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问题描述
我正在使用lstm方法实施情绪分析，我已经训练了模型，并且正在做我的预测部分，而我已经正确地进行了预测.现在，我想添加在数据帧中获得的输出，我尝试了一下，但是结果有误.有人可以帮我更正我的代码吗.
I am implementing an emotion analysis using lstm method, I have already trained my model and I am doing my prediction part where I have already done the prediction correctly. Now i want to add the output I obtained in a dataframe, I tried it but I am having wrong results. Can someone please help me with the correction of my codes please.
我将发布代码以及获得的输出以及输出的显示方式.
I am posting my codes along with the output obtained and how I want my output to be.
这是我的代码:
with open('output1.json', 'w') as f:
json.dump(new_data, f)
selection1 = new_data['selection1']
for item in selection1:
name = item['name']
print ('>>>>>>>>>>>>>>>>>> ', name)
Date = item['reviews']
for d in Date:
date = d['date']
print('>>>>>>>>>>>>>>>>>> ', date)
CommentID = item['reviews']
for com in CommentID:
comment = com['review'].lower() # converting all to lowercase
result = re.sub(r'\d+', '', comment) # remove numbers
results = (result.translate(
str.maketrans('', '', string.punctuation))).strip() # remove punctuations and white spaces
comments = remove_stopwords(results)
print('>>>>>>',comments)
#add the words in comments that are already present in the keys of dictionary
encoded_samples = [[word2id[word] for word in comments if word in word2id.keys()]]
# Padding
encoded_samples = keras.preprocessing.sequence.pad_sequences(encoded_samples, maxlen=max_words)
# Make predictions
label_probs, attentions = model_with_attentions.predict(encoded_samples)
label_probs = {id2label[_id]: prob for (label, _id), prob in zip(label2id.items(), label_probs[0])}
#Get word attentions using attenion vector
print(label_probs)
dataframe={'name': [name],'date': [date], 'comment': [comment], 'label':[label_probs]}
table = pd.DataFrame(dataframe, columns=['name','date', 'comment', 'label'])
print(table)
下面是我获得的输出:
name ... label
0 Oasis Villas by Evaco Holidays ... {'joy': 0.018415175, 'surprise': 4.6217923e-05...
[1 rows x 4 columns]
这是不正确的..
以上打印输出如下:
>>>>>>>>>>>>>>>>>> Heritage The Villas
>>>>>>>>>>>>>>>>>> December 23, 2018
>>>>>>>>>>>>>>>>>> January 10, 2018
>>>>>>>>>>>>>>>>>> January 05, 2018
>>>>>>>>>>>>>>>>>> July 23, 2015
>>>>>> ['booked', 'villa', 'valriche', 'mari', 'deal', 'nights', 'checkin', 'lengthy', 'almost', 'hours', 'requested', 'make', 'deposit', 'rs', 'credit', 'card', 'never', 'informed', 'upon', 'booking']
{'joy': 0.03916626, 'surprise': 8.855841e-05, 'love': 0.09760322, 'anger': 0.6667219, 'sadness': 0.0010696664, 'fear': 0.1953505}
>>>>>> ['lovely', 'place', 'recharge']
{'joy': 0.0032763705, 'surprise': 0.0022357441, 'love': 0.11014917, 'anger': 0.09073347, 'sadness': 0.7297514, 'fear': 0.063853815}
>>>>>> ['one', 'word', 'suoerb']
{'joy': 0.13245165, 'surprise': 0.00014895896, 'love': 0.3051644, 'anger': 0.35698283, 'sadness': 0.00021378326, 'fear': 0.20503832}
>>>>>> ['definitely', 'star', 'extremely', 'poor', 'staff', 'service']
{'joy': 0.031011488, 'surprise': 9.065295e-05, 'love': 0.4330521, 'anger': 0.30516183, 'sadness': 0.000128366, 'fear': 0.23055555}
>>>>>>>>>>>>>>>>>> Oasis Villas by Evaco Holidays
>>>>>>>>>>>>>>>>>> January 12, 2020
>>>>>>>>>>>>>>>>>> June 21, 2019
>>>>>>>>>>>>>>>>>> May 30, 2017
>>>>>>>>>>>>>>>>>> December 06, 2015
>>>>>> ['excellent']
{'joy': 0.030443083, 'surprise': 1.9940982e-05, 'love': 0.036508515, 'anger': 0.8760464, 'sadness': 0.0014704008, 'fear': 0.055511605}
>>>>>> ['spent', 'days', 'family', 'really', 'enjoyed', 'stay', 'advantage', 'oasis', 'privacy', 'children', 'years', 'going', 'dinnerbreakfast', 'hotels', 'often', 'burden', 'rather', 'enjoyable', 'experience', 'children', 'could', 'dinnermessnoise', 'without', 'us', 'worry', 'anything', 'pool', 'right', 'front', 'door', 'made', 'everything', 'children', 'staff', 'friendly', 'welcoming', 'artee', 'menni', 'made', 'sure', 'everything', 'fine', 'brought', 'breakfast', 'warm', 'croissants', 'every', 'morning', 'atish', 'made', 'checkin', 'arrangements', 'fast', 'hassle', 'free', 'definitely', 'go']
{'joy': 0.017099116, 'surprise': 7.2406554e-05, 'love': 0.2651248, 'anger': 0.14370358, 'sadness': 5.6088167e-05, 'fear': 0.573944}
>>>>>> ['passé', 'un', 'excellent', 'séjours', 'les', 'villas', 'oasis', 'sont', 'de', 'loin', 'les', 'meilleur', 'villas', 'du', 'groupe', 'evaco']
{'joy': 0.032395113, 'surprise': 9.250247e-05, 'love': 0.08593403, 'anger': 0.6815374, 'sadness': 0.0015245328, 'fear': 0.1985165}
我希望我的数据框像这样:
I want my dataframe to be like:
name date comment label
Heritage The Villas December 23, 2018 ['booked', 'villa', 'valriche'...] {'joy': 0.03916626, 'surprise': 8.855841e-05, 'love': 0.09760322, 'anger': 0.6667219, 'sadness': 0.0010696664, 'fear': 0.1953505}
Heritage The Villas January 10, 2018 ['lovely', 'place', 'recharge'] {'joy': 0.0032763705, 'surprise': 0.0022357441, 'love': 0.11014917, 'anger': 0.09073347, 'sadness': 0.7297514, 'fear': 0.063853815}
.....
Oasis Villas by Evaco Holidays January 12, 2020 ['excellent'] {'joy': 0.030443083, 'surprise': 1.9940982e-05, 'love': 0.036508515, 'anger': 0.8760464, 'sadness': 0.0014704008, 'fear': 0.055511605}
Oasis Villas by Evaco Holidays June 21, 2019 ['spent', 'days', 'family'....] {'joy': 0.017099116, 'surprise': 7.2406554e-05, 'love': 0.2651248, 'anger': 0.14370358, 'sadness': 5.6088167e-05, 'fear': 0.573944}
.....
能帮我吗?
推荐答案
问题出在这一行:
dataframe={'name': [name],'date': [date], 'comment': [comment], 'label':[label_probs]}
为名称，日期，评论，label_probs留空列表，并将它们附加到该列表中，然后将该列表传递给您的DataFrame
Make empty lists for name, date, comment, label_probs and append them to that list and pass that list to your DataFrame
selection1 = new_data['selection1']
names = []
dates = []
comments = []
labels = []
with open('output1.json', 'w') as f:
json.dump(new_data, f)
selection1 = new_data['selection1']
for item in selection1:
name = item['name']
names.append(name) #<-----------------
.
.
.
Date = item['reviews']
for d in Date:
date = d['date']
dates.append(date) #<--------------
print('>>>>>>>>>>>>>>>>>> ', date)
.
.
.
.
然后
dataframe={'name': names,'date': dates,........}
更新后的答案:
for item in selection1:
name = item['name']
Date = item['reviews']
for d in Date:
names.append(name) #<-----------------
date = d['date']
dates.append(date) #<--------------
.
.
.
这应该可以解决您的问题.
This should solve your problem.
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