pandas dataframe str.contains()AND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,以便它只捕获包含苹果和香蕉的字符串？

"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,橙子,......等)

Answer 1

你可以这样做:

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

Answer 2

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

Answer 3

您也可以使用正则表达式样式：

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

然后，您可以将单词列表构建为正则表达式字符串，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，您可以动态地进行操作。

Answer 4

这有效

df.col.str.contains(r'(?=.*apple)(?=.*banana)',regex=True)

Answer 5

如果您只想使用本机方法并避免编写正则表达式，这里有一个不涉及 lambda 的矢量化版本：

targets = ['apple', 'banana', 'strawberry']
fruit_masks = (df['col'].str.contains(string) for string in targets)
combined_mask = np.vstack(fruit_masks).all(axis=0)
df[combined_mask]