def get_langs(word):
"""
returns a list of the 3 most probable languages. the last two elements might be None
TextBlob return 1 language. langdetect return a list of languages.
if TextBlob == langdetect[0]
languages = langdetect[0:3]
else:
languages = TextBlob + langdetect[0:2]
"""
if (len(word) < 3):
return [None for i in range(3)]
first_lang = TextBlob(word).detect_language().__str__()
langs = [w.lang.__str__() for w in detect_langs(word)]
if (first_lang != langs[0]):
langs.insert(0, first_lang.__str__())
# pad list if there are less than 3 elems
while (len(langs) < 4):
langs.append(None)
# remove last elements there are more than 3 elems
while (len(langs) > 3):
langs = langs[:-1]
return langs
def jaccard_calc(csv_file):
'''Takes in a a table and Returns another with a column of jaccard_values for each team'''
table = pd.read_csv(csv_file)
#Cleaning, lemmatizing, then grouping responses by team into lists of wordlists.
cleaned_table = cleaning_and_lemmatizing(table)
summed_table = cleaned_table.groupby('Teamname')[['Shared Goal']].sum()
summed_table['Shared Goal'] = cleaned_table.groupby('Teamname')['Shared Goal'].apply(list)
table_with_values = summed_table
#Jaccard Calculation
jaccard_value = np.array([])
for responses in table_with_values['Shared Goal']:
response_length = 0
numerator = 0
past_responses = TextBlob('').words
for response in responses:
past_responses += remove_dupes(response)
response_length += len(response)
past_word_freq = TextBlob(past_responses.__str__()).word_counts
for word in list(past_word_freq):
if past_word_freq[word] > 1:
numerator += past_word_freq[word] - 1
jaccard_value = np.append(jaccard_value, numerator / response_length)
table_with_values['jaccard value'] = jaccard_value
return table_with_values
def get_sentiment(text, language="en", extended=True):
logging.debug({'text': text, 'lang': language, 'ext': extended})
tmp = TextBlob(text)
if language != "en":
logging.warn('Message in '+language+' language. Need to be translated')
tmp = tmp.translate(to='en')
logging.debug('Translated: '+tmp.__str__())
if extended:
logging.debug('Extended message reques')
return __get_extended_analysis(text, language, tmp)
else:
logging.debug('Simple message request')
return {'polarity': tmp.sentiment.polarity, 'subjectivity': tmp.sentiment.subjectivity, 'tag': polarity_tag(tmp.sentiment.polarity)}
