使用pandas从字典列中提取值

Question

I am trying to extract the name from the below dictionary:

df = df[[x.get('Name') for x in df['Contact']]]

Given below is how my Dataframe looks like:

data = [{'emp_id': 101,
  'name': {'Name': 'Kevin',
   'attributes': {'type': 'Contact',
    'url': '/services/data/v38.0/sobjects/Contact/00985300000bt4HEG4'}}},
 {'emp_id': 102,
  'name': {'Name': 'Scott',
   'attributes': {'type': 'Contact',
    'url': '/services/data/v38.0/sobjects/Contact/00985300000yr5UTR9'}}}]

df = pd.DataFrame(data)
df

   emp_id                                               name
0     101  {'Name': 'Kevin', 'attributes': {'type': 'Cont...
1     102  {'Name': 'Scott', 'attributes': {'type': 'Cont...

I get an error:

AttributeError: 'NoneType' object has no attribute 'get'

Answer 1

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

Answer 2

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())

Answer 3

请尝试以下行：

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