python - Slice one Pandas DataFrame based on another -


i have created following pandas dataframe based on lists of ids. 

in [8]: df = pd.dataframe({'groups' : [1,2,3,4],                 'id'  : ["[1,3]","[2]","[5]","[4,6,7]"]}) out[9]:     groups     id 0       1    [1,3] 1       2      [2] 2       3      [5] 3       4  [4,6,7]

there dataframe following.

in [12]: df2 = pd.dataframe({'id' : [1,2,3,4,5,6,7],                 'path'  : ["p1,p2,p3,p4","p1,p2,p1","p1,p5,p5,p7","p1,p2,p3,p3","p1,p2","p1","p2,p3,p4"]})

i need path values each group. e.g

groups path 1      p1,p2,p3,p4        p1,p5,p5,p7 2      p1,p2,p1 3      p1,p2 4      p1,p2,p3,p3        p1        p2,p3,p4

i'm not sure quite best way it, worked me. incidentally works if create id variable in df 1 without "" marks, i.e. lists, not strings...

import itertools  df = pd.dataframe({'groups' : [1,2,3,4],                   'id'  : [[1,3],[2],[5],[4,6,7]]}) df2 = pd.dataframe({'id' : [1,2,3,4,5,6,7],                     'path'  : ["p1,p2,p3,p4","p1,p2,p1","p1,p5,p5,p7","p1,p2,p3,p3","p1,p2","p1","p2,p3,p4"]})  paths = [[] group in df.groups.unique()] x in df.index:     paths[x].extend(itertools.chain(*[list(df2[df2.id == int(y)]['path']) y in df.id[x]]))                                       df['paths'] = pd.series(paths) df

there neater way of doing this, odd data structure in way. gives following output 

    groups    id           paths 0    1      [1, 3]        [p1,p2,p3,p4, p1,p5,p5,p7] 1    2      [2]           [p1,p2,p1] 2    3      [5]           [p1,p2] 3    4      [4, 6, 7]     [p1,p2,p3,p3, p1, p2,p3,p4]

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