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Ngram with counts in the below desired output

.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty height:90px;width:728px;box-sizing:border-box;

1

the following got me to this below output:

 words freq
0 hello 5
1 yes 10


I would like the above output to be same for ngrams(4). The results is only showing freq with "1". Can someone help me tune the codes for ngrams and as per the above output. The requirement is Ngrams with freqencies and output in excel(xlsx).

Examples shown below:

 (('benito', 'kanchan'), 1),
 (('kanchan', 'tata'), 1),
 (('tata', 'arora'), 1),

So far the code:

df = pd.read_excel(r"Filename")

#Converting to lovercase
df['Body'] = df['Body'].apply(lambda x: " ".join(x.lower() for x in x.split()))
df['Body'].head()

#Count of Words
df['word_count'] = df['Body'].apply(lambda x: len(str(x).split(" ")))
df[['Body','word_count']].head()

#Removing Punctuation
df['Body'] = df['Body'].str.replace('[^ws]','')
df['Body'].head()

#Removing Stop Words
from nltk.corpus import stopwords
stop = stopwords.words('english')

df['Body'] = df['Body'].apply(lambda x: " ".join(x for x in x.split() if x not in stop))
df['Body'].head()

#df['Body'] = df['Body'].astype('|S')

# Word Count
tf1 = (df['Body']).apply(lambda x: pd.value_counts(x.split(" "))).sum(axis = 0).reset_index()
print (tf1)
tf1.columns = ['words','tf']
tf1

Ngrams
from collections import Counter
from textblob import TextBlob
a = TextBlob(tf1['words'][0]).ngrams(4)
a = [','.join(map(str, l)) for l in a]
print (a)
counter = (Counter (a))
counter.most_common(150)
counter.columns = ['ngram','tf']
counter

python n-gram

share|improve this question

asked Mar 22 at 13:40

stenin joshistenin joshi

62

add a comment | 

1

the following got me to this below output:

 words freq
0 hello 5
1 yes 10


I would like the above output to be same for ngrams(4). The results is only showing freq with "1". Can someone help me tune the codes for ngrams and as per the above output. The requirement is Ngrams with freqencies and output in excel(xlsx).

Examples shown below:

 (('benito', 'kanchan'), 1),
 (('kanchan', 'tata'), 1),
 (('tata', 'arora'), 1),

So far the code:

df = pd.read_excel(r"Filename")

#Converting to lovercase
df['Body'] = df['Body'].apply(lambda x: " ".join(x.lower() for x in x.split()))
df['Body'].head()

#Count of Words
df['word_count'] = df['Body'].apply(lambda x: len(str(x).split(" ")))
df[['Body','word_count']].head()

#Removing Punctuation
df['Body'] = df['Body'].str.replace('[^ws]','')
df['Body'].head()

#Removing Stop Words
from nltk.corpus import stopwords
stop = stopwords.words('english')

df['Body'] = df['Body'].apply(lambda x: " ".join(x for x in x.split() if x not in stop))
df['Body'].head()

#df['Body'] = df['Body'].astype('|S')

# Word Count
tf1 = (df['Body']).apply(lambda x: pd.value_counts(x.split(" "))).sum(axis = 0).reset_index()
print (tf1)
tf1.columns = ['words','tf']
tf1

Ngrams
from collections import Counter
from textblob import TextBlob
a = TextBlob(tf1['words'][0]).ngrams(4)
a = [','.join(map(str, l)) for l in a]
print (a)
counter = (Counter (a))
counter.most_common(150)
counter.columns = ['ngram','tf']
counter

python n-gram

share|improve this question

asked Mar 22 at 13:40

stenin joshistenin joshi

62

add a comment | 

the following got me to this below output:

 words freq
0 hello 5
1 yes 10


I would like the above output to be same for ngrams(4). The results is only showing freq with "1". Can someone help me tune the codes for ngrams and as per the above output. The requirement is Ngrams with freqencies and output in excel(xlsx).

Examples shown below:

 (('benito', 'kanchan'), 1),
 (('kanchan', 'tata'), 1),
 (('tata', 'arora'), 1),

So far the code:

df = pd.read_excel(r"Filename")

#Converting to lovercase
df['Body'] = df['Body'].apply(lambda x: " ".join(x.lower() for x in x.split()))
df['Body'].head()

#Count of Words
df['word_count'] = df['Body'].apply(lambda x: len(str(x).split(" ")))
df[['Body','word_count']].head()

#Removing Punctuation
df['Body'] = df['Body'].str.replace('[^ws]','')
df['Body'].head()

#Removing Stop Words
from nltk.corpus import stopwords
stop = stopwords.words('english')

df['Body'] = df['Body'].apply(lambda x: " ".join(x for x in x.split() if x not in stop))
df['Body'].head()

#df['Body'] = df['Body'].astype('|S')

# Word Count
tf1 = (df['Body']).apply(lambda x: pd.value_counts(x.split(" "))).sum(axis = 0).reset_index()
print (tf1)
tf1.columns = ['words','tf']
tf1

Ngrams
from collections import Counter
from textblob import TextBlob
a = TextBlob(tf1['words'][0]).ngrams(4)
a = [','.join(map(str, l)) for l in a]
print (a)
counter = (Counter (a))
counter.most_common(150)
counter.columns = ['ngram','tf']
counter

python n-gram

share|improve this question

asked Mar 22 at 13:40

stenin joshistenin joshi

62

 words freq
0 hello 5
1 yes 10


I would like the above output to be same for ngrams(4). The results is only showing freq with "1". Can someone help me tune the codes for ngrams and as per the above output. The requirement is Ngrams with freqencies and output in excel(xlsx).

 (('benito', 'kanchan'), 1),
 (('kanchan', 'tata'), 1),
 (('tata', 'arora'), 1),

So far the code:

df = pd.read_excel(r"Filename")

#Converting to lovercase
df['Body'] = df['Body'].apply(lambda x: " ".join(x.lower() for x in x.split()))
df['Body'].head()

#Count of Words
df['word_count'] = df['Body'].apply(lambda x: len(str(x).split(" ")))
df[['Body','word_count']].head()

#Removing Punctuation
df['Body'] = df['Body'].str.replace('[^ws]','')
df['Body'].head()

#Removing Stop Words
from nltk.corpus import stopwords
stop = stopwords.words('english')

df['Body'] = df['Body'].apply(lambda x: " ".join(x for x in x.split() if x not in stop))
df['Body'].head()

#df['Body'] = df['Body'].astype('|S')

# Word Count
tf1 = (df['Body']).apply(lambda x: pd.value_counts(x.split(" "))).sum(axis = 0).reset_index()
print (tf1)
tf1.columns = ['words','tf']
tf1

share|improve this question

asked Mar 22 at 13:40

stenin joshistenin joshi

62

share|improve this question

asked Mar 22 at 13:40

stenin joshistenin joshi

62

asked Mar 22 at 13:40

stenin joshistenin joshi

62

asked Mar 22 at 13:40

stenin joshistenin joshi

62