Python：字典中来自另一个列表的出现次数

Question

I am trying to count the number of times a word exists in a dict column based on a subset of interested words.

First I import my data

products = graphlab.SFrame('amazon_baby.gl/')
products['word_count'] = graphlab.text_analytics.count_words(products['review'])
products.head(5)

Data can be found here: https://drive.google.com/open?id=0BzbhZp-qIglxM3VSVWRsVFRhTWc

I then create list of words i am interested in:

words = ['awesome', 'great', 'fantastic']

I would like to count the number of times each word in "words" occurs in the products['word_count'].

I am not married to using graphlab. It was just suggested to me by a colleague.

Answer 1

Well, I am not pretty sure about what you mean by 'in a dict column'. If it is a list:

import operator
dictionary={'texts':['red blue blue','red black','blue white white','red','white','black','blue red']}
words=['red','white','blue']
freqs=dict()
for t in dictionary['texts']:
    for w in words:
        try:
             freqs[w]+=t.count(w)
        except:
            freqs[w]=t.count(w)
top_words = sorted(freqs.items(), key=operator.itemgetter(1),reverse=True)

If it is just one text:

import operator
dictionary={'text':'red blue blue red black blue white white red white black blue red'}
words=['red','white','blue']
freqs=dict()
for w in words:
    try:
        freqs[w]+=dictionary['text'].count(w)
    except:
        freqs[w]=dictionary['text'].count(w)
top_words = sorted(freqs.items(), key=operator.itemgetter(1),reverse=True) 

Answer 2

If you want to count occurrences of words, a fast way to do it is to use Counter object from collections

For example :

In [3]: from collections import Counter
In [4]: c = Counter(['hello', 'world'])

In [5]: c
Out[5]: Counter({'hello': 1, 'world': 1})

Could you show the output of your products.head(5) command ?

Answer 3

If you stick with graphlab (or SFrame), use the SArray.dict_trim_by_keys method. The documentation is here: https://dato.com/products/create/docs/generated/graphlab.SArray.dict_trim_by_keys.html

import graphlab as gl
sf = gl.SFrame({'review': ['what a good book', 'terrible book']})
sf['word_bag'] = gl.text_analytics.count_words(sf['review'])

keywords = ['good', 'book']
sf['key_words'] = sf['word_bag'].dict_trim_by_keys(keywords, exclude=False)
print sf

+------------------+---------------------+---------------------+
|      review      |       word_bag      |      key_words      |
+------------------+---------------------+---------------------+
| what a good book | {'a': 1, 'good':... | {'good': 1, 'boo... |
|  terrible book   | {'book': 1, 'ter... |     {'book': 1}     |
+------------------+---------------------+---------------------+ 
[2 rows x 3 columns]

Answer 4

Do you want to put each of the counts in a separate column? In that case this may work:

keywords = ['keyword1' , 'keyword2']

def word_counter(dict_cell , word):
if word in dict_cell:
    return dict_cell[word]
else:
    return 0

for words in keywords:
  df[words] = df['word_count'].apply(lambda x:word_counter(x,words))

Answer 5

def count_words(x, w):
    if w in x:
        return x.count(w)
    else:
        return 0   

selected_words = ['awesome', 'great', 'fantastic', 'amazing', 'love', 'horrible', 'bad', 'terrible', 'awful', 'wow', 'hate']

for words in selected_words:
    products[words]=products['review'].apply(lambda x:count_words(x,words))