Python Pandas：字符串包含和不包含
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Python Pandas: String Contains and Doesn't Contain
提问by Sam Perry
I'm trying to match rows of a Pandas DataFrame that contains and doesn't contain certain strings. For example:
我正在尝试匹配包含和不包含某些字符串的 Pandas DataFrame 的行。例如：
import pandas
df = pandas.Series(['ab1', 'ab2', 'b2', 'c3'])
df[df.str.contains("b")]
Output:
输出：
0 ab1
1 ab2
2 b2
dtype: object
Desired output:
期望的输出：
2 b2
dtype: object
Question: is there an elegant way of saying something like this?
问题：有没有一种优雅的表达方式？
df[[df.str.contains("b")==True] and [df.str.contains("a")==False]]
# Doesn't give desired outcome
回答by maxymoo
You're almost there, you just haven't got the syntax quite right, it should be:
你快到了，你只是没有完全正确的语法，它应该是：
df[(df.str.contains("b") == True) & (df.str.contains("a") == False)]
Another approach which might be cleaner if you have a lot of conditions to apply would to be to chain your filters together with reduce or a loop:
如果您有很多条件要应用，另一种可能更干净的方法是将过滤器与 reduce 或循环链接在一起：
from functools import reduce
filters = [("a", False), ("b", True)]
reduce(lambda df, f: df[df.str.contains(f[0]) == f[1]], filters, df)
#outputs b2
回答by behzad.nouri
Either:
任何一个：
>>> ts.str.contains('b') & ~ts.str.contains('a')
0 False
1 False
2 True
3 False
dtype: bool
or use regex:
或使用正则表达式：
>>> ts.str.contains('^[^a]*b[^a]*$')
0 False
1 False
2 True
3 False
dtype: bool
回答by lstodd
You can use .loc and ~ to index:
您可以使用 .loc 和 ~ 来索引：
df.loc[(df.str.contains("b")) & (~df.str.contains("a"))]
2 b2
dtype: object
