从json中提取值并使用python进行过滤

Question

我对python很陌生，我正在学习。

我有一个包含以下json数据的json文件。

{
"document_tone": {
"tone_categories": [
  {
    "category_id": "emotion_tone", 
    "tones": [
      {
        "tone_name": "Anger", 
        "score": 0.041202, 
        "tone_id": "anger"
      }, 
      {
        "tone_name": "Disgust", 
        "score": 0.054272, 
        "tone_id": "disgust"
      }, 
      {
        "tone_name": "Fear", 
        "score": 0.080706, 
        "tone_id": "fear"
      }, 
      {
        "tone_name": "Joy", 
        "score": 0.813125, 
        "tone_id": "joy"
      }, 
      {
        "tone_name": "Sadness", 
        "score": 0.155878, 
        "tone_id": "sadness"
      }
    ], 
    "category_name": "Emotion Tone"
  }, 
  {
    "category_id": "writing_tone", 
    "tones": [
      {
        "tone_name": "Analytical", 
        "score": 0.0, 
        "tone_id": "analytical"
      }, 
      {
        "tone_name": "Confident", 
        "score": 0.0, 
        "tone_id": "confident"
      }, 
      {
        "tone_name": "Tentative", 
        "score": 0.0, 
        "tone_id": "tentative"
      }
    ], 
    "category_name": "Writing Tone"
  }, 
  {
    "category_id": "social_tone", 
    "tones": [
      {
        "tone_name": "Openness", 
        "score": 0.028, 
        "tone_id": "openness_big5"
      }, 
      {
        "tone_name": "Conscientiousness", 
        "score": 0.314, 
        "tone_id": "conscientiousness_big5"
      }, 
      {
        "tone_name": "Extraversion", 
        "score": 0.944, 
        "tone_id": "extraversion_big5"
      }, 
      {
        "tone_name": "Agreeableness", 
        "score": 0.982, 
        "tone_id": "agreeableness_big5"
      }, 
      {
        "tone_name": "Emotional Range", 
        "score": 0.865, 
        "tone_id": "neuroticism_big5"
      }
    ], 
    "category_name": "Social Tone"
  }
]
}
}

首先我要提取以下字段，在提取字段后，我需要“tone_name”和最高分数。

^{pr2}$

我的输出应该是：喜悦

我的代码是

^{3}$

我的数据.json文件包含

"{\n  \"document_tone\": {\n    \"tone_categories\": [\n      {\n            
 \"category_id\": \"emotion_tone\", \n        \"tones\": [\n                        
 {\n            \"tone_name\": \"Anger\", \n            \"score\": 
 0.372974, \n            \"tone_id\": \"anger\"\n          }, \n          
 {\n            \"tone_name\": \"Disgust\", \n            \"score\": 
 0.114389, \n            \"tone_id\": \"disgust\"\n          }, \n          
 {\n            \"tone_name\": \"Fear\", \n            \"score\": 
 0.083108, \n            \"tone_id\": \"fear\"\n          }, \n          
 {\n            \"tone_name\": \"Joy\", \n            \"score\": 
 0.028716, \n            \"tone_id\": \"joy\"\n          }, \n          
 {\n            \"tone_name\": \"Sadness\", \n            \"score\": 
 0.461562, \n            \"tone_id\": \"sadness\"\n          }\n        
 ], \n        \"category_name\": \"Emotion Tone\"\n      }, \n      
 {\n        \"category_id\": \"writing_tone\", \n        \"tones\": 
 [\n          {\n            \"tone_name\": \"Analytical\", \n            
 \"score\": 0.722, \n            \"tone_id\": \"analytical\"\n          
 }, \n          {\n            \"tone_name\": \"Confident\", \n            
 \"score\": 0.0, \n            \"tone_id\": \"confident\"\n          
 }, \n          {\n            \"tone_name\": \"Tentative\", \n              
 \"score\": 0.0, \n            \"tone_id\": \"tentative\"\n          
 }\n        ], \n        \"category_name\": \"Writing Tone\"\n      }, 
 \n      {\n        \"category_id\": \"social_tone\", \n        
 \"tones\": [\n          {\n            \"tone_name\": \"Openness\", 
 \n            \"score\": 0.015, \n            \"tone_id\": 
 \"openness_big5\"\n          }, \n          {\n            
 \"tone_name\": \"Conscientiousness\", \n            \"score\": 0.045, 
 \n            \"tone_id\": \"conscientiousness_big5\"\n          }, 
 \n          {\n            \"tone_name\": \"Extraversion\", \n            
 \"score\": 0.722, \n            \"tone_id\": \"extraversion_big5\"\n          
 }, \n          {\n            \"tone_name\": \"Agreeableness\", \n            
 \"score\": 0.706, \n            \"tone_id\": \"agreeableness_big5\"\n          
 }, \n          {\n            \"tone_name\": \"Emotional Range\", \n               
 \"score\": 0.974, \n            \"tone_id\": \"neuroticism_big5\"\n          
 }\n        ], \n        \"category_name\": \"Social Tone\"\n      }\n    
 ]\n  }\n}"

Answer 1

基本上，要想在这里做你想做的事情，你只需要在dict中导航，直到你得到你的音调列表，然后循环每个音调，并为这个音调打印出它的tone_name

parsedJson = json.loads(jsonFile)
for tone in parsedJson['document_tone']['tone_categories'][0]['tones']:
    print(tone['tone_name'])
# Anger
# Disgust
# Fear
# Joy
# Sadness

这是你的固定密码

^{pr2}$