parsing a dictionary in a pandas dataframe cell into new row cells (new columns)

Question

I have a Pandas Dataframe that contains one column containing cells containing a dictionary of key:value pairs, like this:

{\"name\":\"Test Thorton\",\"compa         


        

Answer 1

I think you can use concat:

df = pd.DataFrame({1:['a','h'],2:['b','h'], 5:[{6:'y', 7:'v'},{6:'u', 7:'t'}] })

print (df)
   1  2                 5
0  a  b  {6: 'y', 7: 'v'}
1  h  h  {6: 'u', 7: 't'}

print (df.loc[:,5].values.tolist())
[{6: 'y', 7: 'v'}, {6: 'u', 7: 't'}]

df1 = pd.DataFrame(df.loc[:,5].values.tolist())
print (df1)
   6  7
0  y  v
1  u  t

print (pd.concat([df, df1], axis=1))
   1  2                 5  6  7
0  a  b  {6: 'y', 7: 'v'}  y  v
1  h  h  {6: 'u', 7: 't'}  u  t

Timings (len(df)=2k):

In [2]: %timeit (pd.concat([df, pd.DataFrame(df.loc[:,5].values.tolist())], axis=1))
100 loops, best of 3: 2.99 ms per loop

In [3]: %timeit (pir(df))
1 loop, best of 3: 625 ms per loop

df = pd.concat([df]*1000).reset_index(drop=True)

print (pd.concat([df, pd.DataFrame(df.loc[:,5].values.tolist())], axis=1))


def pir(df):
    df[['F', 'G']] = df[5].apply(pd.Series)
    df.drop(5, axis=1)
    return df

print (pir(df))