def create_word_cloud():
""" create the cloud of word with wordcloud_fa module"""
# mask.jpg is a image in black and white picture that word will write in that
mask_array = np.array(Image.open("mask.jpg"))
wc = WordCloudFa(persian_normalize=True,
include_numbers=False,
mask=mask_array,
background_color="white",
collocations=False)
with open('telegramtxt.txt', 'r') as file:
text = file.read()
frequencies = wc.process_text(text)
avr = 0
count = 0
frequencies = {k: v for k, v in frequencies.items() if v > 1}
for k, v in frequencies.items():
count += 1
avr += v
avr = avr // count
print(f'avr of word count : {avr}')
frequencies = {k: v for k, v in frequencies.items() if v > avr}
frequencies = {
k: v
for k, v in sorted(
frequencies.items(), key=lambda item: item[1], reverse=True)
}
word_cloud = wc.generate_from_frequencies(frequencies)
image = word_cloud.to_image()
image.save('cloud.png')
text = text.translate(str.maketrans(' ', ' ', "\n"))
word_list = WordTokenizer().tokenize(text)
stop_words = stopwords.words('english')
punctuations = list(string.punctuation)
words = [
word.strip() for word in word_list if word not in stop_words
and word not in stop_words_main and word not in punctuations
]
text = ""
for x in words:
text += x + " "
# alice = np.array(Image.open("mask.png"))
word_cloud = WordCloudFa(persian_normalize=True,
width=2000,
height=2000,
margin=20,
repeat=False,
max_words=500)
frequencies = word_cloud.process_text(text)
wc = word_cloud.generate_from_frequencies(frequencies)
fig = plt.figure(figsize=(20, 20), facecolor=None)
plt.figure()
plt.imshow(word_cloud)
plt.axis('off')
plt.savefig('WordsCloud.png', dpi=2000, transparent=True)
plt.show()
words = remove_punctuations(words)
words = re.sub(
'http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\(\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))',
'',
words,
flags=re.MULTILINE)
words = re.sub(r"@(\w+)", ' ', words, flags=re.MULTILINE)
wordcloud = WordCloudFa(persian_normalize=True,
stopwords=list(STOPWORDS) +
hazm.stopwords_list(),
include_numbers=False,
background_color='white',
width=700,
height=500)
frequencies = wordcloud.process_text(words)
wc = wordcloud.generate_from_frequencies(frequencies)
image = wc.to_image()
st.image(image)
# Dataframe
st.subheader('**Data**')
st.write(data)
# Random Tweet
col1, col2 = st.beta_columns(2)
with col1:
st.markdown('')
st.markdown('')
random_tweet = st.button('Show another random tweet')
with col2:
st.markdown('')