Convert a column containing a list of dictionaries to multiple columns in pandas dataframe

Question

I have a Pandas dataframe like :

pd.DataFrame({'a':[1,2], 'b':[[{'c':1,'d':5},{'c':3, 'd':7}],[{'c':10,'d':50}]]})
Out[2]: 
   a                                         b
0  1  [{u'c': 1, u'd': 5}, {u'c': 3, u'd': 7}]
1  2                    [{u'c': 10, u'd': 50}]

And I want to expand the 'b' column and repeat 'a' column if there are more than one element in 'b' as follow:

Out[2]: 
   a   c   d
0  1   1   5
1  1   3   7
2  2  10  50

I tried to use apply function on each row but I was not successful, apparently apply convert one row to one row.

Answer 1

You can use concat with list comprehension:

df = pd.concat([pd.DataFrame(x) for x in df['b']], keys=df['a'])
       .reset_index(level=1, drop=True).reset_index()

print (df)
   a   c   d
0  1   1   5
1  1   3   7
2  2  10  50

EDIT:

If index is unique, then is possible use join for all columns:

df1 = pd.concat([pd.DataFrame(x) for x in df['b']], keys=df.index)
        .reset_index(level=1,drop=True)
df = df.drop('b', axis=1).join(df1).reset_index(drop=True)
print (df)
   a   c   d
0  1   1   5
1  1   3   7
2  2  10  50

I try simplify solution:

l = df['b'].str.len()
df1 = pd.DataFrame(np.concatenate(df['b']).tolist(), index=np.repeat(df.index, l))
df = df.drop('b', axis=1).join(df1).reset_index(drop=True)
print (df)
   a   c   d
0  1   1   5
1  1   3   7
2  2  10  50