python安娜卡列妮娜詞雲圖製做

原文連接：​​​​​​​http://tecdat.cn/?p=6852

知識點普及

詞頻：某個詞在該文檔中出現的次數停用詞：數據處理時過濾掉某些字或詞，如：網站、的等語料庫：也就是咱們要分析的全部文檔的集合中文分詞：將漢字序列分紅一個個單獨的詞

使用第三方庫介紹

jieba jieba.cut(content) content 爲分詞的句子pandas pandas.DataFrame()生成DataFrame對象 pandas.DataFrame.groupby()分組統計 分組統計實例 pandas.DataFrame.groupby(by=列名數組)[統計列名數組].agg({ 統計項名稱:統計函數})wordcloudpython構建詞雲的庫文件 安裝方式請自行案例

詞雲實現

#!/usr/bin/env python
# coding=utf-8import osimport jiebaimport codecsimport pandas as pdimport numpy as npfrom wordcloud import WordCloud,ImageColorGeneratorimport matplotlib.pyplot as plt
#導入所用庫文件basefile = data存儲路徑
# 語料庫加載
f_in = codecs.open(basefile+'an.txt','r','utf-8') content = f_in.read()
#分詞,生成segments列表segments = []
segs = jieba.cut(content)for seg in segs: if len(seg)>1: segments.append(seg)
#生成DataFrame對象segmentDF = pd.DataFrame({'segment':segments})
#分組統計segStat = segmentDF.groupby( by = ['segment'] )['segment'].agg({ '計數':np.size}).reset_index().sort_values(by = ['計數'], ascending = False )
#加載停用詞 stopwords = pd.read_csv( "./StopwordsCN.txt", encoding='utf8', index_col=False)
#移除停用詞,並作去反操做fSegStat = segStat[ ~segStat.segment.isin(stopwords.stopword)]
#構建詞雲文件wordcloud = WordCloud( font_path='./simhei.ttf',
 #詞雲展現字體 background_color="black",
#詞雲展現背景顏色
)
words = fSegStat.set_index('segment').to_dict()wordcloud.fit_words(words['計數'])plt.imshow(wordcloud)plt.show()

效果展現

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AnnaKarenina

詞雲美化

from scipy.misc import imread
#讀取圖片背景
bimg = imread(basefile+'An.png')
wordcloud = WordCloud( background_color="white", mask=bimg, font_path='./simhei.ttf')wordcloud = wordcloud.fit_words(words['計數'])
#設置圖片大小
plt.figure( num=None, figsize=(8, 6), dpi=80, facecolor='w', edgecolor='k')
#獲取圖片顏色
bimgColors = ImageColorGenerator(bimg)plt.axis("off")
#重置詞雲顏色
plt.imshow(wordcloud.recolor(color_func=bimgColors))plt.show()