我正在尝试为tf-idf值形成一个词云:
以下是数据框中的tf-idf值。当我尝试形成一个词云时,值更高的值,在这种情况下"座位 - 2.57"以最大的字体显示。但我需要反之亦然。 "尼斯 - 2.088"拥有更大的字体,因为它更重要。
[[u'nice' 2.0886619578149417]
[u'owl' 2.2729656758128876]
[u'person' 2.386294361119891]
[u'read' 2.455287232606842]
[u'seat' 2.5766480896111092]]
以下是代码:
print(top_10.values)
d = {}
for a, x in top_10.values:
d[a] = x
import matplotlib.pyplot as plt
from wordcloud import WordCloud
wordcloud = WordCloud()
wordcloud.generate_from_frequencies(frequencies=d)
plt.figure( figsize=(20,10) )
plt.imshow(wordcloud, interpolation="bilinear")
plt.axis("off")
plt.show()
答案 0 :(得分:3)
您可以使用不同的频率提供给wordcloud。
E.g。
d[a] = 3-x
或
d[a] = 1./x
完整示例:
top_10 = lambda :""
top_10.values = [[u'nice', 2.0886619578149417],
[u'owl', 2.2729656758128876],
[u'person', 2.386294361119891],
[u'read', 2.455287232606842],
[u'seat', 2.5766480896111092]]
d = {}
for a, x in top_10.values:
d[a] = 3-x
import matplotlib.pyplot as plt
from wordcloud import WordCloud
wordcloud = WordCloud()
wordcloud.generate_from_frequencies(frequencies=d)
plt.figure( figsize=(5,3) )
plt.imshow(wordcloud, interpolation="bilinear")
plt.axis("off")
plt.show()