[英]Convert dictionaries in pandas dataframe to list
I have a dataframe我有一个 dataframe
fruit1 fruit2
[banana,apple,orange] [apple,nuts,strawberry]
[apple,mango,grape] [apple,mango,grape,guava]
My code for adding the two additional columns is我添加另外两个列的代码是
df["fruits_added"] = df.apply(lambda row: set(row.fruit2) - set(row.fruit1), axis=1)
df["fruits_deleted"] = df.apply(lambda row: set(row.fruit1) - set(row.fruit2), axis=1)
My desired output is我想要的 output 是
fruit1 fruit2 fruits_added fruits_deleted
[banana,apple,orange] [apple,nuts,strawberry] [strawberry,nuts] [banana,orange]
[apple,mango,grape] [apple,mango,grape,guava] [guava] []
but I am getting dictionaries instead但我得到的是字典
fruit1 fruit2 fruits_added fruits_deleted
[banana,apple,orange] [apple,nuts,strawberry] {strawberry,nuts} {banana,orange}
[apple,mango,grape] [apple,mango,grape,guava] {guava} {}
Any input is appreciated任何输入表示赞赏
You can use np.setdiff1d
您可以使用
np.setdiff1d
df['fruits_deleted'] = df.apply(lambda x: np.setdiff1d(x.fruit1, x.fruit2), axis=1)
df['fruits_added'] = df.apply(lambda x: np.setdiff1d(x.fruit2, x.fruit1), axis=1)
Convert sets to lists:将集合转换为列表:
df["fruits_added"] = df.apply(lambda row: list(set(row.fruit2) - set(row.fruit1)), axis=1)
df["fruits_deleted"] = df.apply(lambda row: list(set(row.fruit1) - set(row.fruit2)), axis=1)
Alternative solution:替代解决方案:
zipped = zip(df['fruit1'], df['fruit2'])
df["fruits_added"] = [list(set(y) - set(x)) for x, y in zipped]
df["fruits_deleted"] = [list(set(x) - set(y)) for x, y in zipped]
声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.