with open(os.path.join(directory, myFile), 'r') as f:
# Here, the JSON is converted back to a Python object
transcript = json.load(f)
transcripts.append(transcript)
# Create lists for the years and the length of the text for each year.
years = []
lengths = []
# Go through each transcript
for transcript in transcripts:
# Get the date - converting the ISO date back into a datetime.date object
date = cf.iso_to_datetime(transcript['date'])
# Convert the year into a campaign year
year = cf.campaign_year_from_year(date.year)
years.append(year)
# Create a string for all of the text in the debate
allText = ""
# Add all the text spoken by speakers to that string
for speaker in transcript['text_by_speakers']:
allText += (" " + speaker['text'])
# removes punctuation, digits, splits text into words
# remove words shorter than 3 characters and suffixes
for p in list(punctuation):
total_pos_words = len(
[True for x in long_words if x in positive_words])
total_neg_words = len(
[True for x in long_words if x in negative_words])
print total_pos_words, total_neg_words, word_count, year
transcript_results.append(
dict(total_pos_words=total_pos_words,
total_neg_words=total_neg_words,
word_count=word_count,
year=year))
# Get a unique list of the years
uniqueYears = list(
set([
cf.campaign_year_from_year(transcript_result['year'])
for transcript_result in transcript_results
]))
uniqueYears.sort()
print uniqueYears
year_results = []
# For each unique year
for uniqueYear in uniqueYears:
transcript_results_for_year = [
transcript_result for transcript_result in transcript_results if
cf.campaign_year_from_year(transcript_result['year']) == uniqueYear
]
word_count = sum([
uniqueYears = list(set(years))
# Create a new list for the simplicity corresponding to each year.
uniquesimplewords = []
# For each unique year
for uniqueYear in uniqueYears:
# Create a list which will contain all simplicity values for a year
simplewordsforyear = []
nounsforyear = []
# Go through all the different years, adding the simplicity to that list and dividing
# it over the total number of nouns.
for number in range(len(years)):
if cf.campaign_year_from_year(years[number]) == uniqueYear:
simplewordsforyear.append(simplicity[number])
nounsforyear.append(noun_numbers[number])
# Take a simple mean of the simplicity of all texts in a given year.
# Add this to the list uniquesimplewords, which is paired with the uniqueYears list.
if sum(nounsforyear):
uniquesimplewords.append(
sum(simplewordsforyear) / sum(nounsforyear))
results.append({
'party':
party,
'data': [[year for year in uniqueYears if not year % 4],
uniquesimplewords]
})