如何根据文本内容拆分Pandas DataFrame单列至多列？

问题场景 #

现有一个含单列的Pandas DataFrame，数据如下：

id    text_col
1     Was it Accurate?: Yes\n\nReasoning: This is a sample text
2     Was it Accurate?: Yes\n\nReasoning: This is a sample text
3     Was it Accurate?: No\n\nReasoning: This is a sample text

需要将text_col拆分为Was it Accurate?和Reasoning两列，最终目标格式：

id    Was it Accurate?    Reasoning
1     Yes             This is a sample text
2     Yes             This is a sample text
3     No              This is a sample text

尝试使用"\n\nReasoning:"拆分未得到预期结果，代码如下：

df[['Was it Accurate?','Reasoning']] = df['text_col'].str.split("\n\nReasoning:")

问题原因 #

当前拆分仅将文本从\n\nReasoning:处截断，但第一列仍保留了Was it Accurate?: 前缀，所以无法直接得到目标值。

解决方案 #

方法1：分步拆分+前缀清理 #

先拆分出两部分，再移除第一列的冗余前缀：

# 按Reasoning分隔符拆分，expand=True确保返回DataFrame
df[['Was it Accurate?', 'Reasoning']] = df['text_col'].str.split('\n\nReasoning:', expand=True)
# 替换掉第一列的固定前缀
df['Was it Accurate?'] = df['Was it Accurate?'].str.replace('Was it Accurate?: ', '')

方法2：正则表达式提取（推荐） #

直接用正则匹配提取目标内容，一步到位：

# 用正则分组提取两个字段的内容
df[['Was it Accurate?', 'Reasoning']] = df['text_col'].str.extract(r'Was it Accurate?: (.*?)\n\nReasoning: (.*)')

正则说明：

• (.*?)：非贪婪匹配Was it Accurate?: 后的内容（即Yes/No）
• (.*)：匹配\n\nReasoning: 后的所有文本内容

内容的提问来源于stack exchange，提问作者Shubham R