python Pandas : removing rows not matching multiple conditions from dataframe

Question

假设我有一个像这样使用 pandas.dataframe 的列:

index  fruits    origin      attribute
 1     apple     USA         tasty
 2     apple     France      yummy
 3     apple     USA         juicy
 4     apple     England     juicy
 5     apple     Japan       normal
 6     banana    Canada      nice
 7     banana    Italy       good
 .....

我想选择 yummy apple from France(2) 并从表中删除不匹配的 apples，如下所示:

index  fruits    origin      attribute
 1     apple     France      yummy
 2     banana    Canada      nice
 3     banana    Italy       good
 .....

我认为以下应该可行。但事实并非如此:

df.drop(df[(df.fruits == "apple") & (df.origin != "France") | (df.fruits == "apple") & (df.attribute != "yummy")].index)

然后我尝试了以下也不起作用:

df = df[~df[(df.fruits == "apple") & (df.origin != "France") & (df.attribute != "yummy")]

有什么帮助吗，小伙子们？

Answer 1

如果按条件选择:

df[(df.fruits != 'apple') | ((df.fruits == 'apple') & (df.origin == 'France') & (df.attribute == 'yummy'))]

#index  fruits  origin  attribute
#1  2    apple  France      yummy
#5  6   banana  Canada       nice
#6  7   banana   Italy       good

---

如果按不匹配条件移除:需要移除的是fruits为apple但origin不匹配France的行或者 attribute 与 yummy 不匹配:

df[~((df.fruits == 'apple') & ((df.origin != 'France') | (df.attribute != 'yummy')))]

# index fruits  origin  attribute
#1    2  apple  France      yummy
#5    6 banana  Canada       nice
#6    7 banana   Italy       good