def test_display_wordcloud_valid(self):
wc = WordCloud(background_color="white")
wc.generate_from_text(
"this is a word cloud text lmao lmao lmao lmao lo lo lo lol lol lol lol"
)
self.wordcloud.word_clouds.append(wc)
self.wordcloud.display_word_cloud()
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 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 wordcloud():
con = sqlite3.connect('douban.db')
cur = con.cursor()
sql = "select instroduction from movie250"
data = cur.execute(sql)
text = ''
for item in data:
text += item[0]
cur.close()
con.close()
cut = jieba.cut(text)
string = ' '.join(cut)
img = Image.open(r'./static/assets/img/tree.jpg')
img_array = np.array(img)
wc = WordCloud(
background_color='white',
mask=img_array,
font_path=
'/home/yzx/PycharmProjects/douban_flask/templates/MSYH.TTF')
wc.generate_from_text(string)
#绘制图片
fig = plt.figure(1)
plt.imshow(wc)
plt.axis('off')
plt.show()
def main():
con=sqlite3.connect('movie.db')
cur=con.cursor()
sql='select introduction from movie250'
data=cur.execute(sql)
text=''
for item in data:
text+=item[0]
cut =jieba.cut(text)
string =' '.join(cut)
print(len(string))
#print(string)
img=Image.open(r'.\static\assets\img\camel.jfif')
img_array=np.array(img) # 将图片转换为数组
wc=WordCloud(background_color='black',
mask=img_array,
font_path='msyh.ttc')
wc.generate_from_text(string)
# 绘制图片
fig=plt.figure(1)
plt.imshow(wc)
plt.axis('off') # 是否显示坐标轴
#plt.show()
plt.savefig(r'.\static\assets\img\word.png',dpi=500)
def data_analysis():
'''
进行得到txt文件内的数据分析
由于数据限制，这里只进行词云分析
:return: None
'''
with open("text.txt", 'r', encoding="utf-8") as f:
text = f.read()
comment = jieba.cut(text, cut_all=False)
# 获得文件内容
comment = " ".join(comment)
# 解析背景图
bg_img = plt.imread("bg.jpg")
# 拦截词
stopwords = set()
stopwords.add("爱情公寓")
stopwords.add("爱情")
stopwords.add("公寓")
stopwords.add("电影")
# 创建wc对象
wc = WordCloud(width=1800,
height=1000,
background_color='white',
font_path="C:/Windows/Fonts/STFANGSO.ttf",
mask=bg_img,
stopwords=stopwords,
max_font_size=400,
random_state=50)
wc.generate_from_text(comment)
plt.imshow(wc)
plt.axis('off') # 不显示坐标轴
plt.show()
wc.to_file("result.jpg")
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 title_word_cloud():
data = pd.read_csv('hupu-pandas.csv', na_values=['NULL'])
title_data = data['title']
# with open('title.txt', 'w') as f:
# for title in title_data.values:
# f.write(title)
# f.close()
# f = open('title.txt', 'r').read().decode('utf-8')
# text = stop_words(f)
text = open('words.txt').read().decode('utf-8')
image = Image.open(r'C:\Users\lvbiaobiao\Desktop\hupu-1.jpg')
graph = np.array(image)
cloud = WordCloud(
font_path=
r'E:\date\python\SourceHanSerifSC_EL-M\SourceHanSerifSC-Regular.otf',
max_font_size=18,
background_color="white",
width=640,
height=200,
relative_scaling=0.5,
mask=graph,
max_words=100,
colormap='nipy_spectral')
cloud.generate_from_text(text)
# image_color = ImageColorGenerator(graph)
plt.imshow(cloud, interpolation='gaussian')
# plt.imshow(cloud.recolor(color_func=image_color))
plt.axis("off")
plt.show()
cloud.to_file('hupu.png')
def ShowImgHotWord(items, maxwords):
npath = os.getcwd()
imgfile = npath + '\\ntlk1\\cloud.jpg'
back_ground = imread(imgfile)
wc = WordCloud(
background_color="white",
max_words=maxwords,
mask=back_ground,
max_font_size=100,
random_state=42,
font_path="C:/Windows/Fonts/STZHONGS.ttf",
)
#print(items)
wcword = ' '.join(items)
wc.generate_from_text(wcword)
# 基于彩色图像生成相应彩色
image_colors = ImageColorGenerator(back_ground)
wc.recolor(color_func=image_colors)
# 显示图片
plt.imshow(wc)
# 关闭坐标轴
plt.axis('off')
plt.show()
# 绘制词云
# plt.figure()
# plt.imshow(wc.recolor(color_func=image_colors))
# plt.axis('off')
# 保存图片
wc.to_file('123.png')
def wc_english():
# 获取当前文件路径
d = path.dirname(_file_) if "_file_" in locals() else os.getcwd()
#获取文本text
text = open(path.join(d, 'legend.txt')).read()
#读取背景图片
background_Image = np.array(Image.open(path.join(d, 'legend.jpg')))
#提取背景图片颜色
img_colors = ImageColorGenerator(background_Image)
#获取文本词排序，可调整stopwords
#设置英文停止词
stopwords = set(STOPWORDS)
stopwords.add('one')
wc = WordCloud(
margin=2,
scale=2,
max_words=200,
min_font_size=4,
stopwords=stopwords,
random_state=42,
max_font_size=150,
)
wc.generate_from_text(text)
wc.recolor(color_func=grey_color_func)
wc.to_file('1900prol.png')
#显示图像
plt.imshow(wc, interpolation='bilinear')
plt.axis('off')
plt.tight_layout()
#存储图像
#or#plt.savingfig('1900_basic.png',dpi=200)
plt.show()
def gene_word_cloud(_text):
font = "/System/Library/fonts/PingFang.ttc"
wc = WordCloud(
width=600, # 默认宽度
height=200, # 默认高度
margin=2, # 边缘
ranks_only=None,
prefer_horizontal=0.9,
mask=None, # 背景图形,如果想根据图片绘制，则需要设置
color_func=None,
max_words=200, # 显示最多的词汇量
stopwords=None, # 停止词设置，修正词云图时需要设置
random_state=None,
background_color='#ffffff', # 背景颜色设置，可以为具体颜色，比如：white或者16进制数值。
font_step=1,
font_path=font,
mode='RGB',
regexp=None,
collocations=True,
normalize_plurals=True,
contour_width=0,
colormap='viridis', # matplotlib色图，可以更改名称进而更改整体风格
contour_color='Blues',
repeat=False,
scale=2,
min_font_size=10,
max_font_size=200)
wc.generate_from_text(_text)
# 存储图像
wc.to_file('饥饿站台top10关键词textrank.png')
def content_distribution(self, contents):
jieba.load_userdict('userdict.txt')
content_cut = jieba.cut(str(contents), cut_all=False)
words = ' '.join(content_cut)
# 设置屏蔽词
# stopwords = STOPWORDS.copy()
# stopwords.add('电影')
stopwords = set()
with open('stopwords.txt', 'r', encoding='utf-8') as f:
rows = f.readlines()
for row in rows:
stopwords.add(row.replace('\n', ''))
# print(stopwords)
#导入背景图
bg_image = plt.imread('bgimage.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=1200,
height=800,
background_color='white',
mask=bg_image,
font_path='STKAITI.ttf',
stopwords=stopwords,
max_font_size=300,
random_state=40)
# 分词传入云图
wc.generate_from_text(words)
plt.imshow(wc)
# 不显示坐标轴
plt.axis('off')
plt.show()
wc.to_file(self.path + r'/wordcloud.jpg')
def drawCloud(db):
table = db.products
data = pd.DataFrame(list(table.find()))
data = data[['_id']]
text = ''
for line in data['_id']:
r = '[a-zA-Z0-9’!"#$%&\'()*+,-./:;<=>?@，。?★、…【】《》？“”‘’！[\\]^_`{|}~]+'
line = re.sub(r, '', line.replace('笔记本电脑', '').replace('英寸', ''))
text += ' '.join(jieba.cut(line, cut_all=False))
# backgroud_Image = plt.imread('computer.jpeg')
print('text>>',text)
wc = WordCloud(
background_color='white',
# mask=backgroud_Image,
# font_path='DroidSansMono.ttf',#没有字体，图片是方框乱码
max_words=2000,
stopwords=STOPWORDS,
max_font_size=130,
random_state=30
)
wc.generate_from_text(text)
# img_colors = ImageColorGenerator(backgroud_Image)
# wc.recolor(color_func=img_colors)
plt.imshow(wc)
plt.axis('off')
wc.to_file("computer.jpg")
print("生成词云成功")
def create_word_cloud_img(self, data_frame):
# 分隔评论内容
comment = jieba.cut(str(data_frame['comment']), cut_all=False)
wl_space_split = " ".join(comment)
# 自定义屏蔽词
stopwords = self.get_stop_words()
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)
plt.imshow(wc)
plt.axis('off') # 不显示坐标轴
# plt.show()
file_path = ''
if self.movie.platform == 0:
file_path = './' + self.movie.movie_name + '/【豆瓣】《' + self.movie.movie_name + '》词云图.jpg'
elif self.movie.platform == 1:
file_path = './' + self.movie.movie_name + '/【猫眼】《' + self.movie.movie_name + '》词云图.jpg'
else:
file_path = './' + self.movie.movie_name + '/【豆瓣+猫眼】《' + self.movie.movie_name + '》词云图.jpg'
wc.to_file(file_path)
print('词云图创建完毕')
def create_wordcloud(df):
"""
生成地铁名词云
"""
# 分词
text = ''
for line in df['station']:
text += ' '.join(jieba.cut(line, cut_all=False))
text += ' '
backgroud_Image = plt.imread('rocket.jpg')
wc = WordCloud(
background_color='white',
mask=backgroud_Image,
font_path='C:\Windows\Fonts\华康俪金黑W8.TTF',
max_words=1000,
max_font_size=150,
min_font_size=15,
prefer_horizontal=1,
random_state=50,
)
wc.generate_from_text(text)
img_colors = ImageColorGenerator(backgroud_Image)
wc.recolor(color_func=img_colors)
# 看看词频高的有哪些
process_word = WordCloud.process_text(wc, text)
sort = sorted(process_word.items(), key=lambda e: e[1], reverse=True)
print(sort[:50])
plt.imshow(wc)
plt.axis('off')
wc.to_file("地铁名词云.jpg")
print('生成词云成功!')
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 show_fen_ci_beizhu():
# 导入jieba模块，用于中文分词
import jieba
# 导入matplotlib，用于生成2D图形
import matplotlib.pyplot as plt
# 导入wordcount，用于制作词云图
from wordcloud import WordCloud, STOPWORDS
# 获取备注名
remarkNames = []
with open(friends_data, mode='r', encoding='utf-8') as f:
rows = f.readlines()
for row in rows:
remarkName = row.split(',')[1]
if remarkName != '':
remarkNames.append(remarkName)
# 设置分词
split = jieba.cut(str(remarkNames), 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
# 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',
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+'/备注名词云图.jpg')
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 get_wordcloud() -> str:
"""
根据电影简介创建词云图片，返回图片路径
return : path （图片路径）
"""
sql = "select intro from movie250"
data = select(sql)
intro_str = ' '.join(list(map(lambda x: x[0], data)))
# 用jieba提取词语
cut_list = list(jieba.cut(intro_str))
cut_str = ' '.join(cut_list)
# 用PIL打开图片，用numpy转换成数组
# img = Image.open("../static/assets/img/tree.jpg")
img = Image.open("static/assets/img/tree.jpg")
img_arr = np.array(img)
# 用WordCloud创建词云
wc = WordCloud(
background_color='white',
mask=img_arr, # 图片遮罩，数组形式的图片
font_path='msyh.ttc' # 字体所在位置: C:\Windows\Fonts
)
wc.generate_from_text(cut_str)
# 用matplotlib.pyplot绘制图片，并保存
fig = plt.figure()
plt.axis('off')
plt.imshow(wc)
path = "static/assets/img/word_cloud.jpg"
plt.savefig(path, dpi=300)
return path
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 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 genWordCloud(self):
self.getComments()
keywords = self.getKeywords()
text_string = ','.join(keywords)
background_Image = np.array(self.genBackground(self.bg)) if self.bg else None
wc = WordCloud(
width=600,
height=200,
margin=2,
ranks_only=None,
prefer_horizontal=0.9,
mask=background_Image,
color_func=None,
max_words=200,
stopwords=None,
random_state=None,
background_color='#ffffff',
font_step=1,
mode='RGB',
regexp=None,
collocations=True,
normalize_plurals=True,
contour_width=0,
colormap='viridis',
contour_color='Blues',
repeat=False,
scale=2,
min_font_size=10,
max_font_size=200)
wc.generate_from_text(text_string)
plt.imshow(wc, interpolation='bilinear')
plt.axis('off')
plt.tight_layout()
wc.to_file('top10.png')
plt.show()
def wordcloud():
if os.path.exists(r'.\static\assets\img\word.png'):
# 判断本地是否已存在 images 文件夹，有的话直接开始下载，没有创建一个
print("当前目录下已存在词云图片....")
else:
conn = sqlite3.connect("comment.db")
cursor = conn.cursor()
sql = "select distinct message from hotComment"
#distinct关键字可查找唯一的记录，过滤重复数据
data = cursor.execute(sql)
text = ""
for item in data:
text = text + item[0]
print(text)
cursor.close()
conn.close()
# 分词
cut = jieba.cut(text)
string = ' '.join(cut)
print(len(string))
img = Image.open(r'.\static\assets\img\wordbg.jpg') # 打开遮罩图片
img_array = np.array(img)
word_cloud = WordCloud(background_color='white', mask=img_array, font_path="msyh.ttc")
word_cloud.generate_from_text(string)
# 绘制图片
fig = plt.figure(1)
plt.imshow(word_cloud)
plt.axis("off")
# plt.show()
plt.savefig(r'.\static\assets\img\word.png', dpi=500)
return render_template("wordcloud.html")
def creat_wordcloud(df):
text = ''
for line in df['title']:
text += ' '.join(jieba.cut(line, cut_all=False))
text += ' '
background_Image = plt.imread('data/image.jpg')
wc = WordCloud(background_color='white',
mask=background_Image,
font_path='msyh.ttc',
max_words=1000,
max_font_size=150,
min_font_size=15,
prefer_horizontal=1,
random_state=50)
wc.generate_from_text(text)
img_colors = ImageColorGenerator(background_Image)
wc.recolor(color_func=img_colors)
process_word = WordCloud.process_text(wc, text)
sort = sorted(process_word.items(), key=lambda e: e[1], reverse=True)
print(sort[:50])
plt.imshow(wc)
plt.axis('off')
wc.to_file('商家标题词云.jpg')
print('生成词云成功')
def word():
# 1. 词云所需的文字
con = sqlite3.connect('51job.db')
cur = con.cursor()
sql = 'select company_name from job'
data = cur.execute(sql)
text = ''
for item in data:
text += item[0]
cur.close()
con.close()
# 2.分词
cut = jieba.cut(text)
string = ' '.join(cut)
# 3.背景图片
img = Image.open(r'./static/images/tree.jpeg')
imgArray = np.array(img) # 将图片转换为数组
wc = WordCloud(background_color='white',
mask=imgArray,
font_path='/Library/Fonts/Songti.ttc')
wc.generate_from_text(string)
# 4.绘图
flg = plt.figure(1)
plt.imshow(wc)
plt.axis('off') # 是否显示坐标轴
plt.show() # 显示生成的词云图片
# 输出词云文件到文件
# plt.savefig('./static/images/job.jpg')
return render_template('word.html')
def make_worldcloud(wl_space_split):
# text_from_file_with_apath = open(file_path, 'r').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('E:/python/weibo_analysis/result/muban.jpg')
print u'加载图片成功！'
'''设置词云样式'''
# stopwords = STOPWORDS.copy()
# stopwords.add("真的") #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:/python/weibo_analysis/result/ziti.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=200, # 设置最大现实的字数
# stopwords=stopwords,# 设置停用词
max_font_size=300,# 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, "pic.jpg"))
print u'生成词云成功!'
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 keyword_cloud(text):
backgroud_Image = plt.imread(r'C:\Users\Administrator\Desktop\词云生成(wordcloud)\timg.jpg') #背景图片
print('加载图片成功！')
'''''设置词云样式'''
wc = WordCloud(
background_color='white',# 设置背景颜色 (画布颜色)
height=1200, #蒙版的长宽
width=2000,
mask=backgroud_Image,# 设置背景图片 (图片蒙版)
font_path='C:\Windows\Fonts\STZHONGS.TTF', # 选择字体
max_words=500, # 设置最大显示的字数
stopwords=STOPWORDS,# 设置停用词
max_font_size=150,# 设置字体最大值
#min_font_size=4,# 设置字体最小值
random_state=30,# 设置有多少种随机生成状态，即有多少种配色方案
scale = 1 #画布放大比例
)
wc.generate_from_text(text)
print('开始加载文本')
#改变字体颜色
img_colors = ImageColorGenerator(backgroud_Image)
#字体颜色为背景图片的颜色
wc.recolor(color_func=img_colors)
# 显示词云图
plt.imshow(wc)
# 是否显示x轴、y轴下标
plt.axis('off')
plt.show() #显示
wc.to_file(r'') #保存
print('生成词云成功!')
def wc_chinese():
text = open(path.join(d, 'langchao2.txt'), encoding='UTF-8-SIG').read()
font_path = 'C:\Windows\Fonts\STXIHEI.TTF'
background_Image = np.array(Image.open(path.join(d, "circle.jpg")))
img_colors = ImageColorGenerator(background_Image)
stopwords = set('')
wc = WordCloud(
font_path=font_path,
margin=2,
mask=background_Image,
scale=2,
max_words=200,
min_font_size=4,
max_font_size=100,
stopwords=stopwords,
random_state=42,
background_color='white',
)
wc.generate_from_text(text)
# 获取文本词排序，可调整 stopwords
process_word = WordCloud.process_text(wc, text)
sort = sorted(process_word.items(), key=lambda e: e[1], reverse=True)
print(sort[:50]) # 获取文本词频最高的前50个词
wc.recolor(color_func=img_colors)
plt.imshow(wc, interpolation='bilinear')
plt.axis('off')
plt.tight_layout()
plt.savefig('浪潮basic2.png', dpi=200)
plt.show()
def data_analysis():
with open("get.txt", 'r') as f:
text = f.read()
text = jieba.cut(text, cut_all=False)
text = " ".join(text)
bg_img = plt.imread("bg.jpg")
stopwords = set()
stopwords_list = [
"整合包", "mod", "整合", "MCBBS", "精彩", "作品", "世界", "生存", "附属", "冒险", "很棒",
"光影", "内含音乐"
]
for item in stopwords_list:
stopwords.add(item)
wc = WordCloud(width=1800,
height=1000,
background_color='white',
font_path="C:/Windows/Fonts/STFANGSO.ttf",
mask=bg_img,
stopwords=stopwords,
max_font_size=700,
random_state=50)
wc.generate_from_text(text)
img_colors = ImageColorGenerator(bg_img)
wc.recolor(color_func=img_colors)
plt.imshow(wc)
plt.axis('off') # 不显示坐标轴
plt.show()
wc.to_file("result.jpg")
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 cloud_for_document(outfile=None, fulltext=None):
"""Create a wordcloud for the DOCUMENT and save the result in OUTFILE"""
assert outfile != None
assert fulltext != None
wc = WordCloud(width=1024, height=640)
wc.generate_from_text(fulltext)
plt.imshow(wc)
plt.axis("off")
plt.savefig(outfile, dpi=300)
def generate_wordcloud(text, bgcolor, width, height, max_words, mask):
if mask is not None:
mask = _load_mask(mask)
wc = WordCloud(relative_scaling=.5, width=width, height=height,
background_color=bgcolor, mask=mask,
max_words=max_words)
return wc.generate_from_text(text)
def wordcloud_image(text, **kwargs):
""" Build wordcloud from text """
format = 'PNG'
if kwargs.has_key('file_format'):
format = kwargs.pop('file_format')
args = default_settings
args.update(kwargs)
wc = WordCloud(**args)
wc.generate_from_text(text)
img = wc.to_image()
del wc
imgbuf = BytesIO()
img.save(imgbuf, format)
width, height = img.size
imgbuf.seek(0)
del img
return imgbuf, (width, height)
df = pd.read_csv('music_message.csv', header=None)
text = ''
for line in df[2]:
text += ' '.join(jieba.cut(line, cut_all=False))
backgroud_Image = plt.imread('job.jpg')
stopwords = set('')
stopwords.update(['封面', 'none介绍', '介绍', '歌单', '歌曲', '我们', '自己', '没有', '就是', '可以', '知道', '一起', '不是', '因为', '什么', '时候', '还是', '如果', '不要', '那些', '那么', '那个', '所有', '一样', '一直', '不会', '现在', '他们', '这样', '最后', '这个', '只是', '有些', '其实', '开始', '曾经', '所以', '不能', '你们', '已经', '后来', '一切', '一定', '这些', '一些', '只有', '还有'])
wc = WordCloud(
background_color='white',
mask=backgroud_Image,
font_path='C:\Windows\Fonts\STZHONGS.TTF',
max_words=2000,
max_font_size=150,
random_state=30,
stopwords=stopwords
)
wc.generate_from_text(text)
# 看看词频高的有哪些,把无用信息去除
process_word = WordCloud.process_text(wc, text)
sort = sorted(process_word.items(), key=lambda e:e[1], reverse=True)
print(sort[:50])
img_colors = ImageColorGenerator(backgroud_Image)
wc.recolor(color_func=img_colors)
plt.imshow(wc)
plt.axis('off')
wc.to_file("活着.jpg")
print('生成词云成功!')
stopwords.add('目前')
stopwords.add('但是')
stopwords.add('然后')
stopwords.add('这样')
stopwords.add('这种')
stopwords.add('曲唑')
stopwords.add('如果')
stopwords.add('戈舍')
# 导入背景图
bg_image = plt.imread('/Users/youpeng/zhizhi/beastcancer/timg.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(
scale=4,
background_color='white',
mask=bg_image,
font_path='/System/Library/Fonts/PingFang.ttc',
stopwords=stopwords,
max_font_size=400,
random_state=50,
collocations=False
)
# 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('/Users/youpeng/zhizhi/beastcancer/endocrine.jpg')
