Extract values from column of dictionaries using pandas

If there are no NaNs, use json_normalize.

pd.io.json.json_normalize(df.name.tolist())['Name']

0    Kevin
1    Scott
Name: Name, dtype: object

If there are NaNs, you will need to drop them first. However, it is easy to retain the indices.

df

   emp_id                                               name
0   101.0  {'Name': 'Kevin', 'attributes': {'type': 'Cont...
1   102.0                                                NaN
2   103.0  {'Name': 'Scott', 'attributes': {'type': 'Cont...

idx = df.index[df.name.notna()]
names = pd.io.json.json_normalize(df.name.dropna().tolist())['Name']  
names.index = idx

names

0    Kevin
2    Scott
Name: Name, dtype: object

Use apply, and use tolist to make it a list:

print(df['name'].apply(lambda x: x.get('Name')).tolist())

Output:

['Kevin', 'Scott']

If don't need list, want Series, use:

print(df['name'].apply(lambda x: x.get('Name')))

Output:

0    Kevin
1    Scott
Name: name, dtype: object

Update:

print(df['name'].apply(lambda x: x['attributes'].get('Name')).tolist())

Try following line:

names = [name.get('Name') for name in df['name']]