使用其他列表过滤 pandas DataFrame 列列表

Question

Input DataFrame :

data = { "id" : ['[1,2]','[2,4]','[4,3]'],
             "name" : ['a','b','c'] }
df = pd.DataFrame(data)

filterstr = [1,2]

Expected Output:

id     name
[1,2]   a      
[2,4]   b

Tried Code : df1 = df[df.id.map(lambda x: np.isin(np.array(x), [[ str([i]) for i in filter]]).all())]

This works for single value in id column but not for two values like '[1,2]' Not sure where i am going wrong.

Answer 1

Taking exactly what you've given:

data = { "id" : ['[1,2]','[2,4]','[4,3]'],
             "name" : ['a','b','c'] }
df = pd.DataFrame(data)

filterstr = [1,2]

I do:

df['id'] = df['id'].apply(eval) # Convert from string to list.
output = df[df.id.map(lambda id: any(x for x in id if x in filterstr))]
print(output)

Output:

       id name
0  [1, 2]    a
1  [2, 4]    b

Answer 2

Creating DF:

data = { "id" : [[1,2],[2,4],[4,3]], #REMOVE STRING AROUND []!!!
         "name" : ['a','b','c'] }
df = pd.DataFrame(data)
df

Result:

index	id	name
0	1,2	a
1	2,4	b
2	4,3	c

Then let's create a variable which will be our "boolean" filter :

reg = [1,2]
filter = df.id.apply(lambda x: any(i for i in x if i in reg))

Intermediate result:

0     True
1     True
2    False
Name: id, dtype: bool

Then select only " True " values:

df = df[filter]
df

Final result:

index	id	name
0	1,2	a
1	2,4	b