I've extracted the data from API response and created a dictionary function:
def data_from_api(a):
dictionary = dict(
data = a['number']
,created_by = a['opened_by']
,assigned_to = a['assigned']
,closed_by = a['closed']
)
return dictionary
and then to df (around 1k records):
raw_data = []
for k in data['resultsData']:
records = data_from_api(k)
raw_data.append(records)
I would like to create a function allows to extract the nested fields {display_value} in the columns in the dataframe. I need only the names like John Snow, etc. Please see below:
How to create a function extracts the display values for those fields? I've tried to create something like:
df = pd.DataFrame.from_records(raw_data)
def get_nested_fields(nested):
if isinstance(nested, dict):
return nested['display_value']
else:
return ''
df['created_by'] = df['opened_by'].apply(get_nested_fields)
df['assigned_to'] = df['assigned'].apply(get_nested_fields)
df['closed_by'] = df['closed'].apply(get_nested_fields)
but I'm getting an error:
KeyError: 'created_by'
Could you please help me?
CodePudding user response:
You can use .str
and get()
like below. If the key isn't there, it'll write None.
df = pd.DataFrame({'data':[1234, 5678, 5656], 'created_by':[{'display_value':'John Snow', 'link':'a.com'}, {'display_value':'John Dow'}, {'my_value':'Jane Doe'}]})
df['author'] = df['created_by'].str.get('display_value')
output
data created_by author
0 1234 {'display_value': 'John Snow', 'link': 'a.com'} John Snow
1 5678 {'display_value': 'John Dow'} John Dow
2 5656 {'my_value': 'Jane Doe'} None