先放兩張效果圖：
還有這個：
是不是立馬逼格滿滿~
這里用到的是一個有趣的模塊，叫wordcloud：
github: https://github.com/amueller/word_cloud
官網: https://amueller.github.io/word_cloud/
*建議自行通過下載setup.py的方式安裝，pip install 不一定能下載成功。
打開，並下載： https://github.com/amueller/word_cloud/archive/master.zip
然后 python setup.py install
安裝其它依賴的模塊：
必須安裝第一步安裝numpy: https://pypi.python.org/pypi/numpy
scipy: https://pypi.python.org/pypi/scipy
jieba: https://pypi.python.org/pypi/jieba/
下載whl文件，然后 pip install XXXX.whl
如果出現錯誤，請參考https://www.cnblogs.com/nice-forever/p/5371906.html
分享一下源碼：
#coding:utf-8
#author http://blog.csdn.net/fyuanfena/article/details/52038984
from os import path from scipy.misc import imread import matplotlib.pyplot as plt import jieba from wordcloud import WordCloud, STOPWORDS, ImageColorGenerator stopwords = {} def importStopword(filename=''): global stopwords f = open(filename, 'r', encoding='utf-8') line = f.readline().rstrip() while line: stopwords.setdefault(line, 0) stopwords[line] = 1 line = f.readline().rstrip() f.close() def processChinese(text): seg_generator = jieba.cut(text) # 使用jieba分詞，也可以不使用 seg_list = [i for i in seg_generator if i not in stopwords] seg_list = [i for i in seg_list if i != u' '] seg_list = r' '.join(seg_list) return seg_list importStopword(filename='./stopwords.txt') # 獲取當前文件路徑 # __file__ 為當前文件, 在ide中運行此行會報錯,可改為 # d = path.dirname('.') d = path.dirname(__file__) text = open(path.join(d, u'love.txt'),encoding ='utf-8').read() #如果是中文 text = processChinese(text)#中文不好分詞，使用Jieba分詞進行 # read the mask / color image # 設置背景圖片 back_coloring = imread(path.join(d, "./image/love.jpg")) wc = WordCloud( font_path='./font/cabin-sketch.bold.ttf ', #設置字體 要是使用漢字就用simhei.ttf background_color="white", #背景顏色 max_words=1000,# 詞雲顯示的最大詞數 mask=back_coloring,#設置背景圖片 max_font_size=80, #字體最大值 random_state=10, #42 ) # 生成詞雲, 可以用generate輸入全部文本(中文不好分詞),也可以我們計算好詞頻后使用generate_from_frequencies函數 wc.generate(text) # wc.generate_from_frequencies(txt_freq) # txt_freq例子為[('詞a', 100),('詞b', 90),('詞c', 80)] # 從背景圖片生成顏色值 image_colors = ImageColorGenerator(back_coloring) plt.figure() # 以下代碼顯示圖片 plt.imshow(wc) plt.axis("off") plt.show() # 繪制詞雲 # 保存圖片 wc.to_file(path.join(d, "名1稱.png"))
官方的samplecode給出的效果圖示例：
#!/usr/bin/env python """ Image-colored wordcloud ======================= You can color a word-cloud by using an image-based coloring strategy implemented in ImageColorGenerator. It uses the average color of the region occupied by the word in a source image. You can combine this with masking - pure-white will be interpreted as 'don't occupy' by the WordCloud object when passed as mask. If you want white as a legal color, you can just pass a different image to "mask", but make sure the image shapes line up. """ from os import path from PIL import Image import numpy as np import matplotlib.pyplot as plt from wordcloud import WordCloud, STOPWORDS, ImageColorGenerator d = path.dirname(__file__) # Read the whole text. text = open(path.join(d, 'alice.txt')).read() # read the mask / color image taken from # http://jirkavinse.deviantart.com/art/quot-Real-Life-quot-Alice-282261010 alice_coloring = np.array(Image.open(path.join(d, "alice_color.png"))) stopwords = set(STOPWORDS) stopwords.add("said") wc = WordCloud(background_color="white", max_words=2000, mask=alice_coloring, stopwords=stopwords, max_font_size=40, random_state=42) # generate word cloud wc.generate(text) # create coloring from image image_colors = ImageColorGenerator(alice_coloring) # show plt.imshow(wc, interpolation="bilinear")plt.axis("off") plt.figure() # recolor wordcloud and show # we could also give color_func=image_colors directly in the constructor plt.imshow(wc.recolor(color_func=image_colors), interpolation="bilinear") plt.axis("off") plt.figure() plt.imshow(alice_coloring, cmap=plt.cm.gray, interpolation="bilinear") plt.axis("off") plt.show()
最后感謝 http://blog.csdn.net/fyuanfena/article/details/52038984
和ta的項目源碼：https://github.com/fyuanfen/wordcloud
順便提一下
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