dataframe take head() to list and append
what I am trying to do is taking the top 6 most relevant books from my csv of 8371 books. I did take out the top 6 books and i would like to do a for loop so i can get all my 8371 books with a list of 6 more relevant books append next to every book
def tf_similarity(s1, s2):
def add_space(s):
return ' '.join(list(s))
s1, s2 = add_space(s1), add_space(s2)
cv = CountVectorizer(tokenizer=lambda s: s.split())
corpus = [s1, s2]
vectors = cv.fit_transform(corpus).toarray()
return np.dot(vectors[0], vectors[1]) / (norm(vectors[0]) * norm(vectors[1]))
for j in range(0,1):
for i in range(8371):
titles.append(tf_similarity(str(document[i]), document[j]))
df = pd.DataFrame()
df["document"] = document
df["titles"] = titles
dff = df.sort_values("titles", ascending=False).head(6)
newdff=dff.values.T.tolist()
new=newdff[0]
for k in range(0,2):
boolist.append(new)
I would like my list look something like this:
book1 top1 top2 top3 top4 top5 top6
book2 top1 top2 top3 top4 top5 top6
Thank you so much for helping :)
python list dataframe tf
add a comment |
what I am trying to do is taking the top 6 most relevant books from my csv of 8371 books. I did take out the top 6 books and i would like to do a for loop so i can get all my 8371 books with a list of 6 more relevant books append next to every book
def tf_similarity(s1, s2):
def add_space(s):
return ' '.join(list(s))
s1, s2 = add_space(s1), add_space(s2)
cv = CountVectorizer(tokenizer=lambda s: s.split())
corpus = [s1, s2]
vectors = cv.fit_transform(corpus).toarray()
return np.dot(vectors[0], vectors[1]) / (norm(vectors[0]) * norm(vectors[1]))
for j in range(0,1):
for i in range(8371):
titles.append(tf_similarity(str(document[i]), document[j]))
df = pd.DataFrame()
df["document"] = document
df["titles"] = titles
dff = df.sort_values("titles", ascending=False).head(6)
newdff=dff.values.T.tolist()
new=newdff[0]
for k in range(0,2):
boolist.append(new)
I would like my list look something like this:
book1 top1 top2 top3 top4 top5 top6
book2 top1 top2 top3 top4 top5 top6
Thank you so much for helping :)
python list dataframe tf
Please edit your code to make it properly indented so others will read and help you. Use 4 indents into the right to make it a code. Also use Python-specific indentation within your code to make it readable.
– dmitryro
Nov 25 '18 at 0:56
add a comment |
what I am trying to do is taking the top 6 most relevant books from my csv of 8371 books. I did take out the top 6 books and i would like to do a for loop so i can get all my 8371 books with a list of 6 more relevant books append next to every book
def tf_similarity(s1, s2):
def add_space(s):
return ' '.join(list(s))
s1, s2 = add_space(s1), add_space(s2)
cv = CountVectorizer(tokenizer=lambda s: s.split())
corpus = [s1, s2]
vectors = cv.fit_transform(corpus).toarray()
return np.dot(vectors[0], vectors[1]) / (norm(vectors[0]) * norm(vectors[1]))
for j in range(0,1):
for i in range(8371):
titles.append(tf_similarity(str(document[i]), document[j]))
df = pd.DataFrame()
df["document"] = document
df["titles"] = titles
dff = df.sort_values("titles", ascending=False).head(6)
newdff=dff.values.T.tolist()
new=newdff[0]
for k in range(0,2):
boolist.append(new)
I would like my list look something like this:
book1 top1 top2 top3 top4 top5 top6
book2 top1 top2 top3 top4 top5 top6
Thank you so much for helping :)
python list dataframe tf
what I am trying to do is taking the top 6 most relevant books from my csv of 8371 books. I did take out the top 6 books and i would like to do a for loop so i can get all my 8371 books with a list of 6 more relevant books append next to every book
def tf_similarity(s1, s2):
def add_space(s):
return ' '.join(list(s))
s1, s2 = add_space(s1), add_space(s2)
cv = CountVectorizer(tokenizer=lambda s: s.split())
corpus = [s1, s2]
vectors = cv.fit_transform(corpus).toarray()
return np.dot(vectors[0], vectors[1]) / (norm(vectors[0]) * norm(vectors[1]))
for j in range(0,1):
for i in range(8371):
titles.append(tf_similarity(str(document[i]), document[j]))
df = pd.DataFrame()
df["document"] = document
df["titles"] = titles
dff = df.sort_values("titles", ascending=False).head(6)
newdff=dff.values.T.tolist()
new=newdff[0]
for k in range(0,2):
boolist.append(new)
I would like my list look something like this:
book1 top1 top2 top3 top4 top5 top6
book2 top1 top2 top3 top4 top5 top6
Thank you so much for helping :)
python list dataframe tf
python list dataframe tf
edited Nov 25 '18 at 3:44
Irene
asked Nov 25 '18 at 0:54
Irene Irene
11
11
Please edit your code to make it properly indented so others will read and help you. Use 4 indents into the right to make it a code. Also use Python-specific indentation within your code to make it readable.
– dmitryro
Nov 25 '18 at 0:56
add a comment |
Please edit your code to make it properly indented so others will read and help you. Use 4 indents into the right to make it a code. Also use Python-specific indentation within your code to make it readable.
– dmitryro
Nov 25 '18 at 0:56
Please edit your code to make it properly indented so others will read and help you. Use 4 indents into the right to make it a code. Also use Python-specific indentation within your code to make it readable.
– dmitryro
Nov 25 '18 at 0:56
Please edit your code to make it properly indented so others will read and help you. Use 4 indents into the right to make it a code. Also use Python-specific indentation within your code to make it readable.
– dmitryro
Nov 25 '18 at 0:56
add a comment |
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Please edit your code to make it properly indented so others will read and help you. Use 4 indents into the right to make it a code. Also use Python-specific indentation within your code to make it readable.
– dmitryro
Nov 25 '18 at 0:56