def make_worldcloud(file_path): #对应的文件编码
text_from_file_with_apath = open(file_path, 'r', encoding='UTF-8').read()
wordlist_after_jieba = jieba.cut(text_from_file_with_apath, cut_all=False)
wl_space_split = " ".join(wordlist_after_jieba)
print(wl_space_split)
backgroud_Image = plt.imread('D:/下载/123.jpg') #图片路径
print('加载图片成功')
'''设置词云样式'''
stopwords = STOPWORDS.copy()
stopwords.add("如果") #屏蔽词，可以多个
wc = WordCloud(
width=1024,
height=768,
background_color='white', #背景色
mask=backgroud_Image,
font_path='D:/下载/simsun.ttc', #字体文件
max_font_size=400,
random_state=50,
)
wc.generate_from_text(wl_space_split) #开始加载文字
img_colors = ImageColorGenerator(backgroud_Image)
wc.recolor(color_func=img_colors) #字体颜色为背景图片的颜色
plt.imshow(wc) #显示云词图
plt.axis('off') #是否显示X轴，Y轴下标
plt.show() #显示
#获取模块所在的路径
d = path.dirname(__file__)
# os.path.join(): 将多个路径组合后返回
#print(d)
wc.to_file(path.join(d, "h11.jpg")) #生成图片名称
print('生成云词成功')
def parse_comment():
comments = []
with open(file_name, 'r', encoding='utf-8') as f:
lines = f.readlines()
try:
for line in lines:
comment = line.split(',')[2]
if comment:
comments.append(comment)
except Exception as e:
print(e)
comment_after_split = jieba.cut(str(comments), cut_all=False)
words = ''.join(comment_after_split)
#多虑没用的停止词
stopwords = STOPWORDS.copy()
stopwords.add('电影')
stopwords.add('一部')
stopwords.add('一个')
stopwords.add('没有')
stopwords.add('什么')
stopwords.add('有点')
stopwords.add('感觉')
stopwords.add('毒液')
stopwords.add('就是')
stopwords.add('觉得')
bg_image = plt.imread('venmo1.jpg')
wc = WordCloud(width=1024, height=768, background_color='white', mask=bg_image, font_path='STKAITI.TTF',
stopwords=stopwords, max_font_size=400, random_state=50)
wc.generate_from_text(words)
plt.imshow(wc)
plt.axis('off')
plt.show()
def create_word_cloud_b64(word_list):
random.shuffle(word_list)
words = " ".join(word_list)
stopwords = STOPWORDS.copy()
stopwords.add("http")
stopwords.add("https")
stopwords.add("localstorage")
stopwords.add("com_0")
stopwords.add("new")
stopwords.add("http_www")
stopwords.add("sourceid")
try:
wordcloud = WordCloud(stopwords=stopwords,
max_words=150,
background_color="white",
height=700,
width=1200,
margin=0,
regexp=r"\w[\w'@\.]+").generate(words)
plt.axis("off")
plt.imshow(
wordcloud) # this must be here, or the wc image is blank
wordcloud_bytes = cStringIO.StringIO()
plt.savefig(wordcloud_bytes, bbox_inches='tight', format='jpg')
wordcloud_bytes.seek(0)
wordcloud_b64 = base64.b64encode(wordcloud_bytes.read())
return wordcloud_b64
except Exception as e:
logging.error("Problem making word cloud: {}".format(e))
return False
def word_cloud(csv_file, stopwords_path, pic_path):
pic_name = csv_file+"_词云图.png"
path = os.path.abspath(os.curdir)
csv_file = path+ "\\" + csv_file + ".csv"
csv_file = csv_file.replace('\\', '\\\\')
d = pd.read_csv(csv_file, engine='python', encoding='utf-8')
content = []
for i in d['content']:
try:
i = translate(i)
except AttributeError as e:
continue
else:
content.append(i)
comment_after_split = jieba.cut(str(content), cut_all=False)
wl_space_split = " ".join(comment_after_split)
backgroud_Image = plt.imread(pic_path)
stopwords = STOPWORDS.copy()
with open(stopwords_path, 'r', encoding='utf-8') as f:
for i in f.readlines():
stopwords.add(i.strip('\n'))
f.close()
wc = WordCloud(width=1024, height=768, background_color='white',
mask=backgroud_Image, font_path="C:\simhei.ttf",
stopwords=stopwords, max_font_size=400,
random_state=50)
wc.generate_from_text(wl_space_split)
img_colors = ImageColorGenerator(backgroud_Image)
wc.recolor(color_func=img_colors)
plt.imshow(wc)
plt.axis('off')
plt.show()
wc.to_file(pic_name)
def generate_word_cloud(data):
# 设置分词
signatures = jieba.cut(str(data))
words = ' '.join(signatures)
print('签名：',words)
# 设置屏蔽词
stopwords = STOPWORDS.copy()
stopwords.add("span")
stopwords.add("class")
stopwords.add("emoji")
stopwords.add("emoji2764")
# 导入背景图片
bg_img = plt.imread('love.jpg')
# 设置词云参数
wc = WordCloud(width=1024, height=768, background_color='white', mask=bg_img, stopwords=stopwords,
max_font_size=400, random_state=50, font_path='STKAITI.TTF')
# 将分词后的数据导入词图
wc.generate_from_text(words)
# 绘制图像
plt.imshow(wc)
plt.axis('off')
plt.show()
wc.to_file('词云图.jpg')
def wordCl(strs):
stopwords = STOPWORDS.copy()
# stopwords.add('感觉')
# stopwords.add('第一集')
# stopwords.add('已经')
# stopwords.add('为什么')
# stopwords.add('啊啊啊')
# stopwords.add('不要')
# stopwords.add('没有')
# stopwords.add('？')
# stopwords.add('觉得')
# stopwords.add('时候')
# stopwords.add('开始')
# stopwords.add('一下')
# stopwords.add('自己')
# stopwords.add('就是')
# stopwords.add('还有')
# stopwords.add('但是')
# stopwords.add('怎么')
# stopwords.add('不要')
word_list = [" ".join(jieba.cut(strs))]
new_text = ' '.join(word_list)
imagename = path.join(path.dirname(__file__), BACKGROUNDIMG) # 背景图片路径
coloring = imread(imagename) # 读取背景图片
#fontname=path.join(path.dirname(__file__), "msyh.ttf") # 使用的是微软雅黑字体
wordcloud = WordCloud(stopwords=stopwords,
min_font_size=10,
mask=coloring,
font_path="msyh.ttf",
scale=24,
background_color='white').generate(new_text)
plt.imshow(wordcloud)
plt.axis("off")
plt.show()
def create_wordcloud(self, text):
"""生成词云"""
# 对图片做处理
maskPic = np.array(Image.open(IMAGE_PATH))
# 停用词
stopwords = STOPWORDS.copy()
words = ["其次", "不錯看", "其实"]
list(map(stopwords.add, words))
wordcloud = WordCloud(
font_path=TTF_PATH, # 字体路径（中文字需要添加）
width=500,
height=400,
stopwords=stopwords,
max_font_size=100,
random_state=30,
min_font_size=10,
background_color="white").generate(text.replace("\n", ""))
# 改变字体颜色
img_colors = ImageColorGenerator(maskPic)
# 字体颜色为背景图片的颜色
wordcloud.recolor(color_func=img_colors)
# 生成图片并保存
img = wordcloud.to_image()
img.save(SAVE_IMAGE_PATH)
print("词云图【成功】")
def main(save_files = False, db_filename = '../output/database.sqlite'):
conn = sqlite3.connect(db_filename)
c = conn.cursor()
# Retrieve papers
c.execute('''SELECT *
FROM Papers''')
paper_content = c.fetchall()
conn.close()
titles = ''
for pc in paper_content:
titles += pc[1]
# A Marvin Minsky mask
mask = np.array(Image.open("../files/minsky_mask.png"))
wc = WordCloud(background_color="white", max_words=2000, mask=mask, stopwords=STOPWORDS.copy())
# Generate word cloud
wc.generate(titles)
if (save_files):
# Store to file
wc.to_file("../files/title_cloud.png")
# Show word cloud
plt.imshow(wc)
plt.axis("off")
# Show mask
# plt.figure()
# plt.imshow(mask, cmap=plt.cm.gray)
# plt.axis("off")
plt.show()
def generate_wordcloud():
comments = []
with open('data/comments.txt', 'r', encoding='utf-8') as f:
rows = f.readlines()
try:
for row in rows:
comment = row.split(',')[2]
if comment != '':
comments.append(comment)
except Exception as e:
print(e)
comment_after_split = jieba.cut(str(comments), cut_all=False)
words = ' '.join(comment_after_split)
stopwords = STOPWORDS.copy()
stopwords.add('电影')
stopwords.add('一部')
stopwords.add('一个')
stopwords.add('没有')
stopwords.add('什么')
stopwords.add('有点')
stopwords.add('感觉')
stopwords.add('毒液')
stopwords.add('就是')
stopwords.add('觉得')
bg_image = plt.imread('bg.jpg')
wc = WordCloud(background_color='lightblue',
mask=bg_image,
font_path='STKAITI.TTF',
stopwords=stopwords,
max_font_size=400,
random_state=50)
wc.generate_from_text(words)
plt.imshow(wc)
plt.axis('off')
plt.show()
def hope():
d = path.dirname(__file__)
# read the mask image
# taken from
# http://www.stencilry.org/stencils/movies/star%20wars/storm-trooper.gif
mask = imread(path.join(d, "stormtrooper_mask.png"))
text = open(path.join(d, 'input.txt')).read()
# preprocessing the text a little bit
#text = text.replace("HAN", "Han")
#text = text.replace("LUKE'S", "Luke")
# adding movie script specific stopwords
stopwords = STOPWORDS.copy()
stopwords.add("int")
stopwords.add("ext")
wc = WordCloud(max_words=1000,
mask=mask,
stopwords=stopwords,
margin=10,
random_state=1).generate(text)
# store default colored image
default_colors = wc.to_array()
plt.title("Custom colors")
plt.imshow(wc.recolor(color_func=grey_color_func, random_state=3))
wc.to_file("a_new_hope.png")
plt.axis("off")
plt.figure()
plt.title("Default colors")
plt.imshow(default_colors)
plt.axis("off")
plt.show()
def WorldCloud_pic(text_path, pic_path, font_path):
text = open(text_path, 'r', encoding='UTF-8').read()
word_list = jieba.cut(text, cut_all=False)
wl_space_split = " ".join(word_list)
print(wl_space_split)
backgroud_Image = plt.imread(pic_path)
print('加载图片成功！')
stopwords = STOPWORDS.copy() # 使用词云自带的停词表
stopwords.add("哈哈") # 可以加多个屏蔽词
wc = WordCloud(
width=1024,
height=768,
background_color='white', # 设置背景颜色
mask=backgroud_Image, # 设置背景图片
font_path=font_path, # 设置中文字体，若是有中文的话，这句代码必须添加，不然会出现方框，不出现汉字
max_words=600, # 设置最大现实的字数
stopwords=stopwords, # 设置停用词
max_font_size=400, # 设置字体最大值
random_state=50, # 设置有多少种随机生成状态，即有多少种配色方案
)
wc.generate_from_text(wl_space_split) # 开始加载文本
img_colors = ImageColorGenerator(backgroud_Image)
wc.recolor(color_func=img_colors) # 字体颜色为背景图片的颜色
plt.imshow(wc) # 显示词云图
plt.axis('off') # 是否显示x轴、y轴下标
plt.show() # 显示
d = path.dirname(__file__) # 获得模块所在的路径的
wc.to_file(path.join(d, "词云.jpg"))
print('生成词云成功!')
def SetStopWords(self):
"""
停词设置
"""
stopwords = STOPWORDS.copy()
stopwords.add("电影")
return stopwords
def get_word_cloud(comments):
comments_after_aplit = jieba.cut(str(comments), cut_all=False)
words = ' '.join(comments_after_aplit)
# print(words)
stopwords = STOPWORDS.copy()
stopwords.add('哪吒')
stopwords.add('电影')
stopwords.add('我命')
stopwords.add('不由')
bg_img = plt.imread('circle.png')
wc = WordCloud(width=1024,
height=768,
background_color='white',
mask=bg_img,
stopwords=stopwords,
max_font_size=200,
random_state=50,
font_path='STKAITI.TTF')
wc.generate_from_text(words)
plt.imshow(wc)
plt.axis('off')
plt.show()
wc.to_file('词云图.jpg')
def wcplot(text, n):
data_dir = 'data2'
pwd = os.getcwd()
#file_names = os.listdir(os.path.join(pwd, data_dir))
file_ = img_dict[n]
file_dir = os.path.join(pwd, data_dir, file_)
mask = imread(file_dir, mode= 'L')
stopwords = STOPWORDS.copy()
stopwords.add("int")
stopwords.add("ext")
wc = WordCloud(background_color="white", max_words=200,mask=mask,stopwords=stopwords,
random_state=3,font_path=font_path).generate(text)
wc.recolor(color_func=color_func, random_state=3)
plt.figure(figsize=(10,10),facecolor='k')
plt.imshow(wc)
#title = ("top words for topic %d") % n
#plt.title(title)
pic_name = ('{}.jpg') .format(input_movie.replace('/','_'))
wc.to_file(pic_name)
plt.axis("off")
plt.show()
def word_cloud(csv_file, stopwords_path, pic_path):
pic_name = csv_file[:-4] + "_词云图.png"
d = pd.read_csv(csv_file, engine='python', encoding='utf-8')
content = d['job_desc'].values
comment_after_split = jieba.cut(str(content), cut_all=False)
wl_space_split = " ".join(comment_after_split)
background_image = plt.imread(pic_path)
stopwords = STOPWORDS.copy()
with open(stopwords_path, 'r', encoding='utf-8') as f:
for i in f.readlines():
stopwords.add(i.strip('\n'))
f.close()
wc = WordCloud(width=1024,
height=768,
background_color='white',
mask=background_image,
font_path="simhei.ttf",
stopwords=stopwords,
max_font_size=400,
random_state=50)
wc.generate_from_text(wl_space_split)
img_colors = ImageColorGenerator(background_image)
wc.recolor(color_func=img_colors)
plt.imshow(wc)
plt.axis('off')
plt.show()
wc.to_file(pic_name)
def make_cloud(words, image, size=10, filename='figures/cloud.png', max_words=200, horizontal=0.8):
# Remove URLs, 'RT' text, screen names, etc
my_stopwords = ['RT', 'amp', 'lt']
words_no_urls = ' '.join([word for word in words.split()
if word not in my_stopwords])
# Add stopwords, if needed
stopwords = STOPWORDS.copy()
stopwords.add("RT")
stopwords.add('amp')
stopwords.add('lt')
# Load up a logo as a mask & color image
logo = imread(image)
# Generate colors
image_colors = ImageColorGenerator(logo)
# Generate plot
wc = WordCloud(stopwords=stopwords, mask=logo, color_func=image_colors, scale=0.8,
max_words=max_words, background_color='white', random_state=42, prefer_horizontal=horizontal)
wc.generate(words_no_urls)
plt.figure(figsize=(size, size))
plt.imshow(wc)
plt.axis("off")
plt.savefig(filename)
def word_cloud(csv_file, stopwords_path, pic_path):
pic_name = csv_file+"_词云图.png"
path = os.path.abspath(os.curdir)
csv_file = path+ "\\" + csv_file + ".csv"
csv_file = csv_file.replace('\\', '\\\\')
d = pd.read_csv(csv_file, engine='python', encoding='utf-8')
content = []
for i in d['content']:
try:
i = translate(i)
except AttributeError as e:
continue
else:
content.append(i)
comment_after_split = jieba.cut(str(content), cut_all=False)
wl_space_split = " ".join(comment_after_split)
backgroud_Image = plt.imread(pic_path)
stopwords = STOPWORDS.copy()
with open(stopwords_path, 'r', encoding='utf-8') as f:
for i in f.readlines():
stopwords.add(i.strip('\n'))
f.close()
wc = WordCloud(width=1024, height=768, background_color='white',
mask=backgroud_Image, font_path="C:\simhei.ttf",
stopwords=stopwords, max_font_size=400,
random_state=50)
wc.generate_from_text(wl_space_split)
img_colors = ImageColorGenerator(backgroud_Image)
wc.recolor(color_func=img_colors)
plt.imshow(wc)
plt.axis('off')
plt.show()
wc.to_file(pic_name)
def signatures_cloud():
signatures = []
with open('wechatfriends.txt', mode='r', encoding='utf-8') as f:
rows = f.readlines()
for i in rows:
signature = i.split(',')[5]
if signature != '':
signatures.append(signature)
f.close()
split = jieba.cut(str(signatures), cut_all=False)
words = ' '.join(split)
stopwords = STOPWORDS.copy()
stopwords.add('span')
stopwords.add('span')
stopwords.add('class')
stopwords.add('emoji')
stopwords.add('emoji1f334')
stopwords.add('emoji1f388')
stopwords.add('emoji1f33a')
stopwords.add('emoji1f33c')
stopwords.add('emoji1f633')
bg_image = plt.imread('moon.jpeg')
wc = WordCloud(width=1000,
height=1000,
background_color='white',
mask=bg_image,
font_path='simhei.ttf',
stopwords=stopwords,
max_font_size=400,
random_state=50)
wc.generate_from_text(words)
# plt.imshow(wc)
plt.axis('off')
wc.to_file('个性签名云图.jpg')
def gen_tag_cloud(frequencies, filename):
"""生成标签云"""
d = path.dirname(__file__)
mask = np.array(Image.open(path.join(d, "view.jpg")))
stopwords = STOPWORDS.copy()
wc = WordCloud(background_color="white",
max_words=2000,
mask=mask,
stopwords=stopwords,
margin=10,
random_state=42,
font_path="msyh.ttf",
width=1280,
height=1024).fit_words(frequencies)
image_colors = ImageColorGenerator(mask)
plt.imshow(wc)
plt.axis("off")
plt.figure()
wc.to_file(filename + "_tag_cloud_default.png")
plt.imshow(wc.recolor(color_func=image_colors))
plt.axis("off")
plt.figure()
wc.to_file(filename + "_tag_cloud_colored.png")
def generate_wordcloud():
comments = []
with open('maoyan.csv', mode='r', encoding='utf-8') as f:
rows = f.readlines()
for row in rows:
comment = row.split(':')[0]
if comment != '':
comments.append(comment)
comment_after_split = jieba.cut(str(comments), cut_all=False)
words = ''.join(comment_after_split)
print(words)
stopwords = STOPWORDS.copy()
stopwords.add('电影')
stopwords.add('一出')
stopwords.add('好戏')
stopwords.add('有点')
bg_image = plt.imread('123.jpg')
wc = WordCloud(width=1024,
height=768,
background_color='white',
mask=bg_image,
stopwords=stopwords,
max_font_size=400,
random_state=50,
font_path='STKAITI.TTF')
wc.generate_from_text(words)
wc.to_file('output/词云图.jpg')
plt.imshow(wc)
plt.axis('off')
plt.show()
def make_worldcloud(file_path):
text_from_file_with_apath = open(file_path, 'r', encoding='UTF-8').read()
wordlist_after_jieba = jieba.cut(text_from_file_with_apath, cut_all=False)
wl_space_split = " ".join(wordlist_after_jieba)
print(wl_space_split)
backgroud_Image = plt.imread('./douban.jpg')
print('加载图片成功！')
'''设置词云样式'''
stopwords = STOPWORDS.copy()
stopwords.add("哈哈")
stopwords.add("还是") #可以加多个屏蔽词
wc = WordCloud(
width=1024,
height=768,
background_color='white', # 设置背景颜色
mask=backgroud_Image, # 设置背景图片
font_path='E:\simsun.ttf', # 设置中文字体，若是有中文的话，这句代码必须添加，不然会出现方框，不出现汉字
max_words=300, # 设置最大现实的字数
stopwords=stopwords, # 设置停用词
max_font_size=400, # 设置字体最大值
random_state=50, # 设置有多少种随机生成状态，即有多少种配色方案
)
wc.generate_from_text(wl_space_split) #开始加载文本
img_colors = ImageColorGenerator(backgroud_Image)
wc.recolor(color_func=img_colors) #字体颜色为背景图片的颜色
plt.imshow(wc) # 显示词云图
plt.axis('off') # 是否显示x轴、y轴下标
plt.show() #显示
# 获得模块所在的路径的
d = path.dirname(__file__)
# os.path.join()： 将多个路径组合后返回
wc.to_file(path.join(d, "h11.jpg"))
print('生成词云成功!')
def ciyun(filepath):
comment = []
with open(filepath, 'r') as f:
rows = f.readlines()
for row in rows:
if len(row.split(';')) == 5:
comment.append(row.split(';')[4].replace('\n', ''))
comment2 = json.dumps(comment, ensure_ascii=False) # 转码显示中文
print("comment2", comment2)
comment_after_split = jieba.cut(str(comment2), cut_all=False)
# 查看分词效果
wl_space_split = " ".join(comment_after_split)
print("wl_space_split", wl_space_split)
# 以上都运行无误
# 导入背景图
backgroud_Image = plt.imread('1.jpg') # 读取图片数据
stopwords = STOPWORDS.copy()
# 可以加多个屏蔽词
stopwords.add("剧情")
stopwords.add("一部")
stopwords.add("一个")
stopwords.add("没有")
stopwords.add("什么")
stopwords.add("有点")
stopwords.add("这部")
stopwords.add("这个")
stopwords.add("不是")
stopwords.add("真的")
stopwords.add("感觉")
stopwords.add("觉得")
stopwords.add("还是")
stopwords.add("女主")
stopwords.add("皇后")
stopwords.add("贵妃")
stopwords.add("于妈")
stopwords.add("就是")
stopwords.add("可以")
# 设置词云参数
# 参数分别是指定字体、背景颜色、最大的词的大小、使用给定图作为背景形状
wc = WordCloud(background_color='white',
mask=backgroud_Image,
font_path='DroidSansFallback.ttf',
stopwords=stopwords,
max_font_size=400,
random_state=50)
wc.generate_from_text(wl_space_split)
img_colors = ImageColorGenerator(backgroud_Image)
wc.recolor(color_func=img_colors)
# 保存结果到本地
if filepath == 'yanxi.txt':
wc.to_file('yanxi_wordcloud.jpg')
def ciyun(data):
comment = jieba.cut(str(data['comments']), cut_all=False) #分词
wl_space_split = " ".join(comment)
backgroud_Image = plt.imread('shenteng.jpg') #添加背景
stopwords = STOPWORDS.copy()
print(" STOPWORDS.copy()", help(STOPWORDS.copy()))
# 可以自行加多个屏蔽词，也可直接下载停用词表格
stopwords.add("电影")
stopwords.add("一部")
stopwords.add("一个")
stopwords.add("没有")
stopwords.add("什么")
stopwords.add("有点")
stopwords.add("这部")
stopwords.add("这个")
stopwords.add("不是")
stopwords.add("真的")
stopwords.add("感觉")
stopwords.add("觉得")
stopwords.add("还是")
stopwords.add("特别")
stopwords.add("非常")
stopwords.add("可以")
stopwords.add("因为")
stopwords.add("为了")
stopwords.add("比较")
#print(stopwords)
# 设置词云参数
# 参数分别是指定字体/背景颜色/最大的词的大小,使用给定图作为背景形状
wc = WordCloud(width=1024,
height=768,
background_color='white',
mask=backgroud_Image,
font_path='C:\Windows\Fonts\simhei.ttf',
stopwords=stopwords,
max_font_size=400,
random_state=50)
print(wl_space_split)
wc.generate_from_text(str(wl_space_split))
plt.imshow(wc)
plt.axis('off')
plt.show()
wc.to_file(r'shenteng_wordcloud.jpg')
def makeWordCloud(text):
#preprocess
stopwords = STOPWORDS.copy()
# text.replace("State","")
# text.replace("year","")
# text.replace("Congress","")
# text.replace("will","")
wC = WordCloud(max_words=2000, stopwords=stopwords, margin=5, random_state=1, width = 1600, height = 800).generate(text)
plt.imshow(wC)
plt.show()
def cloud(self):
# 设置分词
comments = self.getComments()
print(str(comments))
comment_after_split = jieba.cut(str(comments),
cut_all=False) # 非全模式分词，cut_all=false
words = " ".join(comment_after_split) # 以空格进行拼接
print(type(words))
print(''.join(words))
# print(words)
# 设置屏蔽词
stopwords = STOPWORDS.copy()
stopwords.add("电影")
stopwords.add("一部")
stopwords.add("一个")
stopwords.add("没有")
stopwords.add("什么")
stopwords.add("有点")
stopwords.add("这部")
stopwords.add("这个")
stopwords.add("不是")
stopwords.add("真的")
stopwords.add("感觉")
stopwords.add("觉得")
stopwords.add("还是")
stopwords.add("但是")
stopwords.add("就是")
stopwords.add("他们")
stopwords.add("可能")
stopwords.add("应该")
stopwords.add("怎么")
stopwords.add("大家")
# 导入背景图
bg_image = plt.imread('g.jpg')
# font = '/System/Library/Assets/com_apple_MobileAsset_Font5/6bb29eea6a5b99f3100a5e3f862e6457103557de.asset/AssetData/Hannotate.ttc'
font = '/System/Library/Assets/com_apple_MobileAsset_Font5/4cecce0dd640f147de4d0e4155a97d3cdf47971e.asset/AssetData/Xingkai.ttc'
# 设置词云参数，参数分别表示：画布宽高、背景颜色、背景图形状、字体、屏蔽词、最大词的字体大小
wc = WordCloud(width=1024,
height=768,
background_color='white',
mask=bg_image,
font_path=font,
stopwords=stopwords,
max_font_size=400,
random_state=50)
# 将分词后数据传入云图
wc.generate_from_text(words)
plt.imshow(wc)
plt.axis('off') # 不显示坐标轴
plt.show()
# 保存结果到本地
wc.to_file('myecharts/词云图.jpg')
def draw_cloud(comments):
data = comments['content']
comment_data = []
print("由于数据量比较大，分词这里稍微有点慢，请耐心等候")
for item in data:
if pd.isnull(item) == False:
comment_data.append(item)
comment_after_split = jieba.cut(str(comment_data), cut_all=False)
words = ' '.join(comment_after_split)
# 自定义停用词
stopwords = STOPWORDS.copy()
stopwords.add('复仇者联盟')
stopwords.add('复联')
stopwords.add('联盟')
stopwords.add('复仇')
stopwords.add('电影')
stopwords.add('一部')
stopwords.add('一个')
stopwords.add('没有')
stopwords.add('什么')
stopwords.add('有点')
stopwords.add('感觉')
stopwords.add('就是')
stopwords.add('觉得')
stopwords.add('但是')
stopwords.add('自己')
stopwords.add('我们')
stopwords.add('真的')
stopwords.add('可以')
stopwords.add('非常')
stopwords.add('还是')
stopwords.add('还有')
stopwords.add('这部')
# 这里的字体路径请根据自己电脑的实际情况设置'simfang.ttf'
fortpath = './SourceHanSansCN-Normal-2.otf'
wc = WordCloud(width=1000,
height=700,
background_color='#000000',
font_path=fortpath,
scale=5,
stopwords=stopwords,
max_font_size=200)
wc.generate_from_text(words)
plt.figure(figsize=(10, 8))
plt.imshow(wc)
plt.axis('off')
plt.savefig('./WordCloud.png')
plt.show()
def ciyun(filepath):
comment = []
with open(filepath, 'r') as f:
rows = f.readlines()
for row in rows:
if len(row.split(',')) == 5:
comment.append(row.split(',')[4].replace('\n', ''))
comment2 = json.dumps(comment, ensure_ascii=False) #转码显示中文
print "comment2", comment2
comment_after_split = jieba.cut(str(comment2), cut_all=False)
wl_space_split = " ".join(comment_after_split)
print "wl_space_split", wl_space_split
#导入背景图
backgroud_Image = plt.imread('1.jpg')
stopwords = STOPWORDS.copy()
#可以加多个屏蔽词
stopwords.add("电影")
stopwords.add("一部")
stopwords.add("一个")
stopwords.add("没有")
stopwords.add("什么")
stopwords.add("有点")
stopwords.add("这部")
stopwords.add("这个")
stopwords.add("不是")
stopwords.add("真的")
stopwords.add("感觉")
stopwords.add("觉得")
stopwords.add("还是")
#设置词云参数
#参数分别是指定字体、背景颜色、最大的词的大小、使用给定图作为背景形状
wc = WordCloud(width=1024,
height=768,
background_color='white',
mask=backgroud_Image,
font_path='DroidSansFallbackFull.ttf',
stopwords=stopwords,
max_font_size=400,
random_state=50)
wc.generate_from_text(wl_space_split)
img_colors = ImageColorGenerator(backgroud_Image)
wc.recolor(color_func=img_colors)
#plt.imshow(wc)
#plt.axis('off')#不显示坐标轴
#plt.show()
#保存结果到本地
if filepath == 'xie_zheng.txt':
wc.to_file('xie_zheng_ciyun.jpg')
elif filepath == 'yaoshen.txt':
wc.to_file('yaoshen_ciyun.jpg')
def plotTwiiterWordCloud():
args = sys.argv
tracefile = open(args[2], 'r')
nLines = sum(1 for line in tracefile)
tracefile.seek(0)
dictTerms = dict()
blacklist = STOPWORDS.copy()
blacklist.add('rt')
punctuation = set(string.punctuation)
punctuation.remove('@')
punctuation.remove('&')
# punctuation.remove('#')
for line in tqdm(tracefile, total=nLines):
try:
linesplited = line.split(', ')
tweet = linesplited[6].lower()
for p in punctuation:
tweet = tweet.replace(p, '')
terms = tweet.split(' ')
for t in terms:
if (len(t) > 1) and 'http' not in t and (t not in blacklist):
try:
dictTerms[t] += 1
except KeyError:
dictTerms[t] = 1
except IndexError:
print 'IndexError'
for t in blacklist:
try:
del dictTerms[t]
except KeyError:
continue
popularTerms = sorted(dictTerms.keys(), key=lambda w:dictTerms[w], reverse=True)
popularTerms = [p for p in popularTerms if (dictTerms[p]) > 1]
print len(popularTerms)
text = list()
terms = ''
for p in popularTerms:
text.append((p, dictTerms[p]))
for i in range(dictTerms[p]):
terms += ' ' + p
# print terms
maskfile = 'csgo-icon'
mask = imread(maskfile + '.jpg') # mask=mask
wc = WordCloud(mask=mask, background_color='white', width=1280, height=720).generate(terms) # max_words=10000
default_colors = wc.to_array()
plt.figure()
plt.imshow(default_colors)
plt.axis('off')
plt.savefig(maskfile + '-wordcloud.png', dpi=500, bbox_inches='tight', pad_inches=0) # bbox_inches='tight'
plt.show()
def makeCloud(text, imgFile, words):
"""
Makes a word cloud and stores it in a jpeg file
"""
excludewords = STOPWORDS.copy()
for word in words:
excludewords.add(word)
wordcloud = WordCloud(max_words=NUM_OF_WORDS, width=WIDTH, height=HEIGHT, stopwords=excludewords).generate(text)
image = wordcloud.to_image()
image.show()
image.save(imgFile + '.jpeg')
def get_stop_words(self):
stopwords = STOPWORDS.copy()
# 添加屏蔽词
stopwords.add(self.movie.movie_name)
with open('stopword.txt', 'r', encoding='utf_8_sig', newline='') as f:
for line in f.readlines():
if '\r\n' in line:
stopwords.add(line[:len(line) - 2:])
else:
stopwords.add(line)
# print(stopwords)
return stopwords
def paint_word_cloud():
comments = []
with open('./dataSource.txt', 'r', encoding='utf-8') as f:
rows = f.readlines()
try:
for row in rows:
comment = row.split(':')[2]
if comment != '':
comments.append(comment)
print(comments)
except Exception as e:
print(e)
comment_after_split = jieba.cut(str(comments), cut_all=False)
words = ' '.join(comment_after_split)
print(words)
# 多虑没用的停止词
stopwords = STOPWORDS.copy()
stopwords.add('电影')
stopwords.add('一部')
stopwords.add('一个')
stopwords.add('没有')
stopwords.add('什么')
stopwords.add('有点')
stopwords.add('感觉')
stopwords.add('海王')
stopwords.add('就是')
stopwords.add('觉得')
stopwords.add('但是')
bg_image = plt.imread('./cloudBack.jpg')
print('load image success')
print(words)
wc = WordCloud(
# 画布的宽度和高度，如果设置mask不生效
#width=1024, height=768,
# 背景色
background_color='white',
# 词云形状
mask=bg_image,
# 字体路径，若有中文，必须添加这句代码，否则中文变方框
font_path='/Users/lichuang.lc/Desktop/python/out/STZHONGS.TTF',
# 设置停用时间
stopwords=stopwords,
# 最大字号，如果不指定则为图像高度
max_font_size=400,
#有多少种配色方案
random_state=50)
wc.generate_from_text(words)
wc.to_file('./man.jpg')
plt.imshow(wc)
plt.axis('off')
plt.show()
def writeFreq(text, outFile, words):
"""
Writes frequencies of words into the specified file
"""
excludewords = STOPWORDS.copy()
for word in words:
excludewords.add(word)
wordcloud = WordCloud(max_words=NUM_OF_WORDS, stopwords=excludewords)
freqList = wordcloud.process_text(text)
for item in freqList:
outFile.write(item[0] + ',' + str(item[1]) + '\n')
def main():
d = os.path.dirname(__file__)
DOC_NAME = "cvpr2015papers.txt"
text = open(os.path.join(d, DOC_NAME)).read()
# adding computer vision specific stopwords
stopwords = STOPWORDS.copy()
stopwords.add("image")
wc = WordCloud(max_words=300, stopwords=stopwords, width=800, height=400)
wc.generate(text)
wc.to_file(os.path.join(d, "cvpr2015wordcloud.png"))
plt.imshow(wc)
plt.axis("off")
plt.show()
def main():
d = os.path.dirname(__file__)
DOC_NAME = "cvpr2015papers.txt"
text = open(os.path.join(d, DOC_NAME)).read()
# adding computer vision specific stopwords
stopwords = STOPWORDS.copy()
stopwords.add("image")
wc = WordCloud(max_words=300, stopwords=stopwords, width=800, height=400)
wc.generate(text)
wc.to_file(os.path.join(d, "cvpr2015wordcloud.png"))
plt.imshow(wc)
plt.axis("off")
plt.show()
def generate_word_cloud(text, mask_filename):
d = path.dirname(__file__) #??
mask = imread(path.join(d, mask_filename))
# adding movie script specific stopwords
stopwords = STOPWORDS.copy()
stopwords.add("info")
stopwords.add("meetbot")
stopwords.add("supybot")
wc = WordCloud(max_words=1000, mask=mask, stopwords=stopwords, margin=10,
random_state=1).generate(text)
_, tmpfilename = tempfile.mkstemp('-wordcloud.png')
wc.to_file(tmpfilename)
return tmpfilename
def get_wordcloud(self, filmname):
movieid = MovieHelper().select(1, {"name": filmname})
if (movieid == None):
return False
datalist = CommentHelper().select(conditions={"movieid": movieid})
commentlist = []
for data in datalist:
if data[1] != "" or data[1] != ",":
commentlist.append(data[1])
comments_after_split = jieba.cut(str(commentlist), cut_all=False)
wordlist = "".join(comments_after_split)
stopwords = STOPWORDS.copy()
stopwords.add("电影")
stopwords.add("一部")
stopwords.add("一个")
stopwords.add("没有")
stopwords.add("什么")
stopwords.add("有点")
stopwords.add("这部")
stopwords.add("这个")
stopwords.add("不是")
stopwords.add("真的")
stopwords.add("感觉")
stopwords.add("觉得")
stopwords.add("还是")
stopwords.add("但是")
stopwords.add("就是")
bg_image = np.array(Image.open('bg.jpg'))
# 设置词云参数，参数分别表示：画布宽高、背景颜色、背景图形状、字体、屏蔽词、最大词的字体大小
wc = WordCloud(width=2048,
height=768,
background_color='white',
mask=bg_image,
font_path='STKAITI.TTF',
stopwords=stopwords,
max_font_size=800,
random_state=50)
wc.generate_from_text(wordlist)
plt.imshow(wc)
plt.axis("off")
plt.show()
wc.to_file("词云.jpg")
def show_fen_ci_qianmin():
# jieba是一个基于Python的分词库，完美支持中文分词，功能强大
import jieba
# Matplotlib是一个Python的2D绘图库，能够生成高质量的图形，可以快速生成绘图、直方图、功率谱、柱状图、误差图、散点图等
import matplotlib.pyplot as plt
# wordcloud是一个基于Python的词云生成类库，可以生成词云图
# 可能安装失败 https://www.lfd.uci.edu/~gohlke/pythonlibs/#wordcloud
# python -m pip install wordcloud-1.5.0-cp37-cp37m-win32.whl
from wordcloud import WordCloud, STOPWORDS
# 获取所有个性签名
signatures = []
with open(friends_data, mode='r', encoding='utf-8') as f:
rows = f.readlines()
for row in rows:
signature = row.split(',')[5]
if signature != '':
signatures.append(signature)
# 设置分词
split = jieba.cut(str(signatures), cut_all=False) # False精准模式分词、True全模式分词
words = ' '.join(split) # 以空格进行拼接
# print(words)
# 设置屏蔽词，去除个性签名中的表情、特殊符号等
stopwords = STOPWORDS.copy()
stopwords.add('span')
stopwords.add('class')
stopwords.add('emoji')
stopwords.add('emoji1f334')
stopwords.add('emoji1f388')
stopwords.add('emoji1f33a')
stopwords.add('emoji1f33c')
stopwords.add('emoji1f633')
# 导入背景图
bg_image = plt.imread(current_dir+'/010-wechat-bg.jpg')
# 设置词云参数，参数分别表示：画布宽高、背景颜色、背景图形状、字体、屏蔽词、最大词的字体大小
wc = WordCloud(width=1024, height=768, background_color='white', mask=bg_image, font_path='STKAITI.TTF',
stopwords=stopwords, max_font_size=400, random_state=50)
# 将分词后数据传入云图
wc.generate_from_text(words)
plt.imshow(wc) # 绘制图像
plt.axis('off') # 不显示坐标轴
# 保存结果到本地
wc.to_file(current_dir+'/个性签名词云图.jpg')
def to_wordcloud(text):
# background_image=plt.imread('./xxx.jpg')
stopwords=STOPWORDS.copy()
for i in ['电影','电影院','影片','IMAX']:
stopwords.add(i)
# mask=background_image,
wc = WordCloud(width=1024,height=768,background_color='white',font_path = 'simhei.ttf',stopwords=stopwords,max_font_size=400,random_state=50)
wc.generate_from_text(text)
# img_colors= ImageColorGenerator(background_image)
# wc.recolor(color_func=img_colors)
wc.to_file('maoyan_'+code+'.jpg')
plt.imshow(wc)
plt.axis('off')
plt.show()
def mk_wordcloud():
text_content = open('test.txt', 'r', encoding = 'utf-8').read()
wordlist_cut_by_jieba = jieba.cut(text_content, cut_all=False)
wordlist_space = ' '.join(wordlist_cut_by_jieba)
#print(wordlist_space)
background_image = plt.imread('xpj.jpg')
print('加载图片')
#屏蔽词
stopwords = STOPWORDS.copy()
stopwords.add("还是")
stopwords.add("但是")
stopwords.add("不是")
stopwords.add("就是")
stopwords.add("没有")
stopwords.add("知道")
stopwords.add("因为")
stopwords.add("看到")
stopwords.add("还有")
stopwords.add("觉得")
stopwords.add("有点")
stopwords.add("这么")
stopwords.add("其实")
stopwords.add("一个")
stopwords.add("为什么")
stopwords.add("开始")
stopwords.add("不要")
stopwords.add("本来")
stopwords.add("虽然")
stopwords.add("出来")
wc = WordCloud(
width = 750,
height = 1335,
background_color = 'white',
mask = background_image,
font_path = 'C:\Windows\Fonts\simsun.ttc',
max_words = 400,#最多字数
stopwords = stopwords,
max_font_size=400,#字体最大值
random_state = 50, #随机生成状态，即多少种配色方案
)
wc.generate_from_text(wordlist_space)
img_color = ImageColorGenerator(background_image)#背景色
wc.recolor(color_func=img_color) #字体颜色为背景图片的颜色
plt.imshow(wc) #显示词云图
plt.axis('off')#不显示下标
plt.show()
def generate_wordcloud(text):
def my_color_func(word, font_size, position, orientation, random_state=None, **kwargs):
"""
To change colors change the range for random ints below:
Hue values are between 0 and 360
Follows rainbow:
Red Orange Yellow Green Blue Indigo Violet
0 50 100 150 200 250 300 360
"""
hue_lower = 0
hue_upper = 150
saturation = 500
light_lower = 80
light_upper = 120
return "hsl(%d, %d%%, %d%%)" % (
random.randint(hue_lower, hue_upper),
saturation,
random.randint(light_lower, light_upper),
)
stopwords = STOPWORDS.copy()
stopwords.add("us")
stopwords.add("one")
stopwords.add("will")
stopwords.add("u")
rand_num = random.randint(1, 100)
wc = WordCloud(
max_words=100, stopwords=stopwords, margin=10, random_state=rand_num, width=2000, height=1200
).generate(text)
fig = plt.figure(figsize=(32, 20), dpi=100)
plt.imshow(wc.recolor(color_func=my_color_func, random_state=1))
# Save image
outfilename = "tmp.png"
wc.to_file(outfilename)
plt.axis("off")
plt.show()
def makeWC(theText, mask_image, mw):
SW = STOPWORDS.copy()
mywords = ['and', 'the', 'to', 'by', 'in', 'of', 'up',
'Facebook', 'Twitter', 'Pinterest', 'Flickr',
'Google', 'Instagram', 'login', 'Login', 'Log',
'website', 'Website', 'Contact', 'contact',
'twitter', 'Branding', 'Tweet', 'pic', 'location',
'Details'
] + list(bad_words())
[SW.add(w) for w in mywords]
wordcloud = WordCloud(
relative_scaling=0,
prefer_horizontal=random.uniform(0.5, 1),
stopwords=SW,
background_color='black',
max_words=mw,
mask = mask_image
).generate(theText)
return wordcloud
def main():
data = {}
data['questions'] = []
data['stakeholders'] = []
data['wordclouds'] = {}
stopwords = STOPWORDS.copy()
sphere_stopwords = {'1a':['live', 'born', 'year', 'yrs', 'since'], \
'1b':['live', 'born', 'year', 'yrs', 'moved', 'since'], \
'2a':['time'], \
'2b':[], \
'3':[], \
'4a':['bangalore', 'advantage', 'advantages'], \
'4b':['bangalore', 'challenge', 'challenges'], \
'4c':['work'], \
'4d':['dependency', 'dependencies', 'external'], \
'4e':['area', 'bangalore'], \
'4f':[], \
'5b':['food', 'air'], \
'6a':['end', 'user', 'enduser'], \
'6b':['month', 'income', 'per', 'household'], \
'6c':['interact', 'interaction','end', 'user', 'enduser'], \
'6d':['design', 'end', 'user', 'enduser'], \
'7a':['quality', 'control', 'challenge'], \
'7b':['end', 'user', 'access', 'challenge'], \
'7c':[], \
'7d':[], \
'8a':['tool', 'resource', 'resource'], \
'8b':['average', 'age', 'team'], \
'8c':[], \
'8d':[], \
'8e':[], \
'9a':[], \
'9b':[], \
'10a':[], \
'10b':[], \
'10c':[], \
'10d':[], \
'10e':[], \
'10f':[], \
'11a':[], \
'11b':[], \
'11c':[], \
'12a':[], \
'12b':[], \
'12c':[], \
'13a':[], \
'13b':[], \
'13c':[], \
'13d':[], \
'13e':[], \
'13f':[], \
'13g':[], \
'13h':[], \
'13i':[], \
'14a':[], \
'14b':[], \
}
#Filter out standalone words 2 letters or shorter
shortword = re.compile(r'\W*\b\w{1,2}\b')
with open('alldata.csv') as csvfile:
reader = csv.DictReader(csvfile)
for row in reader:
stakeholder = row['Code']
data['stakeholders'].append(stakeholder)
data[stakeholder] = {}
data[stakeholder]['alltext'] = ''
for key in row:
if key != 'Code':
question = key
if question not in data['questions']:
data['questions'].append(question)
data[question] = ''
raw_response = shortword.sub('', row[key].lower().translate(None,string.punctuation))
stemmed_response = ' '.join([stem(word) for word in raw_response.split()])
data[stakeholder][question] = row[key]
data[stakeholder]['alltext'] += stemmed_response
data[stakeholder]['alltext'] += ' '
data[question] += stemmed_response
data[question] += ' '
#Generate word clouds:
for question in sorted(data['questions']):
if question is not '5a':
#Number of words per question
# print question, ':', len(data[question].split())
try:
s = stopwords.union(set(sphere_stopwords[question]))
data['wordclouds'][question] = WordCloud(stopwords=s).generate(data[question])
except:
print question
for stakeholder in data['stakeholders']:
try:
data['wordclouds'][stakeholder] = WordCloud(stopwords=stopwords).generate(data[stakeholder]['alltext'])
except:
print stakeholder
pickle.dump(data, open('alldata_v2.pickle', 'wb'))
cursor = links.find({},{"body":1})
test=""
for document in cursor :
test=test+document['body']
with codecs.open("text_mining/my_stopwords.txt","r",encoding="utf-8") as f:
read_data = f.readlines()
stopwords = STOPWORDS.copy()
for data in read_data:
stopwords.add(data)
stopwords = map(lambda s: s.strip(), stopwords)
mask_choko = np.array(Image.open("text_mining/chokomag.png"))
wordcloud = WordCloud( stopwords=stopwords,background_color="black", max_words=10000,mask=mask_choko).generate(test)
def main():
data = pickle.load( open('alldata.pickle', 'rb') )
data['wordclouds'] = {}
stopwords = STOPWORDS.copy()
sphere_stopwords = { 'common': ['sam', 'mayu', 'mani'],
'1a':['live', 'born', 'year', 'years', 'yrs', 'since', 'bangalore'], \
'1b':['live', 'born', 'year', 'yrs', 'moved', 'since', 'bangalore'], \
'2a':['balance', 'time'], \
'2b':['inspiration'], \
'3':['lifestyle', ], \
'4a':['bangalore', 'advantage', 'advantages'], \
'4b':['bangalore', 'challenge', 'challenges'], \
'4c':['work'], \
'4d':['dependency', 'dependencies', 'external'], \
'4e':['area', 'bangalore'], \
'4f':['measures'], \
'5b':['food', 'air'], \
'6a':['end', 'user', 'enduser'], \
'6b':['month', 'income', 'per', 'household'], \
'6c':['interact', 'interaction','end', 'user', 'enduser'], \
'6d':['design', 'end', 'user', 'enduser'], \
'7a':['quality', 'control', 'challenge'], \
'7b':['end', 'user', 'access', 'challenge'], \
'7c':[], \
'7d':[], \
'8a':['tool', 'tools', 'resource', 'resources'], \
'8b':['average', 'age', 'years', 'team', 'people'], \
'8c':['fund', 'funding', 'funded', 'money'], \
'8d':['tech', 'technology'], \
'8e':['office', 'location', 'work', 'space'], \
'9a':['skill', 'skills'], \
'9b':['training'], \
'10a':['active', 'internal', 'collaboration', 'collaborate'], \
'10b':['active', 'external', 'collaboration', 'collaborate'], \
'10c':['lead', 'leads', 'learning', 'collaboration', 'collaborate'], \
'10d':['part', 'formal', 'collaboration', 'collaborate', 'platform'], \
'10e':['culture', 'open', 'share', 'sharing', 'sector'], \
'10f':['share', 'shares', 'shared'], \
'11a':['partner', 'partners', 'partnership', 'partnerships'], \
'11b':['criteria', 'partner', 'partners', 'partnership', 'partnerships'], \
'11c':['partner', 'partners', 'partnership', 'partnerships', 'sector'], \
'12a':['monitoring', 'evaluation', 'method', 'methods', 'impact'], \
'12b':['goal', 'next', 'year', 'years'], \
'12c':['impact', 'studies', 'data', 'shared'], \
'13a':['entrepreneur'], \
'13b':['start', 'starting', 'startup'], \
'13c':['entrepreneur', 'entrepreneurs', 'interact', 'interaction'], \
'13d':['entrepreneur', 'entrepreneurs', 'role', 'local', 'needs'], \
'13e':['advantage', 'advantages', 'local', 'entrepreneur', 'entrepreneurs'], \
'13f':['barrier', 'barriers', 'entry', 'local', 'entrepreneur', 'entrepreneurs'], \
'13g':['challenge', 'challenges', 'local', 'entrepreneur', 'entrepreneurs'], \
'13h':['entrepreneur', 'entrepreneurs', 'fail'], \
'13i':['resource', 'resources', 'need', 'needed', 'strengthen', 'local', 'entrepreneur', 'entrepreneurs'], \
'14a':['recommend', 'stakeholder', 'stakeholders'], \
'14b':['map', 'visual'], \
}
#Filter out standalone words 2 letters or shorter
shortword = re.compile(r'\W*\b\w{1,2}\b')
questions = []
text = {}
for stakeholder in data:
text[stakeholder] = ''
for question in data[stakeholder]:
if question not in questions:
questions.append(question)
text[question] = ''
response = shortword.sub('', ' '.join(data[stakeholder][question]).lower().translate(None,string.punctuation))
text[stakeholder] += response + ' '
text[question] += response + ' '
#Generate word clouds:
for question in sorted(questions):
if question is not '5a':
try:
s = stopwords.union(set(sphere_stopwords[question]+sphere_stopwords['common']))
wordcloud = WordCloud(stopwords=s, width=1600, height=800, background_color='white').generate(text[question])
wordcloud.to_file('clouds/'+question+'-'+str(len(text[question].split()))+'words.png')
except:
print question
for stakeholder in data:
try:
s = stopwords.union(set(sphere_stopwords['common']))
wordcloud = WordCloud(stopwords=s, width=1600, height=800, background_color='white').generate(text[stakeholder])
wordcloud.to_file('clouds/'+stakeholder+'-'+str(len(text[stakeholder].split()))+'words.png')
except:
print stakeholder
