我有数据框,其中包含例如:
"vendor a::ProductA"
"vendor b::ProductA"
"vendor a::Productb"
我需要删除所有内容(包括)这两个::以便我最终得到:
"vendor a"
"vendor b"
"vendor a"
我尝试了 str.trim(似乎不存在)和 str.split,但没有成功。 完成此任务的最简单方法是什么?
最佳答案
您可以像正常使用 split 一样使用 pandas.Series.str.split。只需拆分字符串 '::',并索引从 split 方法创建的列表:
>>> df = pd.DataFrame({'text': ["vendor a::ProductA", "vendor b::ProductA", "vendor a::Productb"]})
>>> df
text
0 vendor a::ProductA
1 vendor b::ProductA
2 vendor a::Productb
>>> df['text_new'] = df['text'].str.split('::').str[0]
>>> df
text text_new
0 vendor a::ProductA vendor a
1 vendor b::ProductA vendor b
2 vendor a::Productb vendor a
这是一个非 Pandas 解决方案:
>>> df['text_new1'] = [x.split('::')[0] for x in df['text']]
>>> df
text text_new text_new1
0 vendor a::ProductA vendor a vendor a
1 vendor b::ProductA vendor b vendor b
2 vendor a::Productb vendor a vendor a
编辑:这是对上面 pandas 中发生的事情的逐步解释:
# Select the pandas.Series object you want
>>> df['text']
0 vendor a::ProductA
1 vendor b::ProductA
2 vendor a::Productb
Name: text, dtype: object
# using pandas.Series.str allows us to implement "normal" string methods
# (like split) on a Series
>>> df['text'].str
<pandas.core.strings.StringMethods object at 0x110af4e48>
# Now we can use the split method to split on our '::' string. You'll see that
# a Series of lists is returned (just like what you'd see outside of pandas)
>>> df['text'].str.split('::')
0 [vendor a, ProductA]
1 [vendor b, ProductA]
2 [vendor a, Productb]
Name: text, dtype: object
# using the pandas.Series.str method, again, we will be able to index through
# the lists returned in the previous step
>>> df['text'].str.split('::').str
<pandas.core.strings.StringMethods object at 0x110b254a8>
# now we can grab the first item in each list above for our desired output
>>> df['text'].str.split('::').str[0]
0 vendor a
1 vendor b
2 vendor a
Name: text, dtype: object
我建议查看 pandas.Series.str docs ,或者,更好的是,Working with Text Data in pandas .
关于 python Pandas : remove everything after a delimiter in a string,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/40705480/