CODEWITHSUNDEEP
pythondictionary
Xin
Xin

Reputation: 674

How to group and add dictionary key within a list of dictionaries

Below I have a list of dictionaries:

dict = [{'name': 'Sector',
  'entity': 'ORG(100.0), nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan',
  'synonyms': "Sector:['sector', 'sphere'], , ",
  'definition': 'Sector: a plane figure bounded by two radii and the included arc of a circle',
  'sentiment': ''},
  {'name': 'Community Name',
  'entity': 'PERSON(39.74), GPE(22.88), ORG(20.57), LOC(9.95), FAC(3.6), NORP(2.02), CARDINAL(0.45), LAW(0.39), DATE(0.39), nan, nan, nan, nan, nan',
  'synonyms': "Community:['biotic_community', 'community', 'community_of_interests', 'residential_area', 'residential_district'], Name:['advert', 'appoint', 'bring_up', 'call', 'cite', 'constitute', 'describe', 'diagnose', 'discover', 'distinguish', 'epithet', 'figure', 'gens', 'identify', 'key', 'key_out', 'list', 'make', 'mention', 'name', 'nominate', 'public_figure', 'refer'], ",
  'definition': 'Community: a group of people living in a particular local area, Name: a language unit by which a person or thing is known',
  'sentiment': ''}]

How do I add a new key that groups entity, synonyms, definition, and sentiment as values?

desired output (nlp is the new added key):

dict = [{'name': 'Sector',

  'nlp': {

  'entity': 'ORG(100.0), nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan',
  'synonyms': "Sector:['sector', 'sphere'], , ",
  'definition': 'Sector: a plane figure bounded by two radii and the included arc of a circle',
  'sentiment': ''}},

  {'name': 'Community Name',

  'nlp':{

  'entity': 'PERSON(39.74), GPE(22.88), ORG(20.57), LOC(9.95), FAC(3.6), NORP(2.02), CARDINAL(0.45), LAW(0.39), DATE(0.39), nan, nan, nan, nan, nan',
  'synonyms': "Community:['biotic_community', 'community', 'community_of_interests', 'residential_area', 'residential_district'], Name:['advert', 'appoint', 'bring_up', 'call', 'cite', 'constitute', 'describe', 'diagnose', 'discover', 'distinguish', 'epithet', 'figure', 'gens', 'identify', 'key', 'key_out', 'list', 'make', 'mention', 'name', 'nominate', 'public_figure', 'refer'], ",
  'definition': 'Community: a group of people living in a particular local area, Name: a language unit by which a person or thing is known',
  'sentiment': ''}}]

Upvotes: 0

Views: 49

Answers (2)

Achuth Varghese
Achuth Varghese

Reputation: 2451

pop() removes an element and returns that element

result = [{'name':d.pop('name'), 'nlp':d} for d in dict]

By using dictinary key name we are removing that key from d. As said, d.pop('name') will return the value in d['name']

After d.pop('name'), d will not have the key name in it.

Upvotes: 1

Jan
Jan

Reputation: 43189

You may use .pop() in a for loop:

lst = [{'name': 'Sector',
        'entity': 'ORG(100.0), nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan',
        'synonyms': "Sector:['sector', 'sphere'], , ",
        'definition': 'Sector: a plane figure bounded by two radii and the included arc of a circle',
        'sentiment': ''},
       {'name': 'Community Name',
        'entity': 'PERSON(39.74), GPE(22.88), ORG(20.57), LOC(9.95), FAC(3.6), NORP(2.02), CARDINAL(0.45), LAW(0.39), DATE(0.39), nan, nan, nan, nan, nan',
        'synonyms': "Community:['biotic_community', 'community', 'community_of_interests', 'residential_area', 'residential_district'], Name:['advert', 'appoint', 'bring_up', 'call', 'cite', 'constitute', 'describe', 'diagnose', 'discover', 'distinguish', 'epithet', 'figure', 'gens', 'identify', 'key', 'key_out', 'list', 'make', 'mention', 'name', 'nominate', 'public_figure', 'refer'], ",
        'definition': 'Community: a group of people living in a particular local area, Name: a language unit by which a person or thing is known',
        'sentiment': ''}]

result = []
for dct in lst:
    newdict = {}
    newdict["name"] = dct.pop('name')
    newdict["nlp"] = dct
    result.append(newdict)

print(result)

Which yields

[{'name': 'Sector', 'nlp': {'entity': 'ORG(100.0), nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan', 'synonyms': "Sector:['sector', 'sphere'], , ", 'definition': 'Sector: a plane figure bounded by two radii and the included arc of a circle', 'sentiment': ''}}, {'name': 'Community Name', 'nlp': {'entity': 'PERSON(39.74), GPE(22.88), ORG(20.57), LOC(9.95), FAC(3.6), NORP(2.02), CARDINAL(0.45), LAW(0.39), DATE(0.39), nan, nan, nan, nan, nan', 'synonyms': "Community:['biotic_community', 'community', 'community_of_interests', 'residential_area', 'residential_district'], Name:['advert', 'appoint', 'bring_up', 'call', 'cite', 'constitute', 'describe', 'diagnose', 'discover', 'distinguish', 'epithet', 'figure', 'gens', 'identify', 'key', 'key_out', 'list', 'make', 'mention', 'name', 'nominate', 'public_figure', 'refer'], ", 'definition': 'Community: a group of people living in a particular local area, Name: a language unit by which a person or thing is known', 'sentiment': ''}}]

Upvotes: 1

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