python - 使用字符串方法过滤列值上的行

Question

输入 df：

title                        desc
movie A                  It is a awesome movie with action
movie B                  Slow but intense movie.

我想过滤包含以下关键字的行：

keys =  ["awesome", "action"]

输出DF：

title                        desc
movie A                  It is a awesome movie with action

代码：

index_list = []
for index,rows in df.iterrows():
   if any(x in rows["desc"].split(" ") for x in keys) == True:
       index_list.append(index)

df = df.loc[index_list]

方法：

In each row, I am checking if any of the keywords are present after splitting the rows

这种方法效果很好，但我很想知道 pandas 中是否有任何一种衬垫可以达到同样的效果。

例子：

df.loc[df['column_name'].isin(some_values)]

Answer 1

为什么是的，有 - pandas.Series.str.contains

idx = df['column_name'].str.contains("|".join(keys), regex=True)
df[idx]

Answer 2

以下应该为您解决问题：

>>> import pandas as pd
>>> d = {'title':['movie A', 'movie B'], 'desc':['It is a awesome movie with action', 'Slow but intense movie.']}
>>> df = pd.DataFrame(data=d)
>>> df
                                desc    title
0  It is a awesome movie with action  movie A
1            Slow but intense movie.  movie B
>>> keys =  ["awesome", "action"]
>>> df[df['desc'].str.contains('|'.join(keys))]
                                desc    title
0  It is a awesome movie with action  movie A