extract emotions from text in dataframe in senticnet

Question

I am very novice in python and I treat to extract emotions from sentence in datafram though senticNet
this my code but its not correct
I don't know what's the wrong

from senticnet.senticnet import SenticNet

def emotion_list1(text):

    Emotion_list=[]
    Emotion = pd.DataFrame(columns=['Emotion'])

    sn = SenticNet()

    for elemnt in text:
        for word in elemnt:
            try:              
                Emotion_list.append(sn.moodtags(word))
            except:
                pass
    Emotion = Emotion.append(pd.Series(Emotion_list),ignore_index=True)

    return Emotion


dfe= pd.DataFrame()

clean_text_list = df['translated'].values 

words_list = [text.split() for text in clean_text_list]

dfe = emotion_list1(words_list)

Answer 1

Are you facing any specific errors? I am able to extract the emotions using sn.moodtags() from a sentence.

# import 
from senticnet.senticnet import SenticNet
from nltk.tokenize import word_tokenize

# define sentinet()
sn = SenticNet()

# create empty list to store results
emotion_list = []

# tokenize text 
# you can use word_tokenize() from the nltk library to tokenize your text
text = 'love hate python'
tokenized_text = word_tokenize(text)

# loop through tokenized text and emtion and append to list
for word in tokenized_text:
    emotion_list.append(sn.moodtags(word))

# print
print(emotion_list)

This outputs:

[['#joy', '#eagerness'], ['#pleasantness', '#fear'], ['#pleasantness', '#fear']]