numpy - create a feature vector using pandas or python -


i have binary classifier takes 200 element input feature vector shown below

   [ id, v1,   v2, ...,v190, v200, class]    [  7,   0,   0, ...,   0,    0,    0 ],    [  8,   0,   1, ...,   0,    0,    1 ],    [  9,   0,   0, ...,   0,    0,    1 ], 

for each element x may have set of attributes in v1-v200

   sql = 'select x_id, x_attr elements x_hash = %s'    cur.execute(sql, (x_hash,))    x1 = cur.fetchone()    x1 # x1 returns id , list of attributes     (123, [v2,v56,v200]) 

given output want create feature vector such 1 above, if attribute in list matches attribute in set v1- v200 set 1.

   [  id,   v1,  v2,...,v56,...,v190, v200,    class ],    [  123,   0,   1,...,1,...,   0,    1,    ?     ], 

how can in pandas or python?

first initializing pandas dataframe , building on example:

df = pd.dataframe(none, columns=['v'+str(i) in range(1,201)]) sql = 'select x_id, x_attr elements x_hash = %s' cur.execute(sql, (x_hash,)) x1_id, features = cur.fetchone() df.loc[x1_id] = 0  # initializes values id zero. df.loc[x1_id, features] = 1  # sets relevant features value of one. 

i haven't included class, wasn't sure how using it.


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