I need to convert a doc string sentence into a list

Input file is:

l1 = ['Passing much less urine', 'Bleeding from any body part', 'Feeling extremely lethargic/weak', 'Excessive sleepiness/restlessness', 'Altered mental status', 'Seizure/fits', 'Breathlessness', 'Blood in sputum', 'Chest pain', 'Sound/noise in breathing', 'Drooling of saliva', 'Difficulty in opening mouth']


k=[]
for n in range(0,len(l1)):
    e = l1[n]
    doc =nlp(e)
    for token in doc:
        if token.lemma_ != "-PRON-":
            temp = token.lemma_.lower().strip()
        else:
            temp = token.lower_
        k.append(temp)
    cleaned_tokens = []
    t = []
    d = []
    
    for token in k:
        li = []
        if token not in stopwords and token not in punct:
            cleaned_tokens.append(token)
            
        li= " ".join(cleaned_tokens)
    t.append(li)
    print(t)

This code gives output:

['pass urine']
['pass urine bleed body']
['pass urine bleed body feel extremely lethargic weak']

But I need output should be:

["pass urine", "bleed body", "feel extremely lethargic weak"]

Suggest me how can I get this result.

Answer

This produces the results you want:

import spacy
nlp = spacy.load("en_core_web_md")

l1 = ['Passing much less urine', 'Bleeding from any body part', 'Feeling extremely lethargic/weak', 'Excessive sleepiness/restlessness', 'Altered mental status', 'Seizure/fits', 'Breathlessness', 'Blood in sputum', 'Chest pain', 'Sound/noise in breathing', 'Drooling of saliva', 'Difficulty in opening mouth']
docs = nlp.pipe(l1)

t= []
for doc in docs:
    clean_doc = " ".join([tok.text.lower() for tok in doc if not tok.is_stop and not tok.is_punct])
    t.append(clean_doc)           

print(t)

['passing urine', 'bleeding body', 'feeling extremely lethargic weak', 'excessive sleepiness restlessness', 'altered mental status', 'seizure fits', 'breathlessness', 'blood sputum', 'chest pain', 'sound noise breathing', 'drooling saliva', 'difficulty opening mouth']

In case you need lemma:

t= []
for doc in docs:
    clean_doc = " ".join([tok.lemma_.lower() for tok in doc if not tok.is_stop and not tok.is_punct])
    t.append(clean_doc)           

print(t)
['pass urine', 'bleed body', 'feel extremely lethargic weak', 'excessive sleepiness restlessness', 'alter mental status', 'seizure fit', 'breathlessness', 'blood sputum', 'chest pain', 'sound noise breathing', 'drool saliva', 'difficulty open mouth']