TypeError: Image data cannot be converted to float,where my code is going wrong? - word-cloud

Question

def calculate_frequencies(file_contents):
# Here is a list of punctuations and uninteresting words you can use to process your text
punctuations = '''!()-[]{};:'"\,<>./?##$%^&*_~'''
uninteresting_words = ["the", "a", "to", "if", "is", "it", "of", "and", "or", "an", "as", "i", "me", "my", \
"we", "our", "ours", "you", "your", "yours", "he", "she", "him", "his", "her", "hers", "its", "they", "them", \
"their", "what", "which", "who", "whom", "this", "that", "am", "are", "was", "were", "be", "been", "being", \
"have", "has", "had", "do", "does", "did", "but", "at", "by", "with", "from", "here", "when", "where", "how", \
"all", "any", "both", "each", "few", "more", "some", "such", "no", "nor", "too", "very", "can", "will", "just"]
# LEARNER CODE START HERE
dict1=[]
d ={}
for words in file_contents.split():
if words.isalpha() and words.lower() not in uninteresting_words:
dict1.append(words.lower())
for words in dict1:
if words not in d:
d[words] =0
d[words]+=file_contents.split().count(words)
return d
#wordcloud
cloud = WordCloud(width=900,height=500, max_words=1628,relative_scaling=1,normalize_plurals=False)
cloud.generate_from_frequencies(calculate_frequencies)
return cloud.to_array()`enter code here`)

Answer 1

# LEARNER CODE START HERE
words = file_contents.split(" ")
words_list = []
frequency={}
file_contents=file_contents.split()
for word in words:
for uninteresting_word in uninteresting_words:
if word is not uninteresting_word:
words_list.append(word)
for word in words_list:
if not word.isalpha():
word =''.join([letter for letter in word if word.isalpha()])
words_dict = {}
for word in words_list:
if word not in words_dict.keys():
words_dict[word] = words_list.count(word)
#wordcloud
cloud = wordcloud.WordCloud()
cloud.generate_from_frequencies(words_dict)
return cloud.to_array()

Answer 2

here is a shorter answer
LEARNER CODE START HERE
for s in file_contents:
if s in punctuations:
file_contents = file_contents.replace(s, "")
files = file_contents.lower().split()
result = {}
for word in files:
if word.isalpha() == True and word not in uninteresting_words:
if word in result:
result[word] += 1
else:
result[word] = 1
#wordcloud
cloud = wordcloud.WordCloud()
cloud.generate_from_frequencies(result)
return cloud.to_array()