Unpack dictionary from Pandas Column

Solution 1:

Setup

df = pd.DataFrame(dict(
    codes=[
        {'amount': 12, 'code': 'a'},
        {'amount': 19, 'code': 'x'},
        {'amount': 37, 'code': 'm'},
        np.nan,
        np.nan,
        np.nan,
    ]
))

df

                         codes
0  {'amount': 12, 'code': 'a'}
1  {'amount': 19, 'code': 'x'}
2  {'amount': 37, 'code': 'm'}
3                          NaN
4                          NaN
5                          NaN

apply with pd.Series

Make sure to dropna first

df.codes.dropna().apply(pd.Series)

   amount code
0      12    a
1      19    x
2      37    m

df.drop('codes', 1).assign(**df.codes.dropna().apply(pd.Series))

   amount code
0    12.0    a
1    19.0    x
2    37.0    m
3     NaN  NaN
4     NaN  NaN
5     NaN  NaN

tolist and from_records

Same idea but skip the apply

pd.DataFrame.from_records(df.codes.dropna().tolist())

   amount code
0      12    a
1      19    x
2      37    m

df.drop('codes', 1).assign(**pd.DataFrame.from_records(df.codes.dropna().tolist()))

   amount code
0    12.0    a
1    19.0    x
2    37.0    m
3     NaN  NaN
4     NaN  NaN
5     NaN  NaN

Solution 2:

Setup

                        codes
0  {'amount': 12, 'code': 10}
1    {'amount': 3, 'code': 3}

apply with pd.Series

df.codes.apply(pd.Series)

   amount  code
0      12    10
1       3     3