word_cloud.py

from wordcloud import WordCloud, STOPWORDS

print ('Wordcloud imported!')

import urllib

# # open the file and read it into a variable alice_novel
alice_novel = urllib.request.urlopen('https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DV0101EN-SkillsNetwork/Data%20Files/alice_novel.txt').read().decode("utf-8")

stopwords = set(STOPWORDS)
# instantiate a word cloud object
alice_wc = WordCloud()

# generate the word cloud
alice_wc.generate(alice_novel)

# display the word cloud
plt.imshow(alice_wc, interpolation='bilinear')
plt.axis('off')
plt.show()



#save mask to alice_mask
alice_mask = np.array(Image.open(urllib.request.urlopen('https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DV0101EN-SkillsNetwork/labs/Module%204/images/alice_mask.png')))
fig = plt.figure(figsize=(14, 18))

plt.imshow(alice_mask, cmap=plt.cm.gray, interpolation='bilinear')
plt.axis('off')
plt.show()


# instantiate a word cloud object
alice_wc = WordCloud(background_color='white', max_words=2000, mask=alice_mask, stopwords=stopwords)

# generate the word cloud
alice_wc.generate(alice_novel)

# display the word cloud
fig = plt.figure(figsize=(14, 18))

plt.imshow(alice_wc, interpolation='bilinear')
plt.axis('off')
plt.show()




#from data frame

total_immigration


max_words = 90
word_string = ''
for country in df_can.index.values:
     # check if country's name is a single-word name
    if country.count(" ") == 0:
        repeat_num_times = int(df_can.loc[country, 'Total'] / total_immigration * max_words)
        word_string = word_string + ((country + ' ') * repeat_num_times)

# display the generated text
word_string