我必须画一个词云。 “ tweets.csv”是熊猫数据框,其中有一列名为“文本”。所绘制的图形并非基于最常用的单词,艰难。单词大小如何与数据帧中的频率联系起来?
text = df_final.text.values
wordcloud = WordCloud(
#mask = logomask,
max_words = 1000,
width = 600,
height = 400,
#max_font_size = 1000,
#min_font_size = 100,
normalize_plurals = True,
#scale = 5,
#relative_scaling = 0,
background_color = 'black',
stopwords = STOPWORDS.union(stopwords)
).generate(str(text))
fig = plt.figure(
figsize = (50,40),
facecolor = 'k',
edgecolor = 'k')
plt.imshow(wordcloud, interpolation = 'bilinear')
plt.axis('off')
plt.tight_layout(pad=0)
plt.show()
我的数据框如下:
0 RT @Pontifex_pt: Temos que descobrir as riquezezas ...
1 RT @Pontifex_pt: Todos estamos em viagem rumo ...
2 RT @Pontifex_pt: Unamos as forças, em todos ...
3 RT @GeneralMourao: #Segurançapública, preocupa ...
4 RT @FIFAcom: The Brasileirao U-17 final provided ...
答案 0 :(得分:2)
import pandas as pd
df = pd.DataFrame({'word': ['how', 'are', 'you', 'doing', 'this', 'afternoon'],
'count': [7, 10, 4, 1, 20, 100]})
word
和count
列转换为dict
WordCloud().generate_from_frequencies()
需要一个dict
data = dict(zip(df['word'].tolist(), df['count'].tolist()))
print(data)
>>> {'how': 7, 'are': 10, 'you': 4, 'doing': 1, 'this': 20, 'afternoon': 100}
.generate_from_frequencies
generate_from_frequencies(frequencies, max_font_size=None)
from wordcloud import WordCloud
wc = WordCloud(width=800, height=400, max_words=200).generate_from_frequencies(data)
import matplotlib.pyplot as plt
plt.figure(figsize=(10, 10))
plt.imshow(wc, interpolation='bilinear')
plt.axis('off')
plt.show()
twitter_mask = np.array(Image.open('twitter.png'))
wc = WordCloud(background_color='white', width=800, height=400, max_words=200, mask=twitter_mask).generate_from_frequencies(data_nyt)
plt.figure(figsize=(10, 10))
plt.imshow(wc, interpolation='bilinear')
plt.axis("off")
plt.figure()
plt.imshow(twitter_mask, cmap=plt.cm.gray, interpolation='bilinear')
plt.axis("off")
plt.show()