pandas dataframe str.contains（）和操作

Question

df（Pandas Dataframe）有三行。

some_col_name
"apple is delicious"
"banana is delicious"
"apple and banana both are delicious"

df.col_name.str.contains("apple|banana")

将捕获所有行：

"apple is delicious",
"banana is delicious",
"apple and banana both are delicious".

如何在str.contains方法上应用AND运算符，以便它只获取同时包含apple&banana的字符串？

"apple and banana both are delicious"

我想抓住包含10-20个不同单词的字符串（葡萄、西瓜、浆果、橘子等等）

Answer 1

也可以使用regex表达式样式执行此操作：

df[df['col_name'].str.contains(r'^(?=.*apple)(?=.*banana)')]

然后，您可以将单词列表构建为一个regex字符串，如下所示：

base = r'^{}'
expr = '(?=.*{})'
words = ['apple', 'banana', 'cat']  # example
base.format(''.join(expr.format(w) for w in words))

将呈现：

'^(?=.*apple)(?=.*banana)(?=.*cat)'

然后你可以动态地做你的事情。

Answer 2

你可以这样做：

df[(df['col_name'].str.contains('apple')) & (df['col_name'].str.contains('banana'))]

Answer 3

df = pd.DataFrame({'col': ["apple is delicious",
                           "banana is delicious",
                           "apple and banana both are delicious"]})

targets = ['apple', 'banana']

# Any word from `targets` are present in sentence.
>>> df.col.apply(lambda sentence: any(word in sentence for word in targets))
0    True
1    True
2    True
Name: col, dtype: bool

# All words from `targets` are present in sentence.
>>> df.col.apply(lambda sentence: all(word in sentence for word in targets))
0    False
1    False
2     True
Name: col, dtype: bool