方法：text = "Dr. Sharif Amlani, UC Davis Health, Dr. Joe Biden, UC San Francisco, and Dr. Elton John, Public Health Director for Davis County"text = text.replace(', and' ,',')re.findall("([\w\s]+),([\w\s]+)",text)df = pd.DataFrame(r)df.columns = ("Name", "Affiliation")print(df)输出：           Name                               Affiliation0   Sharif Amlani                           UC Davis Health1       Joe Biden                          UC San Francisco2      Elton John   Public Health Director for Davis County

Answer 3

在抓取过程中，一切都归结为模式匹配。如果字符串的格式不一致，可能会非常痛苦。不幸的是，就你而言，情况似乎就是这样。因此，我建议根据具体情况进行处理。我可以观察到这样一种模式，除了一个例外，所有名字都以“博士”开头。您可以使用它通过正则表达式提取名称。import retext = "Dr. Sharif Amlani, UC Davis Health, Dr. Joe Biden, UC San Francisco, and Dr. Elton John, Public Health Director for Davis County"regex = '((Dr.)( [A-Z]{1}[a-z]+)+)' # this will return three groups of matchesnames = [match[0] for match in re.findall(regex, text)] #simply extracting the first group of matches, which is the name您可以将其应用于其他字符串，但正如我上面提到的，限制是它只能捕获以“Dr.”开头的名称。您也可以对附属关系使用类似的策略。请注意，“，”分隔名称和从属关系，以便我们可以使用它。import retext = "Dr. Sharif Amlani, UC Davis Health, Dr. Joe Biden, UC San Francisco, and Dr. Elton John, Public Health Director for Davis County"affiliations = [term for term in text.split(',') if 'Dr.' not in term] # splitting the text by a comma and then excluding results that contain a 'Dr.'同样，您必须根据特定文本调整您的解决方案，但希望这可以帮助您思考问题。最后，您可以使用 pandas 将结果合并到数据框中：import pandas as pddata = pd.DataFrame(list(zip(names, affiliations)), columns = ['Name', 'Affiliation'])

Answer 4

以下是此示例文本的示例代码：text = "\Sharif Amlani   UC Davis Health\n\Joe Biden       UC San Francisco\n\Elton John      Public Health Director for Davis County\n\Winston Bishop  UC San Francisco\n\Usain Bolt      UC San Francisco"lines = text.split('\n')df = pd.concat([pd.DataFrame([[line[0:16].strip(),line[16:].strip()]]) for line in lines])