如何根據熊貓數據框中的頻率創建詞雲

Question

我必須繪制一個詞雲。 'tweets.csv' 是一個 Pandas 數據框，它有一個名為 'text' 的列。 繪制的圖表並非基於最常見的詞，tough。 單詞大小如何與其在數據框中的頻率相關聯？

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()

我的數據框如下所示：

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 ...

Answer 1

設置示例數據幀：

• 另請參閱DataCamp：在 Python 中生成 WordClouds
• WordCloud 上的 Python 文檔、 GitHib：wordcloud和Anaconda：wordcloud 的打包文檔

import pandas as pd

df = pd.DataFrame({'word': ['how', 'are', 'you', 'doing', 'this', 'afternoon'],
                   'count': [7, 10, 4, 1, 20, 100]}) 

        word  count
0        how      7
1        are     10
2        you      4
3      doing      1
4       this     20
5  afternoon    100

將word & count列轉換為dict

• WordCloud().generate_from_frequencies()需要一個dict
• 使用以下方法之一

# method 1: convert to dict 
data = dict(zip(df['word'].tolist(), df['count'].tolist()))

# method 2: convert to dict
data = df.set_index('word').to_dict()['count']

print(data)

[out]: {'how': 7, 'are': 10, 'you': 4, 'doing': 1, 'this': 20, 'afternoon': 100}                                                                          

詞雲：

• 使用.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)

陰謀

import matplotlib.pyplot as plt

plt.figure(figsize=(10, 10))
plt.imshow(wc, interpolation='bilinear')
plt.axis('off')
plt.show()

使用圖像蒙版：

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()