我想查找拆分列是否包含类列表中的任何内容。如果是，我想使用类列表中的值更新类别列。想要的类别是我的最佳目标。
domain split Category Desired Category
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Class=['NaN','XYT','ssa','abk','abc','def','asds','ssb','bbc','XY','ab']
for index, row in df.iterrows():
for x in class:
intersection=row.split.contains(x)
if intersection:
df.loc[index,'class'] = intersection
就是做不到
请帮忙， 谢谢
最佳答案
使用str.extract。创建一个将匹配列表中的单词之一的正则表达式，并提取将匹配的单词(如果没有，则提取 NaN)。
更新:作为“|”运算符永远不会贪婪，即使它会产生更长的整体匹配，您必须手动对列表进行反向排序。
lst = ['NaN','XY','ab','XYT','ssa','abk','abc','def','asds','ssb','bbc']
lst = sorted(lst, reverse=True)
pat = fr"({'|'.join(lst)})"
df['Category'] = df['split'].str.extract(pat)
>>> df
domain split Category
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>>> lst
['ssb', 'ssa', 'def', 'bbc', 'asds', 'abk', 'abc', 'ab', 'XYT', 'XY', 'NaN']
>>> pat
'(ssb|ssa|def|bbc|asds|abk|abc|ab|XYT|XY|NaN)'
关于python - 如何用另一列中包含的值填充 NaN 值？，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/68854237/