Reputation:
I have a json file with keys
and Results
. The result has 3 parts. like this:
df.json()[0]['Results'][0]
{'categoryId': '2674',
'categoryName': 'software engineer',
'score': '1.0377672767639161'}
I want to collect all keys
who have the same categoryName
in the result. and then count them. Is it possible?
Upvotes: 0
Views: 45
Reputation:
One way of doing it would be iterating over every group in one of the following ways: if you just want to know the count of one group you can do this:
category_name = "software engineer"
count = 0
for cat in df.json()[0]['Results']:
if cat['categoryName'] == category_name:
count += 1
If you want to count all categories at the same time you can do that as well:
category_count = {}
for cat in df.json()[0]['Results']:
category = cat['categoryName']
if category in category_count.keys():
category_count[category] += 1
else:
category_count[category] = 1
to get the corresponding keys you can do:
category_count = {}
for key, cat in enumerate(df.json()[0]['Results']):
category = cat['categoryName']
if category in category_count.keys():
category_count[category].append(key)
else:
category_count[category] = [key]
that way you can get all keys with the categoryName="software engineer"
like this: category_count["software_engineer"]
Upvotes: 2