使用正则表达式将文本数据拆分为多列答案

【问题标题】：Splitting text data into multiple columns using Regex使用正则表达式将文本数据拆分为多列
【发布时间】：2019-09-19 03:12:44
【问题描述】：

我是正则表达式的新手，我想将一些文本数据拆分成列。查看“测试数据”，结构是：名字/姓氏、大学和国家。如何将此文本分成三列（每列包含姓名、大学和国家）？

test_data = "Bob Smith, São Paulo State University/Department of Production Engineering, Brazil James Smith, São Paulo State University/Department of Production Engineering, Brazil Bob James, São Paulo State University/Department of Production Engineering, Brazil"

test_df = pd.DataFrame([test_data], columns=["test_data"])
split_df = test_df["test_data"].str.split(r'\w+,', expand=True)
split_df.head()

提前致谢！

【问题讨论】：

你的测试数据不好。为什么？两个条目之间没有分隔符。
你是对的，但是逗号不能用来分隔数据吗？所有条目都遵循相同的名称、逗号、大学、逗号和国家格式。谢谢。
每个国家后面都少了一个逗号，所以如果你尝试用逗号分割，你最终会在同一个列表元素中得到国家和下一个名字

标签： python regex python-3.x pandas

【解决方案1】：

我不确定您是如何生成输入数据的，我也不确定数据在更大的集合中是否一致。这个答案是基于当前的数据集结构没有修改。您应该能够将最终输出添加到数据框。如果您对此有疑问，我也会添加该部分。

from pprint import pprint

input_string = 'Bob Smith, São Paulo State University/Department of Production Engineering, Brazil James Smith, São Paulo State University/Department of Production Engineering, Brazil Bob James, São Paulo State University/Department of Production Engineering, Brazil'

def split_string_keep_delimiter(string_to_split, delimiter):
  result_list = []
  tokens = string_to_split.split(delimiter)
  for i in range(len(tokens) - 1):
    result_list.append(tokens[i] + delimiter)
  result_list.append(tokens[len(tokens)-1])
  return  result_list

# This is going to split your input text on the word Brazil
# the output is a list
split_input = split_string_keep_delimiter(input_string, "Brazil")
pprint(split_input)
# output
['Bob Smith, São Paulo State University/Department of Production '
'Engineering,Brazil',
'James Smith, São Paulo State University/Department of Production '
'Engineering,Brazil',
'Bob James, São Paulo State University/Department of Production '
'Engineering,Brazil',
'']

# This is going to split the previous list at the commas (,).
# the output is a nested list
results = [item.split(',') for item in split_input if len(item) > 0]
print (results)
# output
[['Bob Smith', ' São Paulo State University/Department of Production Engineering', ' Brazil'], [' James Smith', ' São Paulo State University/Department of Production Engineering', ' Brazil'], [' Bob James', ' São Paulo State University/Department of Production Engineering', ' Brazil']]

# This loops through the results and extracts 4 items from each list.
for item in results:
  name = item[0].strip()
  university_name = item[1].strip().split('/')[0]
  department = item[1].strip().split('/')[1]
  country = item[2].strip()
  print (f'{name} - {university_name} - {department} - {country}')
  # output
  Bob Smith - São Paulo State University - Department of Production Engineering - Brazil
  James Smith - São Paulo State University - Department of Production Engineering - Brazil
  Bob James - São Paulo State University - Department of Production Engineering - Brazil

【讨论】：

谢谢 - 我能够使用它。我确实想出了一个似乎适用于我的大部分数据集的替代方案：split_df = test_df["test_data"].str.split(r'(.*?,.*?,\s\w+)', expand=True)

【解决方案2】：

如果您的数据结构更好，每列由“，”分隔，那么您可以执行以下操作。

在：

test_data = "São Paulo State University/Department of Production Engineering, Brazil, James Smith, São Paulo State University/Department of Production Engineering, Brazil, Bob James, São Paulo State University/Department of Production Engineering, Brazil, Mike Smith"

df = pd.DataFrame(data = np.array(test_data.split(',')).reshape(-1, 3), columns = ['University', 'Country', 'Name'])

输出：

|   |                            University                           | Country | Name        |
|---|:---------------------------------------------------------------:|---------|-------------|
| 0 | São Paulo State University/Department of Production Engineering | Brazil  | James Smith |
| 1 | São Paulo State University/Department of Production Engineering | Brazil  | Bob James   |
| 2 | São Paulo State University/Department of Production Engineering | Brazil  | Mike Smith  |

【讨论】：