从 Tone Analyser 的 JSON 响应的词典列表中提取数据
Extracting data from list of dictionaries from Tone Analyser's JSON response
我正在使用 IBM Watson 的语气分析器分析文本,我正在尝试提取与句子语气相关的所有信息(例如;sentence_id
、text
、tones
、tone_id
、tone_name
、score
) 并将其添加到数据框(包含列;sentence_id
、text
、tones
、tone_id
、 score
和 tone_name
)。这是我的输出示例:
> [{'document_tone': {'tones': [{'score': 0.551743,
'tone_id': 'analytical',
'tone_name': 'Analytical'}]},
'sentences_tone': [{'sentence_id': 0,
'text': '@jozee25 race is the basis on which quotas are implemented.',
'tones': []},
{'sentence_id': 1, 'text': 'helloooooo', 'tones': []}]},
{'document_tone': {'tones': []}},
{'document_tone': {'tones': [{'score': 0.802429,
'tone_id': 'analytical',
'tone_name': 'Analytical'},
{'score': 0.60167, 'tone_id': 'confident', 'tone_name': 'Confident'}]},
'sentences_tone': [{'sentence_id': 0,
'text': '@growawaysa @cricketandre i have the answer on top yard from dpw:it is not currently "surplus to govt requirements".it is still being used for garaging until a new facility is ready in maitland.the',
'tones': [{'score': 0.631014,
'tone_id': 'analytical',
'tone_name': 'Analytical'}]},
{'sentence_id': 1,
'text': 'cost of the housing options will of course depend on prospects for cross subsidisation.',
'tones': [{'score': 0.589295,
'tone_id': 'analytical',
'tone_name': 'Analytical'},
{'score': 0.509368, 'tone_id': 'confident', 'tone_name': 'Confident'}]}]},
{'document_tone': {'tones': [{'score': 0.58393,
'tone_id': 'tentative',
'tone_name': 'Tentative'},
{'score': 0.641954, 'tone_id': 'analytical', 'tone_name': 'Analytical'}]}},
{'document_tone': {'tones': [{'score': 0.817073,
'tone_id': 'joy',
'tone_name': 'Joy'},
{'score': 0.920556, 'tone_id': 'analytical', 'tone_name': 'Analytical'},
{'score': 0.808202, 'tone_id': 'tentative', 'tone_name': 'Tentative'}]},
'sentences_tone': [{'sentence_id': 0,
'text': 'thanks @khayadlangaand colleagues for the fascinating tour yesterday.really',
'tones': [{'score': 0.771305, 'tone_id': 'joy', 'tone_name': 'Joy'},
{'score': 0.724236, 'tone_id': 'analytical', 'tone_name': 'Analytical'}]},
{'sentence_id': 1,
'text': 'eyeopening and i learnt a lot.',
'tones': [{'score': 0.572756, 'tone_id': 'joy', 'tone_name': 'Joy'},
{'score': 0.842108, 'tone_id': 'analytical', 'tone_name': 'Analytical'},
{'score': 0.75152, 'tone_id': 'tentative', 'tone_name': 'Tentative'}]}]},
这是我为获得此输出而编写的代码:
result =[]
for i in helen['Tweets']:
tone_analysis = tone_analyzer.tone(
{'text': i},
'application/json'
).get_result()
result.append(tone_analysis)
首先,由于您的 JSON 格式不正确,我使用的是来自 Tone 分析器的 JSON API 可用参考 here
使用 API 参考中的 JSON 和 Pandas json_normalize,这是我想出的代码
from pandas.io.json import json_normalize
jsonfile = {
"document_tone": {
"tones": [
{
"score": 0.6165,
"tone_id": "sadness",
"tone_name": "Sadness"
},
{
"score": 0.829888,
"tone_id": "analytical",
"tone_name": "Analytical"
}
]
},
"sentences_tone": [
{
"sentence_id": 0,
"text": "Team, I know that times are tough!",
"tones": [
{
"score": 0.801827,
"tone_id": "analytical",
"tone_name": "Analytical"
}
]
},
{
"sentence_id": 1,
"text": "Product sales have been disappointing for the past three quarters.",
"tones": [
{
"score": 0.771241,
"tone_id": "sadness",
"tone_name": "Sadness"
},
{
"score": 0.687768,
"tone_id": "analytical",
"tone_name": "Analytical"
}
]
},
{
"sentence_id": 2,
"text": "We have a competitive product, but we need to do a better job of selling it!",
"tones": [
{
"score": 0.506763,
"tone_id": "analytical",
"tone_name": "Analytical"
}
]
}
]
}
mydata = json_normalize(jsonfile['sentences_tone'])
mydata.head(3)
print(mydata)
tones_data = json_normalize(data=jsonfile['sentences_tone'], record_path='tones')
tones_data.head(3)
print(tones_data)
输出数据帧将是
sentence_id ... tones
0 0 ...[{'score': 0.801827, 'tone_id': 'analytical', ...
1 1 ...[{'score': 0.771241, 'tone_id': 'sadness', 'to...
2 2 ...[{'score': 0.506763, 'tone_id': 'analytical', ...
[3 rows x 3 columns]
score tone_id tone_name
0 0.801827 analytical Analytical
1 0.771241 sadness Sadness
2 0.687768 analytical Analytical
3 0.506763 analytical Analytical
此外,我已经创建了 REPL 供您更改输入和 运行 浏览器上的代码 - https://repl.it/@aficionado/DarkturquoiseUnnaturalDistributeddatabase
参考这个 Kaggle link 了解更多关于 flattening JSON in Python using Pandas
我正在使用 IBM Watson 的语气分析器分析文本,我正在尝试提取与句子语气相关的所有信息(例如;sentence_id
、text
、tones
、tone_id
、tone_name
、score
) 并将其添加到数据框(包含列;sentence_id
、text
、tones
、tone_id
、 score
和 tone_name
)。这是我的输出示例:
> [{'document_tone': {'tones': [{'score': 0.551743,
'tone_id': 'analytical',
'tone_name': 'Analytical'}]},
'sentences_tone': [{'sentence_id': 0,
'text': '@jozee25 race is the basis on which quotas are implemented.',
'tones': []},
{'sentence_id': 1, 'text': 'helloooooo', 'tones': []}]},
{'document_tone': {'tones': []}},
{'document_tone': {'tones': [{'score': 0.802429,
'tone_id': 'analytical',
'tone_name': 'Analytical'},
{'score': 0.60167, 'tone_id': 'confident', 'tone_name': 'Confident'}]},
'sentences_tone': [{'sentence_id': 0,
'text': '@growawaysa @cricketandre i have the answer on top yard from dpw:it is not currently "surplus to govt requirements".it is still being used for garaging until a new facility is ready in maitland.the',
'tones': [{'score': 0.631014,
'tone_id': 'analytical',
'tone_name': 'Analytical'}]},
{'sentence_id': 1,
'text': 'cost of the housing options will of course depend on prospects for cross subsidisation.',
'tones': [{'score': 0.589295,
'tone_id': 'analytical',
'tone_name': 'Analytical'},
{'score': 0.509368, 'tone_id': 'confident', 'tone_name': 'Confident'}]}]},
{'document_tone': {'tones': [{'score': 0.58393,
'tone_id': 'tentative',
'tone_name': 'Tentative'},
{'score': 0.641954, 'tone_id': 'analytical', 'tone_name': 'Analytical'}]}},
{'document_tone': {'tones': [{'score': 0.817073,
'tone_id': 'joy',
'tone_name': 'Joy'},
{'score': 0.920556, 'tone_id': 'analytical', 'tone_name': 'Analytical'},
{'score': 0.808202, 'tone_id': 'tentative', 'tone_name': 'Tentative'}]},
'sentences_tone': [{'sentence_id': 0,
'text': 'thanks @khayadlangaand colleagues for the fascinating tour yesterday.really',
'tones': [{'score': 0.771305, 'tone_id': 'joy', 'tone_name': 'Joy'},
{'score': 0.724236, 'tone_id': 'analytical', 'tone_name': 'Analytical'}]},
{'sentence_id': 1,
'text': 'eyeopening and i learnt a lot.',
'tones': [{'score': 0.572756, 'tone_id': 'joy', 'tone_name': 'Joy'},
{'score': 0.842108, 'tone_id': 'analytical', 'tone_name': 'Analytical'},
{'score': 0.75152, 'tone_id': 'tentative', 'tone_name': 'Tentative'}]}]},
这是我为获得此输出而编写的代码:
result =[]
for i in helen['Tweets']:
tone_analysis = tone_analyzer.tone(
{'text': i},
'application/json'
).get_result()
result.append(tone_analysis)
首先,由于您的 JSON 格式不正确,我使用的是来自 Tone 分析器的 JSON API 可用参考 here
使用 API 参考中的 JSON 和 Pandas json_normalize,这是我想出的代码
from pandas.io.json import json_normalize
jsonfile = {
"document_tone": {
"tones": [
{
"score": 0.6165,
"tone_id": "sadness",
"tone_name": "Sadness"
},
{
"score": 0.829888,
"tone_id": "analytical",
"tone_name": "Analytical"
}
]
},
"sentences_tone": [
{
"sentence_id": 0,
"text": "Team, I know that times are tough!",
"tones": [
{
"score": 0.801827,
"tone_id": "analytical",
"tone_name": "Analytical"
}
]
},
{
"sentence_id": 1,
"text": "Product sales have been disappointing for the past three quarters.",
"tones": [
{
"score": 0.771241,
"tone_id": "sadness",
"tone_name": "Sadness"
},
{
"score": 0.687768,
"tone_id": "analytical",
"tone_name": "Analytical"
}
]
},
{
"sentence_id": 2,
"text": "We have a competitive product, but we need to do a better job of selling it!",
"tones": [
{
"score": 0.506763,
"tone_id": "analytical",
"tone_name": "Analytical"
}
]
}
]
}
mydata = json_normalize(jsonfile['sentences_tone'])
mydata.head(3)
print(mydata)
tones_data = json_normalize(data=jsonfile['sentences_tone'], record_path='tones')
tones_data.head(3)
print(tones_data)
输出数据帧将是
sentence_id ... tones
0 0 ...[{'score': 0.801827, 'tone_id': 'analytical', ...
1 1 ...[{'score': 0.771241, 'tone_id': 'sadness', 'to...
2 2 ...[{'score': 0.506763, 'tone_id': 'analytical', ...
[3 rows x 3 columns]
score tone_id tone_name
0 0.801827 analytical Analytical
1 0.771241 sadness Sadness
2 0.687768 analytical Analytical
3 0.506763 analytical Analytical
此外,我已经创建了 REPL 供您更改输入和 运行 浏览器上的代码 - https://repl.it/@aficionado/DarkturquoiseUnnaturalDistributeddatabase
参考这个 Kaggle link 了解更多关于 flattening JSON in Python using Pandas