Python - Looping through nested dictionaries and fetching values

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I have the same format of nested dictionaries within a list. I am trying to iterate through every element and find the number of time we have values for summary as through the API and also count the number of assignees for through the API.

[{'id': '101',
 'type': 'log_file',
 'summary': 'Escalated to Mark through the API',
 'assignees': [{'id': 'xyz',
 'type': 'user_reference',
 'summary': 'Mark'}]},
 {'id': '102',
  'type': 'log_file',
  'summary': 'Escalated to Kevin by SMS',
  'assignees': [{'id': 'abc',
  'type': 'user_reference',
  'summary': 'Kevin'}]},
 {'id': '103',
  'type': 'log_file',
  'summary': 'Escalated to Scott through the API',
  'assignees': [{'id': 'pqr',
  'type': 'user_reference',
  'summary': 'Scott'}]}]

In the sample above, I expect a count of 2 for number of times through the API has returned for summary and the assignee value as Mark and Scott as these two different people have been assigned.

list dictionary python
2 Answers

You can just loop through the list. Here is my example:

data = [{'id': '101', 'type': 'log_file', 'summary': 'Escalated to Mark through the API', 'assignees': [{'id': 'xyz', 'type': 'user_reference', 'summary': 'Mark'}]}, {'id': '102', 'type': 'log_file', 'summary': 'Escalated to Kevin by SMS', 'assignees': [{'id': 'abc', 'type': 'user_reference', 'summary': 'Kevin'}]}, {'id': '103', 'type': 'log_file', 'summary': 'Escalated to Scott through the API', 'assignees': [{'id': 'pqr', 'type': 'user_reference', 'summary': 'Scott'}]}]
people = [sum["assignees"][0]["summary"] for sum in data if "through the API" in sum["summary"]]   #This will return ["Mark", "Scott"]
number_of_assignees = len(people)    #This will return 2
user_124663290

Make a Pandas DataFrame:

df=pd.DataFrame(dd)

Count the number of appearances and put assignees names in a separate column:

df['summary'].str.contains('through the API').sum()
df['names'] = pd.Series([df.iloc[s,3][0]['summary'] for s in np.arange(0,df.shape[0])])
user_40086570
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