Proper way to extract rows from a dataframe based on list values

Question

For a dataframe with label group of some integers, what is the best way to get the sub-dataframe based on a list of group labels?

map = [[9,13],[21,22]]

train

         group  feature1
id
0          24 -0.141691
1          22 -0.527684
2          13 -0.586026
3           9  0.233221
4          21 -0.545011

Currently I am using for loop which obviously is sub-optimal.

df = pd.DataFrame()
for i in map[0]:
  new_df = pd.concat([df,train[train.group==i]],axis=0)

new_df           

             group feature1
    id
    2          13 -0.586026
    3           9  0.233221

Answer 1

I think you're looking for pd.Series.isin ?

df[df['group'].isin(np.concatenate(map))]

    group  feature1
id                 
1      22 -0.527684
2      13 -0.586026
3       9  0.233221
4      21 -0.545011

If you want just the records associated with map[0] :

df[df['group'].isin(map[0])]

    group  feature1
id                 
2      13 -0.586026
3       9  0.233221